Best Enterprise Machine Learning Software

How Many Machine Learning Software Products Does G2 Track?

Total Products under this Category: 1,064

Category Stats (Oct 2026)

  • Average Rating: 4.34/5 (↑0.01 vs Sep 2026) The average rating of products in this category, based on all submitted ratings
  • Top Trending Product: Modal Labs (+3.52%) - Among all products in this category, Modal Labs recorded the largest rating increase compared to last month

Last updated: October 21, 2026

How Does G2 Rank Machine Learning Software Products?

Why You Can Trust G2's Software Rankings:

  • 30 Analysts and Data Experts
  • 14,400+ Authentic Reviews
  • 1,064+ 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 Machine Learning Software

G2 Grid® for Machine Learning Software plotting products by satisfaction and market presence

Highlighted products: SAS Viya, IBM watsonx.ai, Gemini platform, Azure OpenAI Service, Dataiku, Alteryx, machine-learning in Python, and Amazon Forecast.

Underlying data: [Grid® JSON](https://www.g2.com/categories/machine-learning/grids.json?focus%5B%5D=sas-sas-viya&focus%5B%5D=ibm-watsonx-ai&focus%5B%5D=gemini-platform&focus%5B%5D=azure-openai-service&focus%5B%5D=dataiku&focus%5B%5D=alteryx&focus%5B%5D=machine-learning-in-python&focus%5B%5D=amazon-forecast&segment=enterprise)

SAS Viya

SAS Viya is a cloud-native data and AI platform that enables teams to build, deploy and scale explainable AI that drives trusted, confident decisions. It unites the entire data and AI life cycle and empowers teams to innovate quickly while balancing speed, automation and governance by design. Viya unifies data management, advanced analytics and decisioning in a single platform, so organizations can move from experimentation to production with confidence, delivering measurable business impact that is secure, explainable and scalable across any environment. Key capabilities required to deliver trusted decisions include: • End-to-end clarity across the data and AI life cycle, with built-in lineage, auditability and continuous monitoring to support defensible decisions. • Governance by design, enabling consistent oversight across data, models and decisions to reduce risk and accelerate adoption. • Explainable AI at scale, so insights and outcomes can be understood, validated and trusted by business and regulators alike. • Operationalized analytics, ensuring value continues beyond deployment through monitoring, retraining and life cycle management. • Flexible, cloud-native deployment, allowing organizations to start anywhere and scale everywhere while maintaining control.

Average Rating: 4.4/5.0

Total Reviews: 784

How Do G2 Users Rate SAS Viya?

  • Has the product been a good partner in doing business?: 8.2/10 (Category avg: 8.7/10)
  • Ease of Use: 8.2/10 (Category avg: 8.5/10)
  • Quality of Support: 8.4/10 (Category avg: 8.4/10)
  • Ease of Admin: 7.6/10 (Category avg: 8.5/10)

Who Is the Company Behind SAS Viya?

  • Seller: SAS Institute
  • Company Website:
  • Year Founded: 1976
  • HQ Location: Cary, NC
  • Twitter: @SASsoftware
    60,863 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    15,122 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Student, Biostatistician
  • Top Industries: Pharmaceuticals, Banking
  • Company Size: 33% Small, 33% Large

What Do G2 Reviewers Say About SAS Viya?

AI-generated summary from verified user reviews

Pros
  • Users value the ease of use in SAS Viya, enhancing data visualization and decision-making for businesses.
  • Users appreciate the advanced analytical capabilities of SAS Viya, making data analysis and decision-making more efficient.
  • Users value the sophisticated analytical capabilities of SAS Viya, enhancing decision-making and insights from diverse data sources.
  • Users value the end-to-end data lifecycle tooling in SAS Viya, enhancing insights and strategic decision-making capabilities.
  • Users commend SAS Viya for its user-friendly interface, making complex analytics accessible to individuals of all skill levels.
Cons
  • Users find SAS Viya difficult for non-technical users to navigate, impacting ease of access to reports and dashboards.
  • Users find the learning curve challenging, especially for non-technical individuals navigating reports and dashboards.
  • Users find the visualization complexity of SAS Viya challenging, especially for those without technical expertise.
  • Users find the difficult learning curve for SAS Viya challenging, especially for non-technical users attempting to access features.
  • Users find the expensive pricing of SAS Viya a potential barrier, complicating their decision-making process.

What Are Recent G2 Reviews of SAS Viya?

What Are G2 Users Discussing About SAS Viya?

IBM watsonx.ai

Watsonx.ai is part of the IBM watsonx platform that brings together new generative AI capabilities, powered by foundation models and traditional machine learning into a powerful studio spanning the AI lifecycle. With watsonx.ai, you can build, train, validate, tune and deploy generative AI, foundation models and machine learning capabilities with ease and build AI applications in a fraction of the time with a fraction of the data.

Average Rating: 4.4/5.0

Total Reviews: 140

How Do G2 Users Rate IBM watsonx.ai?

  • Has the product been a good partner in doing business?: 8.8/10 (Category avg: 8.7/10)
  • Ease of Use: 8.8/10 (Category avg: 8.5/10)
  • Quality of Support: 8.6/10 (Category avg: 8.4/10)
  • Ease of Admin: 8.5/10 (Category avg: 8.5/10)

Who Is the Company Behind IBM watsonx.ai?

  • Seller: IBM
  • Company Website:
  • Year Founded: 1911
  • HQ Location: Armonk, New York, United States
  • Twitter: @IBMSecurity
    74,660 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    344,328 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Consultant
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 41% Small, 32% Large

What Do G2 Reviewers Say About IBM watsonx.ai?

AI-generated summary from verified user reviews

Pros
  • Users praise the ease of use of IBM watsonx.ai, facilitating straightforward integration and model development.
  • Users value the wide range of model types in IBM watsonx.ai, enhancing flexibility and efficiency in development.
  • Users appreciate the user-friendly platform that simplifies building and deploying AI models efficiently and effectively.
  • Users appreciate the user-friendly AI studio of IBM watsonx.ai, enabling efficient chatbot