# Best Natural Language Understanding (NLU) Software

## How Many Natural Language Understanding (NLU) Software Products Does G2 Track?

**Total Products under this Category:** 79

### Category Stats (Aug 2026)

- **Average Rating:** 4.42/5 (↓0.01 vs Jul 2026) The average rating of products in this category, based on all submitted ratings
- **Top Trending Product:** Google NotebookLM (+0.21%) - Among all products in this category, Google NotebookLM recorded the largest rating increase compared to last month

_Last updated: August 02, 2026_

## How Does G2 Rank Natural Language Understanding (NLU) Software Products?

**Why You Can Trust G2's Software Rankings:**

- 30 Analysts and Data Experts
- 2,500+ Authentic Reviews
- 79+ Products
- Unbiased Rankings

G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category.

## G2 Grid® for Natural Language Understanding (NLU) Software
 ![G2 Grid® for Natural Language Understanding (NLU) Software plotting products by satisfaction and market presence](https://www.g2.com/categories/natural-language-understanding-nlu/grids.png?focus%5B%5D=1579500&focus%5B%5D=21473&focus%5B%5D=1562959&focus%5B%5D=52116&focus%5B%5D=21472&focus%5B%5D=113977&focus%5B%5D=77169&focus%5B%5D=1375562)

Highlighted products: Claude, Google Cloud Translation API, Microsoft 365 Copilot, Amazon Comprehend, Google Cloud Natural Language API, Google Cloud AutoML Natural Language, Deepgram, and Azure AI Language.

Underlying data: [Grid® JSON](https://www.g2.com/categories/natural-language-understanding-nlu/grids.json?focus%5B%5D=claude-2025-12-11&focus%5B%5D=google-cloud-translation-api&focus%5B%5D=microsoft-microsoft-365-copilot&focus%5B%5D=amazon-comprehend&focus%5B%5D=google-cloud-natural-language-api&focus%5B%5D=google-cloud-automl-natural-language&focus%5B%5D=deepgram&focus%5B%5D=azure-ai-language)

**Sponsored**

### Amazon SageMaker

Amazon SageMaker is a fully managed service that enables data scientists and developers to build, train, and deploy machine learning (ML) models at scale. It provides a comprehensive suite of tools and infrastructure, streamlining the entire ML workflow from data preparation to model deployment. With SageMaker, users can quickly connect to training data, select and optimize algorithms, and deploy models in a secure and scalable environment. Key Features and Functionality: - Integrated Development Environments (IDEs): SageMaker offers a unified, web-based interface with built-in IDEs, including JupyterLab and RStudio, facilitating seamless development and collaboration. - Pre-built Algorithms and Frameworks: It includes a selection of optimized ML algorithms and supports popular frameworks like TensorFlow, PyTorch, and Apache MXNet, allowing flexibility in model development. - Automated Model Tuning: SageMaker can automatically tune models to achieve optimal accuracy, reducing the time and effort required for manual adjustments. - Scalable Training and Deployment: The service manages the underlying infrastructure, enabling efficient training of models on large datasets and deploying them across auto-scaling clusters for high availability. - MLOps and Governance: SageMaker provides tools for monitoring, debugging, and managing ML models, ensuring robust operations and compliance with enterprise security standards. Primary Value and Problem Solved: Amazon SageMaker addresses the complexity and resource-intensive nature of developing and deploying ML models. By offering a fully managed environment with integrated tools and scalable infrastructure, it accelerates the ML lifecycle, reduces operational overhead, and enables organizations to derive insights and value from their data more efficiently. This empowers businesses to innovate rapidly and implement AI solutions without the need for extensive in-house expertise or infrastructure management.

[Visit website](https://www.g2.com/external_clickthroughs/record?secure%5Bad_program%5D=ppc&secure%5Bad_slot%5D=category_product_list_llm&secure%5Bcategory_id%5D=2270&secure%5Bchosen_at%5D=2026-08-03T23%3A36%3A45Z&secure%5Bdisplayable_resource_id%5D=2270&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=2270&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=52115&secure%5Bresource_id%5D=2270&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fnatural-language-understanding-nlu%3Fopen_modal_url%3D%252Fproducts%252Fgoogle-notebooklm%252Fwishlists%253Fhost_path%253D%25252Fcategories%25252Fnatural-language-understanding-nlu%2526source%253Dcategory&secure%5Btoken%5D=4fc87fb2b40b5e0fa84a700cda9eb8dc4896601d41ac1585a2140492ab90f991&secure%5Burl%5D=https%3A%2F%2Faws.amazon.com%2Fsagemaker%2F%3Ftrk%3De054ba95-b51d-4594-98bc-aa0239b1797a%26sc_channel%3Ddisplay%2Bads&secure%5Burl_type%5D=custom_url)

### [Claude](https://www.g2.com/products/claude-2025-12-11/reviews)

Claude is a state-of-the-art large language model (LLM) developed by Anthropic, designed to serve as a helpful, honest, and harmless AI assistant. With its advanced reasoning capabilities and conversational tone, Claude excels in tasks ranging from complex coding to in-depth financial analysis, making it a versatile tool for developers, enterprises, and financial professionals. Key Features and Functionality: - Advanced Coding Capabilities: Claude Opus 4 leads in coding performance, achieving top scores on benchmarks like SWE-bench and Terminal-bench. It supports sustained, long-running tasks, enabling continuous work for several hours, which is ideal for complex software development projects. - Financial Analysis Tools: Claude integrates seamlessly with financial data platforms such as Databricks and Snowflake, providing a unified interface for market analysis, research, and investment decision-making. It offers direct hyperlinks to source materials for instant verification, enhancing the efficiency of financial workflows. - Extended Context Windows: With an enhanced 500k context window available in Claude Sonnet 4, users can upload extensive documents, including hundreds of sales transcripts or large codebases, facilitating comprehensive analysis and collaboration. - Tool Use and Integration: Claude's extended thinking capabilities allow it to utilize tools like web search during reasoning processes, improving response accuracy. It also supports background tasks via GitHub Actions and integrates natively with development environments like VS Code and JetBrains for seamless pair programming. - Enterprise-Grade Security: The Claude Enterprise plan offers advanced security features, including Single Sign-On (SSO), Just-in-Time Provisioning (JIT), role-based permissions, audit logs, and custom data retention controls, ensuring data safety and compliance for organizations. Primary Value and User Solutions: Claude addresses the need for a reliable and intelligent AI assistant capable of handling complex tasks across various domains. For developers, it enhances productivity through advanced coding support and integration with development tools. Financial professionals benefit from its ability to unify and analyze diverse data sources, streamlining research and decision-making processes. Enterprises gain from its scalable solutions and robust security features, enabling efficient and secure deployment of AI capabilities within their operations. Overall, Claude empowers users to achieve higher efficiency, accuracy, and innovation in their respective fields.

**Average Rating:** 4.6/5.0

**Total Reviews:** 409

#### How Do G2 Users Rate Claude?

- **Summarization:** 9.9/10 (Category avg: 9.0/10)
- **Language Detection:** 9.4/10 (Category avg: 8.8/10)
- **Part of Speech Tagging:** 9.0/10 (Category avg: 8.7/10)
- **Quality of Support:** 8.1/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Claude?

- **Seller:** [Anthropic](https://www.g2.com/sellers/anthropic-b3e27488-b6f4-49c9-a8c7-d860a4207ff3)
- **HQ Location:** San Francisco, California
- **Twitter:** @AnthropicAI  
1,440,248 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=f77a1b8402d5e638c3ef9380f68189346d52f732c0a71bc7354dd50d5f3763e8&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fanthropicresearch%2F&secure%5Burl_type%5D=linkedin_company_website)  
5,178 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Software Engineer, Data Analyst
- **Top Industries:** Computer Software, Information Technology and Services
- **Company Size:** 52% Small, 34% Medium

#### What Do G2 Reviewers Say About Claude?

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **ease of use** of Claude, enabling them to create clear and structured educational content effortlessly.
- Users commend Claude for its **ability to maintain long, deep discussions** , enhancing their intellectual and creative projects.
- Users find Claude to be **exceptionally helpful** for deep discussions and managing various intellectual tasks effectively.
- Users value the **accurate results** provided by Claude, enhancing their efficiency and experience with the tool.
- Users value Claude's **clear and structured communication** , enhancing their ability to educate and inform effectively.

##### Cons

- Users find **usage limitations** frustrating, especially with access restrictions and inconsistent performance impacting their experience.
- Users find Claude has **significant limitations** in visual content support, integration, and responsiveness, affecting efficiency and creativity.
- Users find Claude's **limited functionality** restrictive, particularly in visual content support and research speed.
- Users find Claude overly cautious and **slow to respond** , which can hinder quick and efficient communication.
- Users express concern over **resource limitations** like token usage and search caps, affecting productivity significantly.

#### What Are Recent G2 Reviews of Claude?

**["Claude Desktop Feels Like a True Coding Partner for Large Codebases"](https://www.g2.com/survey_responses/claude-review-13195714)**

**Rating:** 4.5/5.0 stars

_— Sree K._

[Read full review](https://www.g2.com/survey_responses/claude-review-13195714)

**["Claude’s Impressive Coding and Reasoning—A Real Time-Saver for Engineers"](https://www.g2.com/survey_responses/claude-review-13166368)**

**Rating:** 4.0/5.0 stars

_— Darshil M._

[Read full review](https://www.g2.com/survey_responses/claude-review-13166368)

### [Google Cloud Translation API](https://www.g2.com/fr/products/google-cloud-translation-api/reviews)

Votre contenu et vos applications multilingues avec une traduction automatique rapide et dynamique disponible dans des milliers de paires de langues.

**Average Rating:** 4.4/5.0

**Total Reviews:** 364

#### How Do G2 Users Rate Google Cloud Translation API?

- **Résumé:** 8.7/10 (Category avg: 9.0/10)
- **Détection de langue:** 8.9/10 (Category avg: 8.8/10)
- **Partie du balisage vocal:** 8.8/10 (Category avg: 8.7/10)
- **Qualité du support:** 8.5/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Google Cloud Translation API?

- **Vendeur:** [Google](https://www.g2.com/fr/sellers/google)
- **Année de fondation:** 1998
- **Emplacement du siège social:** Mountain View, CA
- **Twitter:** @google  
31,899,995 abonnés Twitter
- **Page LinkedIn®:** [www.linkedin.com](https://www.g2.com/fr/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=fe4a5936665c9702418dd53c477fef5a7baea08078bb117ed67e966fc581b9ec&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1441%2F&secure%5Burl_type%5D=linkedin_company_website)  
341,888 employés sur LinkedIn®
- **Propriété:** NASDAQ:GOOG

#### Who Uses This Product?

- **Who Uses This:** Ingénieur logiciel, Ingénieur de données
- **Top Industries:** Logiciels informatiques, Technologie de l'information et services
- **Company Size:** 53% Small, 24% Large

#### What Do G2 Reviewers Say About Google Cloud Translation API?

_AI-generated summary from verified user reviews_

##### Pros

- Les utilisateurs louent la **qualité impressionnante et la précision** des traductions de l'API Google Cloud Translation, appréciant son intégration rapide.
- Les utilisateurs trouvent la **facilité d'utilisation** de l'API de traduction Google Cloud inestimable pour des traductions rapides et efficaces.
- Les utilisateurs apprécient la **précision remarquable** de l'API de traduction Google Cloud, profitant de traductions efficaces et précises dans de nombreuses langues.
- Les utilisateurs apprécient le **soutien multilingue étendu** de l'API de traduction Google Cloud, améliorant ainsi la communication mondiale sans effort.
- Les utilisateurs apprécient la **haute précision et la détection automatique des langues** de l'API de traduction Google Cloud pour une communication mondiale efficace.

##### Cons

- Les utilisateurs trouvent que **la précision de la traduction est insuffisante** , surtout avec les dialectes locaux et l'argot, ce qui conduit à des expériences frustrantes.
- Les utilisateurs expriment des préoccupations concernant les **prix élevés** , surtout pour les grands volumes et les options limitées de niveau gratuit.
- Les utilisateurs expriment des préoccupations concernant les **problèmes de précision** de l'API de traduction de Google Cloud, entraînant des traductions incohérentes entre les langues.
- Les utilisateurs constatent que **les coûts d'abonnement peuvent s'accumuler rapidement** en cas d'utilisation intensive, limitant ainsi l'accessibilité et la flexibilité.
- Les utilisateurs rencontrent des **problèmes de traduction** avec le contexte et les dialectes locaux, affectant la fiabilité et l'utilisabilité de l'API.

#### What Are Recent G2 Reviews of Google Cloud Translation API?

**["Traduction fiable et rapide avec une intégration facile"](https://www.g2.com/fr/survey_responses/google-cloud-translation-api-review-13188612)**

**Rating:** 4.5/5.0 stars

_— Affan A._

[Read full review](https://www.g2.com/fr/survey_responses/google-cloud-translation-api-review-13188612)

**["Traductions rapides et précises avec une intégration transparente à Google Cloud"](https://www.g2.com/fr/survey_responses/google-cloud-translation-api-review-13186992)**

**Rating:** 4.5/5.0 stars

_— Subhashree S._

[Read full review](https://www.g2.com/fr/survey_responses/google-cloud-translation-api-review-13186992)

#### What Are G2 Users Discussing About Google Cloud Translation API?

- [What advice do you have for developers considering Google Cloud Translation API for multilingual applications?](https://www.g2.com/fr/discussions/what-advice-do-you-have-for-developers-considering-google-cloud-translation-api-for-multilingual-applications)
- [À quoi sert l'API de traduction Google Cloud ?](https://www.g2.com/fr/discussions/what-is-google-cloud-translation-api-used-for) - 1 upvote

### [Microsoft 365 Copilot](https://www.g2.com/products/microsoft-microsoft-365-copilot/reviews)

Microsoft 365 Copilot is a generative AI assistant for work that’s built into the Microsoft 365 apps people use every day—like Word, Excel, PowerPoint, Outlook, and Teams. It helps you stay in the flow of work by turning your ideas, content, and data into action. Powered by Work IQ, Copilot connects the dots across your work—bringing together your emails, files, meetings, and conversations to deliver more relevant, contextual, and personalized assistance. It understands how work gets done in your organization and adapts to your role, priorities, and patterns over time. Copilot works alongside you to help draft content, analyze data, summarize meetings, and automate tasks—so you can move faster and focus on what matters most. Because it’s built directly into the apps you already use, there’s no need to switch tools or start from scratch. Copilot also inherits Microsoft 365 security, privacy, and compliance controls, so it only surfaces information users are authorized to access while keeping your data protected. By combining AI with the tools and data organizations already rely on, Microsoft 365 Copilot helps people work smarter, move faster, and get more done. Apps like Word, Excel, PowerPoint, Outlook, Teams, and Loop work with Copilot to support users in the context of their work. For example, Copilot in Word helps users create, understand, and edit documents. By using Microsoft 365 Copilot Chat, you can draft content, review what you missed, and get answers to questions by using open-ended prompts. This information is securely grounded in your work data. Copilot Search is an AI-powered universal search experience across all your Microsoft 365 applications and connected non-Microsoft data sources. It's integrated with Microsoft 365 Copilot, so users can find the results they need by using search, then seamlessly transition to chat for deeper exploration or follow-up task completion. Out of the box agents like Facilitator, Interpreter, or Channels help support meeting logistics, communication, and collaboration in Microsoft Teams.

**Average Rating:** 4.2/5.0

**Total Reviews:** 61

#### How Do G2 Users Rate Microsoft 365 Copilot?

- **Summarization:** 8.3/10 (Category avg: 9.0/10)
- **Quality of Support:** 8.7/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Microsoft 365 Copilot?

- **Seller:** [Microsoft](https://www.g2.com/sellers/microsoft)
- **Company Website:** www.microsoft.com
- **Year Founded:** 1975
- **HQ Location:** Redmond, Washington
- **Twitter:** @microsoft  
13,091,739 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=9458f51bd6ded48ad432a804f19ad736469f007787569b63827154231c315630&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fmicrosoft%2F&secure%5Burl_type%5D=linkedin_company_website)  
231,632 employees on LinkedIn®

#### Who Uses This Product?

- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 35% Large, 31% Medium

#### What Are Recent G2 Reviews of Microsoft 365 Copilot?

**["Seamless Microsoft Ecosystem Integration That Boosts Productivity"](https://www.g2.com/survey_responses/microsoft-365-copilot-review-13197261)**

**Rating:** 4.0/5.0 stars

_— Eyad B._

[Read full review](https://www.g2.com/survey_responses/microsoft-365-copilot-review-13197261)

**["Microsoft 365 Copilot: A Practical Time-Saver for Writing, Docs, and Summaries"](https://www.g2.com/survey_responses/microsoft-365-copilot-review-13171008)**

**Rating:** 4.5/5.0 stars

_— Sree K._

[Read full review](https://www.g2.com/survey_responses/microsoft-365-copilot-review-13171008)

### [Amazon Comprehend](https://www.g2.com/products/amazon-comprehend/reviews)

Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to find insights and relationships in text. Amazon Comprehend identifies the language of the text; extracts key phrases, places, people, brands, or events; understands how positive or negative the text is; and automatically organizes a collection of text files by topic.

**Average Rating:** 4.3/5.0

**Total Reviews:** 83

#### How Do G2 Users Rate Amazon Comprehend?

- **Summarization:** 8.6/10 (Category avg: 9.0/10)
- **Language Detection:** 8.3/10 (Category avg: 8.8/10)
- **Part of Speech Tagging:** 8.8/10 (Category avg: 8.7/10)
- **Quality of Support:** 8.5/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Amazon Comprehend?

- **Seller:** [Amazon Web Services (AWS)](https://www.g2.com/sellers/amazon-web-services-aws-3e93cc28-2e9b-4961-b258-c6ce0feec7dd)
- **Year Founded:** 2006
- **HQ Location:** Seattle, WA
- **Twitter:** @awscloud  
2,232,483 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=072881eee28a2afe24f8d1bda9f20e3e146b9fb4b214f216411ce2ed6898b31e&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Famazon-web-services%2F&secure%5Burl_type%5D=linkedin_company_website)  
147,094 employees on LinkedIn®
- **Ownership:** NASDAQ: AMZN

#### Who Uses This Product?

- **Top Industries:** Information Technology and Services, Accounting
- **Company Size:** 40% Medium, 39% Small

#### What Do G2 Reviewers Say About Amazon Comprehend?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **data protection** features of Amazon Comprehend, ensuring sensitive information is managed securely.
- Users value the **valuable insights** that Amazon Comprehend provides, making data analysis from text simpler and more efficient.
- Users appreciate the **ease of use** of Amazon Comprehend, enabling valuable insights without needing machine learning experience.
- Users appreciate the **valuable insights extraction** capability of Amazon Comprehend, enhancing their data analysis processes efficiently.
- Users value the **insightful text analysis** capabilities of Amazon Comprehend, enhancing understanding from various textual sources.

##### Cons

- Users find that **accuracy issues** arise without sufficient training data, impacting insights and increasing costs significantly.
- Users find the **cost of Amazon Comprehend high** , particularly when dealing with large volumes of data for analysis.
- Users find that **insufficient training** can limit accuracy and raise costs for high-volume data processing with Amazon Comprehend.

#### What Are Recent G2 Reviews of Amazon Comprehend?

**["Accurate Pre-Trained NLP Models with Seamless PII Redaction"](https://www.g2.com/survey_responses/amazon-comprehend-review-12955644)**

**Rating:** 4.5/5.0 stars

_— Ruchi P._

[Read full review](https://www.g2.com/survey_responses/amazon-comprehend-review-12955644)

**["Powerful, Easy-to-Integrate NLP Insights with Amazon Comprehend"](https://www.g2.com/survey_responses/amazon-comprehend-review-13187739)**

**Rating:** 4.0/5.0 stars

_— Atharva P._

[Read full review](https://www.g2.com/survey_responses/amazon-comprehend-review-13187739)

### [Google Cloud Natural Language API](https://www.g2.com/fr/products/google-cloud-natural-language-api/reviews)

Derive des insights à partir de texte non structuré en utilisant l'apprentissage automatique de Google.

**Average Rating:** 4.3/5.0

**Total Reviews:** 100

#### How Do G2 Users Rate Google Cloud Natural Language API?

- **Résumé:** 8.6/10 (Category avg: 9.0/10)
- **Détection de langue:** 8.9/10 (Category avg: 8.8/10)
- **Partie du balisage vocal:** 8.6/10 (Category avg: 8.7/10)
- **Qualité du support:** 8.7/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Google Cloud Natural Language API?

- **Vendeur:** [Google](https://www.g2.com/fr/sellers/google)
- **Année de fondation:** 1998
- **Emplacement du siège social:** Mountain View, CA
- **Twitter:** @google  
31,899,995 abonnés Twitter
- **Page LinkedIn®:** [www.linkedin.com](https://www.g2.com/fr/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=fe4a5936665c9702418dd53c477fef5a7baea08078bb117ed67e966fc581b9ec&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1441%2F&secure%5Burl_type%5D=linkedin_company_website)  
341,888 employés sur LinkedIn®
- **Propriété:** NASDAQ:GOOG

#### Who Uses This Product?

- **Who Uses This:** Ingénieur logiciel
- **Top Industries:** Logiciels informatiques, Technologie de l'information et services
- **Company Size:** 55% Small, 23% Large

#### What Do G2 Reviewers Say About Google Cloud Natural Language API?

_AI-generated summary from verified user reviews_

##### Pros

- Les utilisateurs apprécient la **capacité de téléchargement de la base de données** de l'API Google Cloud Natural Language, améliorant la prise de décision dans les services de santé.
- Les utilisateurs apprécient la **gestion efficace des données** de l'API Google Cloud Natural Language, améliorant la prise de décision dans les services de santé.
- Les utilisateurs adorent le **support de téléchargement de base de données** de l'API Google Cloud Natural Language, améliorant la prise de décision dans diverses applications.

##### Cons

- Les utilisateurs trouvent **l'interface peu conviviale** , ce qui rend difficile la compréhension et l'utilisation efficace de l'API.

#### What Are Recent G2 Reviews of Google Cloud Natural Language API?

**["Un choix solide pour l'analyse de texte et la détection des sentiments"](https://www.g2.com/fr/survey_responses/google-cloud-natural-language-api-review-13174091)**

**Rating:** 4.5/5.0 stars

_— Jeni J._

[Read full review](https://www.g2.com/fr/survey_responses/google-cloud-natural-language-api-review-13174091)

**["Informations textuelles rapides et précises avec l'API Google Cloud Natural Language"](https://www.g2.com/fr/survey_responses/google-cloud-natural-language-api-review-13188869)**

**Rating:** 4.5/5.0 stars

_— Anjaly T._

[Read full review](https://www.g2.com/fr/survey_responses/google-cloud-natural-language-api-review-13188869)

### [Google Cloud AutoML Natural Language](https://www.g2.com/products/google-cloud-automl-natural-language/reviews)

The powerful pre-trained models of the Natural Language API let developers work with natural language understanding features including sentiment analysis, entity analysis, entity sentiment analysis, content classification, and syntax analysis.

**Average Rating:** 4.5/5.0

**Total Reviews:** 18

#### How Do G2 Users Rate Google Cloud AutoML Natural Language?

- **Summarization:** 9.0/10 (Category avg: 9.0/10)
- **Language Detection:** 8.3/10 (Category avg: 8.8/10)
- **Part of Speech Tagging:** 8.6/10 (Category avg: 8.7/10)
- **Quality of Support:** 8.6/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Google Cloud AutoML Natural Language?

- **Seller:** [Google](https://www.g2.com/sellers/google)
- **Year Founded:** 1998
- **HQ Location:** Mountain View, CA
- **Twitter:** @google  
31,899,995 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=fe4a5936665c9702418dd53c477fef5a7baea08078bb117ed67e966fc581b9ec&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1441%2F&secure%5Burl_type%5D=linkedin_company_website)  
341,888 employees on LinkedIn®
- **Ownership:** NASDAQ:GOOG

#### Who Uses This Product?

- **Company Size:** 61% Small, 22% Large

#### What Are Recent G2 Reviews of Google Cloud AutoML Natural Language?

**["Easy No-Code Training with Custom Data Uploads"](https://www.g2.com/survey_responses/google-cloud-automl-natural-language-review-13193104)**

**Rating:** 5.0/5.0 stars

_— Dulce G._

[Read full review](https://www.g2.com/survey_responses/google-cloud-automl-natural-language-review-13193104)

**["Accurate, Custom Text Classification with Smooth Google Cloud Integration"](https://www.g2.com/survey_responses/google-cloud-automl-natural-language-review-13179214)**

**Rating:** 4.5/5.0 stars

_— Muhammed A._

[Read full review](https://www.g2.com/survey_responses/google-cloud-automl-natural-language-review-13179214)

#### What Are G2 Users Discussing About Google Cloud AutoML Natural Language?

- [What is Google Cloud Natural Language API?](https://www.g2.com/discussions/google-cloud-automl-natural-language-what-is-google-cloud-natural-language-api)
- [What is Google Cloud Natural Language API?](https://www.g2.com/discussions/what-is-google-cloud-natural-language-api)
- [Does Google use natural language processing?](https://www.g2.com/discussions/does-google-use-natural-language-processing)
- [What can AutoML be used for?](https://www.g2.com/discussions/what-can-automl-be-used-for)
- [What is Google AutoML natural language?](https://www.g2.com/discussions/what-is-google-automl-natural-language) - 1 comment, 1 upvote

### [Deepgram](https://www.g2.com/fr/products/deepgram/reviews)

Plateforme d'IA vocale d'entreprise conçue pour les développeurs créant des produits axés sur la voix en utilisant des API de reconnaissance vocale, de synthèse vocale ou de conversion vocale. Plus de 200 000 développeurs construisent avec les modèles fondamentaux natifs de la voix de Deepgram, accessibles via des API ou des logiciels autogérés. Au-delà de cela, les développeurs peuvent : 🔊 Traiter l'audio en direct ou préenregistré avec une précision supérieure 🗣️ Convertir le texte en voix IA naturelle pour des cas d'utilisation d'entreprise avec la synthèse vocale 🌎 Transcrire avec précision l'audio en plus de 36 langues ⚙️ Entraîner des modèles personnalisés pour des cas d'utilisation uniques 🔑 Accéder à une compréhension du langage naturel approfondie avec une API unifiée 💻 Construire dans n'importe quel langage de programmation avec nos SDK ✅ Déployer sur site ou sur le cloud géré de DG 📈 Obtenir une infrastructure GPU évolutive pour l'entraînement et l'inférence

**Average Rating:** 4.6/5.0

**Total Reviews:** 467

#### How Do G2 Users Rate Deepgram?

- **Résumé:** 10.0/10 (Category avg: 9.0/10)
- **Détection de langue:** 10.0/10 (Category avg: 8.8/10)
- **Partie du balisage vocal:** 10.0/10 (Category avg: 8.7/10)
- **Qualité du support:** 8.8/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Deepgram?

- **Vendeur:** [Deepgram](https://www.g2.com/fr/sellers/deepgram)
- **Site Web de l'entreprise:** deepgram.com
- **Année de fondation:** 2015
- **Emplacement du siège social:** San Francisco, California
- **Twitter:** @DeepgramAI  
10,837 abonnés Twitter
- **Page LinkedIn®:** [www.linkedin.com](https://www.g2.com/fr/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=6a4f09519882843ef34c69f2628a3c6c1cc8fa6dbc3212cdb2bd60ad3ad50f36&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fdeepgram%2F&secure%5Burl_type%5D=linkedin_company_website)  
325 employés sur LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Ingénieur logiciel, PDG
- **Top Industries:** Logiciels informatiques, Technologie de l'information et services
- **Company Size:** 80% Small, 19% Medium

#### What Do G2 Reviewers Say About Deepgram?

_AI-generated summary from verified user reviews_

##### Pros

- Les utilisateurs soulignent la **haute précision** de Deepgram, appréciant ses capacités de transcription vocale rapides et fiables.
- Les utilisateurs louent les **transcriptions rapides et fiables** de Deepgram, ce qui leur permet de gagner considérablement du temps dans leurs flux de travail.
- Les utilisateurs apprécient la **facilité d'utilisation** de Deepgram, grâce à son API simple et à son support linguistique étendu.
- Les utilisateurs louent la **précision excellente de la transcription** de Deepgram, bénéficiant constamment de ses capacités efficaces de traitement audio.
- Les utilisateurs louent Deepgram pour sa **transcription en temps réel rapide et précise** , améliorant diverses applications comme l'analyse des appels et le sous-titrage.

##### Cons

- Les utilisateurs notent un **manque de support linguistique** dans Deepgram, limitant l'utilisabilité et la polyvalence pour les audiences mondiales.
- Les utilisateurs trouvent les **problèmes de tarification** de Deepgram préoccupants, surtout pour les grands projets et les startups avec des budgets limités.
- Les utilisateurs trouvent que **les prix sont un peu élevés** pour les grands projets, ce qui rend cela difficile pour les startups et les étudiants.
- Les utilisateurs rencontrent des **problèmes d'inexactitude** avec Deepgram, y compris des mots manquants et un support linguistique limité affectant la qualité de la transcription.
- Les utilisateurs remarquent le **soutien linguistique limité** dans Deepgram, bien que des améliorations soient en cours pour élargir les options.

#### What Are Recent G2 Reviews of Deepgram?

**["Grande valeur STT/TTS avec des fonctionnalités puissantes de Nova 3 et une intégration facile"](https://www.g2.com/fr/survey_responses/deepgram-review-13198079)**

**Rating:** 4.5/5.0 stars

_— Akshay M._

[Read full review](https://www.g2.com/fr/survey_responses/deepgram-review-13198079)

**["Le service de reconnaissance vocale le plus rapide que j'ai jamais utilisé !"](https://www.g2.com/fr/survey_responses/deepgram-review-6632115)**

**Rating:** 5.0/5.0 stars

_— D Santhosh K._

[Read full review](https://www.g2.com/fr/survey_responses/deepgram-review-6632115)

#### What Are G2 Users Discussing About Deepgram?

- [À quoi sert Deepgram ?](https://www.g2.com/fr/discussions/what-is-deepgram-used-for) - 1 comment

### [Azure AI Language](https://www.g2.com/products/azure-ai-language/reviews)

Azure AI Language is a managed service for developing natural language processing applications. Identify key terms and phrases, analyze sentiment, summarize text, and build conversational interfaces. Use Language to annotate, train, evaluate, and deploy customizable AI models with minimal machine-learning expertise.

**Average Rating:** 4.3/5.0

**Total Reviews:** 79

#### How Do G2 Users Rate Azure AI Language?

- **Summarization:** 8.3/10 (Category avg: 9.0/10)
- **Language Detection:** 8.6/10 (Category avg: 8.8/10)
- **Part of Speech Tagging:** 8.1/10 (Category avg: 8.7/10)
- **Quality of Support:** 8.4/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Azure AI Language?

- **Seller:** [Microsoft](https://www.g2.com/sellers/microsoft)
- **Year Founded:** 1975
- **HQ Location:** Redmond, Washington
- **Twitter:** @microsoft  
13,091,739 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=9458f51bd6ded48ad432a804f19ad736469f007787569b63827154231c315630&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fmicrosoft%2F&secure%5Burl_type%5D=linkedin_company_website)  
231,632 employees on LinkedIn®
- **Ownership:** MSFT

#### Who Uses This Product?

- **Top Industries:** Computer Software, Information Technology and Services
- **Company Size:** 42% Small, 32% Large

#### What Are Recent G2 Reviews of Azure AI Language?

**["Azure AI Language Helps Us Understand Customer Sentiment and Respond More Warmly"](https://www.g2.com/survey_responses/azure-ai-language-review-12862917)**

**Rating:** 4.5/5.0 stars

_— Somashekar N._

[Read full review](https://www.g2.com/survey_responses/azure-ai-language-review-12862917)

**["Powerful, Easy-to-Implement NLP Insights with Azure AI"](https://www.g2.com/survey_responses/azure-ai-language-review-13017464)**

**Rating:** 4.5/5.0 stars

_— Rafee N._

[Read full review](https://www.g2.com/survey_responses/azure-ai-language-review-13017464)

#### What Are G2 Users Discussing About Azure AI Language?

- [What is Azure QnA Maker API used for?](https://www.g2.com/discussions/what-is-azure-qna-maker-api-used-for)
- [What is API in Microsoft Azure?](https://www.g2.com/discussions/what-is-api-in-microsoft-azure) - 1 comment

### [Google NotebookLM](https://www.g2.com/products/google-notebooklm/reviews)

The ultimate tool for understanding the information that matters most to you, built with Gemini 2.0

**Average Rating:** 4.8/5.0

**Total Reviews:** 19

#### How Do G2 Users Rate Google NotebookLM?

- **Summarization:** 9.9/10 (Category avg: 9.0/10)
- **Language Detection:** 8.3/10 (Category avg: 8.8/10)
- **Part of Speech Tagging:** 8.1/10 (Category avg: 8.7/10)
- **Quality of Support:** 9.7/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Google NotebookLM?

- **Seller:** [Google](https://www.g2.com/sellers/google-f3801d18-1641-4e22-99de-30e7422a874d)
- **HQ Location:** N/A
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=7886df2ed926834e5eb248c77dcfa8e5c815d3ab1f0fe3132ced0dba45868834&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2FNo-Linkedin-Presence-Added-Intentionally-By-DataOps&secure%5Burl_type%5D=linkedin_company_website)  
1 employees on LinkedIn®

#### Who Uses This Product?

- **Company Size:** 42% Small, 37% Medium

#### What Do G2 Reviewers Say About Google NotebookLM?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **visual content creation** features of Google NotebookLM, enhancing understanding and engagement with learning materials.
- Users highlight the **efficiency** of Google NotebookLM in enhancing collaboration and productivity through easy note tracking and sharing.
- Users appreciate the **AI-driven insights** of Google NotebookLM, enhancing collaboration and boosting decision-making efficiency.
- Users appreciate the **visual learning support** of Google NotebookLM, enhancing understanding through videos, flashcards, and mental maps.
- Users love the **intuitive user interface** of Google NotebookLM, making research and insights extraction seamless and enjoyable.

##### Cons

- Users are frustrated by **inefficient file management** as chat history can be lost, impacting their experience.
- Users report **language limitations** in Google NotebookLM, lacking subtitle options and specific English accents like Indian English.
- Users face challenges with **limited language support** , as features like subtitles and regional accents are missing.
- Users find the **poor response quality** of Google NotebookLM's male voice to be repetitive and in need of improvement.

#### What Are Recent G2 Reviews of Google NotebookLM?

**["Fast, Clean Summaries and Notes Across PDFs, Videos, and More"](https://www.g2.com/survey_responses/google-notebooklm-review-12862814)**

**Rating:** 5.0/5.0 stars

_— Saumy V._

[Read full review](https://www.g2.com/survey_responses/google-notebooklm-review-12862814)

**["NotebookLM Turns Team Docs Into a Shared, Question-Answerable Knowledge Base"](https://www.g2.com/survey_responses/google-notebooklm-review-12853687)**

**Rating:** 5.0/5.0 stars

_— Bindu Madhuri J._

[Read full review](https://www.g2.com/survey_responses/google-notebooklm-review-12853687)

### [Stanford CoreNLP](https://www.g2.com/products/stanford-corenlp/reviews)

Stanford CoreNLP provides a set of natural language analysis tools that can give the base forms of words, their parts of speech, whether they are names of companies, people, etc., normalize dates, times, and numeric quantities, and mark up the structure of sentences in terms of phrases and word dependencies, indicate which noun phrases refer to the same entities, indicate sentiment, extract open-class relations between mentions, etc.

**Average Rating:** 4.3/5.0

**Total Reviews:** 10

#### How Do G2 Users Rate Stanford CoreNLP?

- **Quality of Support:** 6.7/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Stanford CoreNLP?

- **Seller:** [Stanford NLP Group](https://www.g2.com/sellers/stanford-nlp-group)
- **HQ Location:** Stanford, CA
- **Twitter:** @stanfordnlp  
187,198 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=7886df2ed926834e5eb248c77dcfa8e5c815d3ab1f0fe3132ced0dba45868834&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2FNo-Linkedin-Presence-Added-Intentionally-By-DataOps&secure%5Burl_type%5D=linkedin_company_website)  
1 employees on LinkedIn®

#### Who Uses This Product?

- **Company Size:** 60% Small, 20% Medium

#### What Are Recent G2 Reviews of Stanford CoreNLP?

**["Natural Language parser with an ivy league touch"](https://www.g2.com/survey_responses/stanford-corenlp-review-1677049)**

**Rating:** 4.5/5.0 stars

_— Verified User in Management Consulting_

[Read full review](https://www.g2.com/survey_responses/stanford-corenlp-review-1677049)

**["Develop a Working Understanding of Natural Langauge Processing"](https://www.g2.com/survey_responses/stanford-corenlp-review-2157709)**

**Rating:** 4.5/5.0 stars

_— Verified User in Online Media_

[Read full review](https://www.g2.com/survey_responses/stanford-corenlp-review-2157709)

### [scite.ai](https://www.g2.com/fr/products/scite-ai/reviews)

scite est un outil de recherche primé qui aide les utilisateurs à mieux découvrir, comprendre et évaluer la recherche grâce aux Smart Citations. Les Smart Citations affichent le contexte de la citation et décrivent si l'article fournit des preuves à l'appui ou des preuves contradictoires.

**Average Rating:** 4.7/5.0

**Total Reviews:** 27

#### How Do G2 Users Rate scite.ai?

- **Résumé:** 8.5/10 (Category avg: 9.0/10)
- **Détection de langue:** 8.5/10 (Category avg: 8.8/10)
- **Partie du balisage vocal:** 6.9/10 (Category avg: 8.7/10)
- **Qualité du support:** 8.8/10 (Category avg: 8.7/10)

#### Who Is the Company Behind scite.ai?

- **Vendeur:** [scite.ai](https://www.g2.com/fr/sellers/scite-ai)
- **Année de fondation:** 2018
- **Emplacement du siège social:** New York, US
- **Page LinkedIn®:** [www.linkedin.com](https://www.g2.com/fr/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=e68bcede3c60a1362a89f1b65e709076684aa2fbff0ed3ecbf797f9af00e3f00&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fsciteai%2F&secure%5Burl_type%5D=linkedin_company_website)  
5 employés sur LinkedIn®

#### Who Uses This Product?

- **Top Industries:** Recherche, Enseignement supérieur
- **Company Size:** 52% Small, 11% Medium

#### What Do G2 Reviewers Say About scite.ai?

_AI-generated summary from verified user reviews_

##### Pros

- Les utilisateurs apprécient la **base de données étendue et les outils de visualisation** de scite.ai, rendant les revues de littérature efficaces et perspicaces.
- Les utilisateurs trouvent scite.ai **incroyablement facile à utiliser** , améliorant ainsi leur efficacité de recherche et leur processus de revue de littérature.
- Les utilisateurs apprécient la **haute précision** des résumés de citations de scite.ai, offrant confiance et fiabilité dans les résultats de recherche.
- Les utilisateurs trouvent que scite.ai améliore considérablement **l'efficacité** dans les revues de littérature, rationalisant la recherche et améliorant le processus d'écriture.
- Les utilisateurs trouvent que scite.ai est un **assistant personnel de recherche précieux** , améliorant leur processus de revue de littérature avec des références fiables.

##### Cons

- Les utilisateurs rencontrent une **performance lente** avec scite.ai, ce qui peut interrompre le flux de travail et nuire à l'expérience utilisateur.
- Les utilisateurs rencontrent des **problèmes de vitesse de réponse** avec l'interface de scite.ai, ce qui limite son efficacité globale et la satisfaction des utilisateurs.
- Les utilisateurs rencontrent des **problèmes de compréhension du contexte** car scite.ai fournit souvent des réponses génériques ou vaguement liées au lieu d'informations ciblées.
- Les utilisateurs rencontrent une **mauvaise qualité de réponse** avec scite.ai, recevant souvent des réponses redondantes et génériques qui perturbent les flux de travail.
- Les utilisateurs trouvent le **contenu répétitif** dans scite.ai frustrant, car il conduit souvent à des réponses non pertinentes et trop générales.

#### What Are Recent G2 Reviews of scite.ai?

**["Votre assistant de recherche personnel—Un incontournable pour les étudiants et les chercheurs"](https://www.g2.com/fr/survey_responses/scite-ai-review-11931827)**

**Rating:** 5.0/5.0 stars

_— Melike G._

[Read full review](https://www.g2.com/fr/survey_responses/scite-ai-review-11931827)

**["Essentiel pour les citations académiques avec une limitation mineure de jetons"](https://www.g2.com/fr/survey_responses/scite-ai-review-12729378)**

**Rating:** 5.0/5.0 stars

_— Myrto P._

[Read full review](https://www.g2.com/fr/survey_responses/scite-ai-review-12729378)

### [InMoment Experience Improvement (XI) Platform](https://www.g2.com/fr/products/inmoment-experience-improvement-xi-platform/reviews)

InMoment, le leader dans l'amélioration des expériences et la plateforme et société de services CX la plus recommandée au monde, est renommé pour aider les clients à collecter et intégrer les données d'expérience client afin de découvrir les insights qui permettent les actions les plus intelligentes. En tant que pionniers dans l'application de l'IA primée, ses clients mondiaux activent chaque octet de leurs données d'expérience - des enquêtes structurées et des avis sociaux aux conversations non structurées issues des journaux d'appels, des e-mails, des tickets de support et des transcriptions de chat pour briser les silos de données. Cette technologie unique combinée à des experts du secteur en interne permet aux marques d'obtenir un retour sur investissement de leurs programmes CX en deux fois moins de temps que ses concurrents. Débloquez le véritable potentiel de chaque donnée client avec InMoment. Pour en savoir plus, visitez inmoment.com

**Average Rating:** 4.7/5.0

**Total Reviews:** 314

#### How Do G2 Users Rate InMoment Experience Improvement (XI) Platform?

- **Qualité du support:** 9.0/10 (Category avg: 8.7/10)

#### Who Is the Company Behind InMoment Experience Improvement (XI) Platform?

- **Vendeur:** [PG Forsta](https://www.g2.com/fr/sellers/pg-forsta)
- **Emplacement du siège social:** Salt Lake City, Utah
- **Page LinkedIn®:** [www.linkedin.com](https://www.g2.com/fr/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=e56037fcec61d213a1f4229eb926938e0c1373395be6ee138691fc922b14a1dc&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fweareinmoment%2F&secure%5Burl_type%5D=linkedin_company_website)  
411 employés sur LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Chef de produit, Responsable du succès client
- **Top Industries:** Logiciels informatiques, Technologie de l'information et services
- **Company Size:** 47% Small, 39% Medium

#### What Are Recent G2 Reviews of InMoment Experience Improvement (XI) Platform?

**["Outils faciles à utiliser. Personnel visionnaire et solidaire."](https://www.g2.com/fr/survey_responses/inmoment-experience-improvement-xi-platform-review-9832822)**

**Rating:** 5.0/5.0 stars

_— Beth W._

[Read full review](https://www.g2.com/fr/survey_responses/inmoment-experience-improvement-xi-platform-review-9832822)

**["Intégration transparente avec le POS pour l'enquête"](https://www.g2.com/fr/survey_responses/inmoment-experience-improvement-xi-platform-review-9337685)**

**Rating:** 5.0/5.0 stars

_— Lakshay D._

[Read full review](https://www.g2.com/fr/survey_responses/inmoment-experience-improvement-xi-platform-review-9337685)

#### What Are G2 Users Discussing About InMoment Experience Improvement (XI) Platform?

- [What is InMoment Experience Intelligence (XI) Platform used for?](https://www.g2.com/fr/discussions/what-is-inmoment-experience-intelligence-xi-platform-used-for)

### [MITIE: MIT Information Extraction](https://www.g2.com/products/mitie-mit-information-extraction/reviews)

MITIE: MIT Information Extraction is a tool that include performing named entity extraction and binary relation detection for training custom extractors and relation detectors.

**Average Rating:** 4.2/5.0

**Total Reviews:** 12

#### How Do G2 Users Rate MITIE: MIT Information Extraction?

- **Summarization:** 8.3/10 (Category avg: 9.0/10)
- **Language Detection:** 8.3/10 (Category avg: 8.8/10)
- **Part of Speech Tagging:** 8.9/10 (Category avg: 8.7/10)
- **Quality of Support:** 9.4/10 (Category avg: 8.7/10)

#### Who Is the Company Behind MITIE: MIT Information Extraction?

- **Seller:** [MITIE](https://www.g2.com/sellers/mitie)
- **Year Founded:** 1987
- **HQ Location:** London, UK
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=65144c6b190f8683904b8f0f4f6478c1d79c8fce0ce7c2a2a208e54b56e9a395&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fmitie&secure%5Burl_type%5D=linkedin_company_website)  
19,119 employees on LinkedIn®
- **Ownership:** LON: MTO

#### Who Uses This Product?

- **Company Size:** 42% Large, 33% Small

#### What Are Recent G2 Reviews of MITIE: MIT Information Extraction?

**["MITIE as a way of extracting reliable information"](https://www.g2.com/survey_responses/mitie-mit-information-extraction-review-7161286)**

**Rating:** 5.0/5.0 stars

_— Alexander M._

[Read full review](https://www.g2.com/survey_responses/mitie-mit-information-extraction-review-7161286)

**["Information extraction sharing review"](https://www.g2.com/survey_responses/mitie-mit-information-extraction-review-7580451)**

**Rating:** 4.0/5.0 stars

_— Sairaj Y._

[Read full review](https://www.g2.com/survey_responses/mitie-mit-information-extraction-review-7580451)

#### What Are G2 Users Discussing About MITIE: MIT Information Extraction?

- [What is MITIE: MIT Information Extraction used for?](https://www.g2.com/discussions/what-is-mitie-mit-information-extraction-used-for)

### [Level AI](https://www.g2.com/products/level-ai/reviews)

Level AI is the intelligence and orchestration layer for customer experience. We analyze 100% of customer interactions across voice, chat, email, and messaging to turn unstructured conversations into measurable insights and automation. From Voice of Customer and journey insights to automated quality, real-time coaching, and AI agents, Level AI helps teams improve customer outcomes, operational performance, and profitable growth.

**Average Rating:** 4.6/5.0

**Total Reviews:** 211

#### How Do G2 Users Rate Level AI?

- **Summarization:** 9.7/10 (Category avg: 9.0/10)
- **Language Detection:** 8.9/10 (Category avg: 8.8/10)
- **Part of Speech Tagging:** 9.2/10 (Category avg: 8.7/10)
- **Quality of Support:** 9.0/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Level AI?

- **Seller:** [Level AI](https://www.g2.com/sellers/level-ai)
- **Company Website:** thelevel.ai
- **Year Founded:** 2018
- **HQ Location:** Mountain View, US
- **Twitter:** @TheLevelAI  
204 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=88837a04d6b731eeff4a45c0aa27c4813f367a54aa990a1bb13415f8187aba9e&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Flevel-ai&secure%5Burl_type%5D=linkedin_company_website)  
212 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Quality Analyst, Supervisor
- **Top Industries:** Consumer Services, Food & Beverages
- **Company Size:** 56% Medium, 32% Large

#### What Do G2 Reviewers Say About Level AI?

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **ease of use** of Level AI, enjoying its uncluttered interface and intuitive dashboard.
- Users value the **helpfulness** of Level AI, enhancing customer service with quick, accurate information and user-friendly features.
- Users value the **enhanced efficiency** of Level AI, enabling quicker access to insights and streamlined processes.
- Users praise the **intuitive user interface** of Level AI, finding it easy to learn and navigate effectively.
- Users value the **accuracy** of Level AI, which enhances customer interactions with prompt and precise information delivery.

##### Cons

- Users experience **inaccuracies** in AI QA scores and face issues with delayed evaluations and visibility of scores.
- Users experience **slow performance** , which hampers timely updates and complicates monitoring and coaching efforts.
- Users highlight **accuracy issues** in Level AI, affecting evaluations, scores, and overall reliability of monitoring.
- Users find the **translation accuracy lacking** due to occasional misinterpretations of accents and context, affecting insights.
- Users report **AI inaccuracy** affecting scores and monitoring, with significant delays and issues capturing conversations accurately.

#### What Are Recent G2 Reviews of Level AI?

**["Efficient Call Review with Handy Transcription, Needs Enhanced Details"](https://www.g2.com/survey_responses/level-ai-review-11320627)**

**Rating:** 4.0/5.0 stars

_— Verified User in Consumer Services_

[Read full review](https://www.g2.com/survey_responses/level-ai-review-11320627)

**["Our Level AI Partnership has been a magical experience!"](https://www.g2.com/survey_responses/level-ai-review-13022467)**

**Rating:** 4.5/5.0 stars

_— Aaron H._

[Read full review](https://www.g2.com/survey_responses/level-ai-review-13022467)

#### What Are G2 Users Discussing About Level AI?

- [What is LevelAI used for?](https://www.g2.com/discussions/what-is-levelai-used-for) - 1 comment

### [Tungsten TotalAgility](https://www.g2.com/products/tungsten-totalagility/reviews)

The Industry’s Only Low‑Code, Integrated, End‑to‑End Intelligent Automation Solution Tungsten TotalAgility is a powerful all-in-one solution that combines document and process intelligence using the industry's leading capture, OCR, and process orchestration technology. Harness the Tungsten Intelligent Automation Platform, Tungsten TotalAgility, to go beyond AI-powered RPA by unlocking document intelligence, connecting disparate systems, and orchestrating human and digital workers to execute and automate workflows across your high-value business processes. • Document Intelligence: Apply cognitive capture and artificial intelligence to unstructured data to  automate and extract information and unlock data insights. • Process Orchestration: Orchestrate digital workflows in collaboration with users, systems , and data. • Connected Systems: Bring together your critical business systems— enterprise applications, legacy systems, mobile, chatbots, and more—across internal and external business processes. :: Successful Organizations Rely on TotalAgility :: Tungsten TotalAgility® streamlines building and deploying intelligent process automation so you can expand human and digital workforce capacity. Receive, execute, route, and report on workflow tasks from a single platform. Why customers choose TotalAgility? • Industry-leading document intelligence: Our intelligent document processing technology processes documents and data with the highest accuracy and speed. • Low-code automation: Powerful tools to build, deploy and accelerate enterprise automation. • End-to-end business process handling: A central intelligent automation platform to handle dynamic tasks, trigger automated rules and deploy on-demand workforce capacity. • Mobile engagement: Deliver enhanced customer experiences across any channel and any device.

**Average Rating:** 4.3/5.0

**Total Reviews:** 42

#### How Do G2 Users Rate Tungsten TotalAgility?

- **Summarization:** 10.0/10 (Category avg: 9.0/10)
- **Language Detection:** 10.0/10 (Category avg: 8.8/10)
- **Part of Speech Tagging:** 10.0/10 (Category avg: 8.7/10)
- **Quality of Support:** 8.3/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Tungsten TotalAgility?

- **Seller:** [Tungsten Automation](https://www.g2.com/sellers/tungsten-automation)
- **Year Founded:** 1985
- **HQ Location:** Denver, CO
- **Twitter:** @TungstenAI  
6,445 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=03f6061f54daba272dfcd31b6a9209216c8586cd1c869d15e1fa7ed2ed6a3551&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Ftungstenautomation%2F&secure%5Burl_type%5D=linkedin_company_website)  
1,564 employees on LinkedIn®

#### Who Uses This Product?

- **Top Industries:** Banking, Information Technology and Services
- **Company Size:** 53% Large, 31% Medium

#### What Are Recent G2 Reviews of Tungsten TotalAgility?

**["Automation with Kofax KTA"](https://www.g2.com/survey_responses/tungsten-totalagility-review-8206333)**

**Rating:** 4.5/5.0 stars

_— Shahir A._

[Read full review](https://www.g2.com/survey_responses/tungsten-totalagility-review-8206333)

**["Worked with KOFAX for Helba Investment project where extracted hand written data."](https://www.g2.com/survey_responses/tungsten-totalagility-review-9416972)**

**Rating:** 4.5/5.0 stars

_— Dipen P._

[Read full review](https://www.g2.com/survey_responses/tungsten-totalagility-review-9416972)

#### What Are G2 Users Discussing About Tungsten TotalAgility?

- [What is Kofax Transformation Module?](https://www.g2.com/discussions/what-is-kofax-transformation-module)
- [What is the Kofax system?](https://www.g2.com/discussions/what-is-the-kofax-system)
- [What is the use of Kofax?](https://www.g2.com/discussions/what-is-the-use-of-kofax)
- [What is Kofax TotalAgility?](https://www.g2.com/discussions/what-is-kofax-totalagility) - 1 comment

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 ![Bijou Barry](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Bijou Barry")
BB

Researched and written by [Bijou Barry](https://research.g2.com/insights/author/bijou-barry)

Updated April 9, 2026

Natural language understanding (NLU) software uses machine learning algorithms and statistical methods to help applications better understand human text, providing outputs such as part-of-speech tagging, sentiment analysis, named entity recognition, automatic summarization, emotion detection, and language detection from language inputs.

### Core Capabilities of NLU Software

To qualify for inclusion in the Natural Language Understanding category, a product must:

- Provide a deep learning algorithm specifically for human language interaction
- Connect with language data pools to learn a specific solution or function
- Consume language as an input and provide an outputted solution

### Common Use Cases for NLU Software

Developers and AI teams use NLU software to add human language comprehension capabilities to applications and services. Common use cases include:

- Powering chatbots and virtual assistants with intent recognition and multi-turn conversation understanding
- Enabling social media monitoring tools to analyze brand sentiment and detect mentions automatically
- Supporting translation and language detection applications across diverse linguistic data sources

### How NLU Software Differs from Other Tools

NLU is a specialized form of [natural language processing (NLP)](https://www.g2.com/categories/natural-language-processing-nlp) focused specifically on language comprehension and intent understanding, rather than the full spectrum of text processing tasks. NLU algorithms are examples of deep learning and may be offered as prebuilt capabilities within broader AI platform solutions, making them more focused than general NLP platforms that cover text generation and classification alongside understanding.

### Insights from G2 on NLU Software

Based on category trends on G2, intent recognition accuracy and ease of integration into conversational applications stand out as top capabilities. These platforms deliver improvements in chatbot understanding and reduction in misclassified user inputs as primary outcomes of adoption.

Show More

### Natural Language Understanding (NLU) Topics

- [What is Natural Language Understanding Software?](#what-is-natural-language-understanding-software)
- [What are the Common Features of Natural Language Understanding Software?](#what-are-the-common-features-of-natural-language-understanding-software)
- [What are the Benefits of Natural Language Understanding Software?](#what-are-the-benefits-of-natural-language-understanding-software)
- [Who Uses Natural Language Understanding Software?](#who-uses-natural-language-understanding-software)
- [What are the Alternatives to Natural Language Understanding Software?](#what-are-the-alternatives-to-natural-language-understanding-software)
- [Challenges with Natural Language Understanding Software](#challenges-with-natural-language-understanding-software)
- [Which Companies Should Buy Natural Language Understanding Software?](#which-companies-should-buy-natural-language-understanding-software)
- [How to Buy Natural Language Understanding Software](#how-to-buy-natural-language-understanding-software)
- [What Does Natural Language Understanding Software Cost?](#what-does-natural-language-understanding-software-cost)
- [Natural Language Understanding Software Trends](#natural-language-understanding-software-trends)

[
### Natural Language Understanding (NLU) Topics
Expand/Collapse ](#)
- [What is Natural Language Understanding Software?](#what-is-natural-language-understanding-software)
- [What are the Common Features of Natural Language Understanding Software?](#what-are-the-common-features-of-natural-language-understanding-software)
- [What are the Benefits of Natural Language Understanding Software?](#what-are-the-benefits-of-natural-language-understanding-software)
- [Who Uses Natural Language Understanding Software?](#who-uses-natural-language-understanding-software)
- [What are the Alternatives to Natural Language Understanding Software?](#what-are-the-alternatives-to-natural-language-understanding-software)
- [Challenges with Natural Language Understanding Software](#challenges-with-natural-language-understanding-software)
- [Which Companies Should Buy Natural Language Understanding Software?](#which-companies-should-buy-natural-language-understanding-software)
- [How to Buy Natural Language Understanding Software](#how-to-buy-natural-language-understanding-software)
- [What Does Natural Language Understanding Software Cost?](#what-does-natural-language-understanding-software-cost)
- [Natural Language Understanding Software Trends](#natural-language-understanding-software-trends)

## Learn More About Natural Language Understanding (NLU) Software

### What is Natural Language Understanding Software?

Natural language understanding, a subset of natural language processing (NLP), makes predictions or decisions based on text data. These learning algorithms can be embedded within applications to provide automated artificial intelligence (AI) features. A connection to a data source is necessary for the algorithm to learn and adapt over time. 

Pulling out actionable insights from numerical data housed in ERP systems, CRM software, or accounting software is one thing, but gaining insights from unstructured data sources is invaluable. Without dedicated software for this task, businesses must spend significant time and resources building natural language understanding models or haphazardly investigating the data.

These algorithms may be developed with supervised learning or unsupervised learning. Supervised learning involves training an algorithm to determine a pattern of inference by feeding it consistent data to produce a repeated, general output. Human training is necessary for this type of learning. Unsupervised algorithms independently reach an output and are a feature of deep learning algorithms. Reinforcement learning is the final form of machine learning, which consists of algorithms that understand how to react based on their situation or environment.

End users of intelligent applications may not be aware that an everyday software tool utilizes a machine learning algorithm to provide automation of some kind. Additionally, machine learning solutions for businesses may come in a machine learning as a service (MLaaS) model.

**What Does NLU Stand For?**

NLU stands for Natural Language Understanding, which is a subset of natural language processing (NLP).

#### What Types of Natural Language Understanding Software Exist?

Natural language understanding, at its core, allows machines to understand human language in spoken or written form. There are two key methods this can be accomplished.

**Machine learning-based systems**

Machine learning algorithms use statistical methods. They learn to perform tasks based on training data they are fed and adjust their methods as more data is processed. Using a combination of machine learning, deep learning, and neural networks, natural language processing algorithms hone their own rules through repeated processing and learning.

**Rules-based systems**

This system uses carefully designed linguistic rules. This approach was used early in the development of natural language processing and is still used.

### What are the Common Features of Natural Language Understanding Software?

The following are some core features within natural language understanding software that can help users better understand text data:

**Part-of-speech (POS) tagging:** With POS tagging, users can parse text by parts of speech. This can help break down sentences into component parts to understand them.

**Named entity recognition (NER):** Sentences are comprised of various entities, from street names to surnames, places, and more. With NER, one can extract these entities. These extracted entities can then be fed into other systems automatically.

**Sentiment analysis:** Language can be positive, negative, or neutral. Using sentiment analysis techniques, one can input text and be given the sentiment (positive or negative) of that text.

**Emotion detection:** Similar to sentiment analysis, emotion detection can detect the emotion of human language, whether written or spoken. Despite the research supporting it, this method has come under scrutiny, and its veracity has been challenged.

### What are the Benefits of Natural Language Understanding Software?

Natural language understanding is useful in many different contexts and industries.

**Application development:** NLU drives the development of AI applications that streamline processes, identify risks, and improve effectiveness.

**Efficiency:** NLU-powered applications are constantly improving because of the recognition of their value and the need to stay competitive in the industries in which they are used. They also increase the efficiency of repeatable tasks. A prime example of this can be seen in eDiscovery, where machine learning has created massive leaps in the efficiency with which legal documents are looked through, and relevant ones are identified.

**Scalability:** Humans are great at analysis, but their analysis skills can break down when the amount of data is vast and when they need to produce results in record time. NLU-powered technology does not get stressed, pressured, or tired. It can analyze a (relatively) small amount of data or a large text corpus with ease, speed, and accuracy. This can be scaled across a business’ text datasets and various use cases.

**Discovering trends:** NLU can do a great job at finding trends and patterns in text data. Through word clouds, graphs and charts, and more, NLU can provide users with deep insight into what is happening beneath the surface.

**Empowering non-technical users:** Much NLU technology in the market is no-code or low-code, which allows non-technical users to benefit from the technology. Gone are the days when one needed to go to a data scientist or IT professional to understand language data.

### Who Uses Natural Language Understanding Software?

NLU has applications across nearly every industry. Some industries that benefit from NLU applications include financial services, cybersecurity, recruiting, customer service, energy, and regulation.

**Marketing:** NLU-powered marketing applications help marketers identify content trends, shape content strategy, and personalize marketing content. 

**Finance:** Financial services institutions are increasing their use of NLU-powered applications to stay competitive with others in the industry who are doing the same. Some examples may include trawling through thousands of insurance claims and identifying ones with a high potential to be fraudulent. The process is similar, and the machine learning algorithm can digest the data to achieve the desired outcome quicker.

**Human resources:** Resumes are long and filled with words. As such, natural language understanding technology can help recruiters comb through large amounts of resumes and other text data to better understand candidates.

### What are the Alternatives to Natural Language Understanding Software?

Alternatives to natural language understanding software can replace this type of software, either partially or completely:

[Machine learning software](https://www.g2.com/categories/machine-learning#learn-more) **:** Natural language understanding (NLU) software is specifically connected to and used for text data. If one is looking for more general-use machine learning algorithms, machine learning software would be a good category to pursue.

[Text analysis software](https://www.g2.com/categories/text-analysis#learn-more) **:** NLU software is geared toward incorporating NLU capabilities into other applications or systems. Text analysis software, however, is an all-purpose solution built to analyze any text data. Businesses looking to focus on analyzing their text data, such as from surveys, review sites, social media, and customer service tools, can leverage text analysis software to achieve this goal. This software enables businesses to consolidate and analyze their text data within a single platform. 

#### Software Related to Natural Language Understanding Software

Related solutions that can be used together with natural language understanding software include:

[Chatbots software](https://www.g2.com/categories/chatbots) **:** Businesses looking for an off-the-shelf conservational AI solution can leverage chatbots. Tools specifically geared toward chatbot creation helps companies use chatbots off the shelf, with little to no development or coding experience necessary.

[Bot platforms software](https://www.g2.com/categories/bot-platforms) **:** Companies looking to build their own chatbot can benefit from bot platforms, which are tools used to build and deploy interactive chatbots. These platforms provide development tools such as frameworks and API toolsets for customizable bot creation.

[Intelligent virtual assistants (IVAs)](https://www.g2.com/categories/intelligent-virtual-assistants) **:** Businesses that want conversational AI with strong natural language understanding capabilities should consider IVAs. IVAs understand a range of different intents from a singular utterance and can even understand responses they are not explicitly programmed to using natural language processing (NLP). With the use of machine learning and deep learning, IVAs can grow intelligently and understand a wider vocabulary and colloquial language, as well as provide more precise and correct responses to requests.

### Challenges with Natural Language Understanding Software

Software solutions can come with their own set of challenges. 

**Data preparation:** A potential concern is preparing the data to be ingested by the NLU tool. The data needs to be stored properly, whether that is in a database or data warehouse. Users may require IT or a dedicated admin to ensure the text analytics tool can consume the data.

**Automation pushback:** One of the biggest potential issues with machine learning-powered applications, such as NLU, lies in removing humans from processes. This is particularly problematic when looking at emerging technologies like self-driving cars. By completely removing humans from the product development lifecycle, machines are given the power to decide in life-or-death situations.

**Data security:** Companies must consider security options to ensure the correct users see the correct data. They must also have security options that allow administrators to assign verified users different levels of access to the platform.

### Which Companies Should Buy Natural Language Understanding Software?

Pattern recognition can help businesses across industries. Effective and efficient predictions can help these businesses make data-informed decisions, such as dynamic pricing based upon a range of data points.

**Retail:** An e-commerce site can leverage an NLU application programming interface (API) to create rich, personalized experiences for every user.

**Entertainment:** Media organizations can leverage NLU to comb through their scripts and other content to catalog and categorize their material.

**Finance:** Financial institutions can analyze contracts and conduct sentiment analysis and named entity recognition to better understand these documents and to scale operations.

### How to Buy Natural Language Understanding Software

#### Requirements Gathering (RFI/RFP) for Natural Language Understanding Software

If a company is just starting out and looking to purchase their first NLU software, wherever they are in the buying process, g2.com can help select the best machine learning software for them.

Taking a holistic overview of the business and identifying pain points can help the team create a checklist of criteria. The checklist serves as a detailed guide that includes both necessary and nice-to-have features, including budget, features, number of users, integrations, security requirements, cloud or on-premises solutions, and more. Depending on the scope of the deployment, it might be helpful to produce an RFI, a one-page list with a few bullet points describing what is needed from a machine learning platform.

#### Compare Natural Language Understanding Software Products

**Create a long list**

From meeting the business functionality needs to implementation, vendor evaluations are an essential part of the software buying process. For ease of comparison, after the demos are complete, it helps to prepare a consistent list of questions regarding specific needs and concerns to ask each vendor.

**Create a short list**

From the long list of vendors, it is advisable to narrow down the list of vendors and come up with a shorter list of contenders, preferably no more than three to five. With this list in hand, businesses can produce a matrix to compare the features and pricing of the various solutions.

**Conduct demos**

To ensure the comparison is thoroughgoing, the user should demo each solution on the shortlist with the same use case and datasets. This will allow the business to evaluate like for like and see how each vendor stacks up against the competition.

#### Selection of Natural Language Understanding Software

**Choose a selection team**

Before getting started, it's crucial to create a winning team that will work together throughout the entire process, from identifying pain points to implementation. The software selection team should consist of members of the organization who have the right interest, skills, and time to participate in this process. A good starting point is to aim for three to five people who fill roles such as the main decision maker, project manager, process owner, system owner, or staffing subject matter expert, as well as a technical lead, IT administrator, or security administrator. In smaller companies, the vendor selection team may be smaller, with fewer participants multitasking and taking on more responsibilities.

**Negotiation**

Prices on a company's pricing page are not always fixed (although some companies will not budge). It is imperative to open up a conversation regarding pricing and licensing. For example, the vendor may be willing to give a discount for multi-year contracts or for recommending the product to others.

**Final decision**

After this stage, and before going all in, it is recommended to roll out a test run or pilot program to test adoption with a small sample size of users. If the tool is well used and well received, the buyer can be confident that the selection was correct. If not, it might be time to go back to the drawing board.

### What Does Natural Language Understanding Software Cost?

NLU software is generally available in different tiers, with the more entry-level solutions costing less than the enterprise-scale ones. The former will usually lack features and may have caps on usage. Vendors may have tiered pricing, in which the price is tailored to the users’ company size, the number of users, or both. This pricing strategy may come with some degree of support, either unlimited or capped at a certain number of hours per billing cycle.

Once set up, they do not often require significant maintenance costs, especially if deployed in the cloud. As these platforms often come with many additional features, businesses looking to maximize the value of their software can contract third-party consultants to help them derive insights from their data and get the most out of the software.

#### Return on Investment (ROI)

Businesses decide to deploy machine learning software with the goal of deriving some degree of ROI. As they are looking to recoup the losses that they spent on the software, it is critical to understand the costs associated with it. As mentioned above, these platforms typically are billed per user, which is sometimes tiered depending on the company size. 

More users will naturally translate into more licenses, which means more money. Users must consider how much is spent and compare that to what is gained, both in terms of efficiency as well as revenue. Therefore, businesses can compare processes between pre- and post-deployment of the software to better understand how processes have been improved and how much time has been saved. They can even produce a case study (either for internal or external purposes) to demonstrate the gains they have seen from their use of the platform.

### Natural Language Understanding Software Trends

**Automation**

With the adoption of NLU and the automation of repetitive tasks, businesses can deploy their human workforce to more creative projects. For example, if a machine learning algorithm automatically displays personalized advertisements based on a user’s text, the human marketing team can work on producing creative material.

**Voice technology**

Voice is a primal method of interacting with others. It is only natural that we now converse with our machines using our voice and that the platforms for said voicebots have seen great success. Voice makes technology feel more human and allows people to trust it more. Voice will prove to be a crucial natural interface that mediates human communication and relationships with devices within an AI-powered world.

**Artificial intelligence (AI)**

AI is quickly becoming a promising feature of many, if not most, types of software. With machine learning, end users can identify patterns in data, allowing them to make sense of content and help them understand what they are seeing. This pattern recognition is fueling the rise of more powerful, contextually-aware chatbots.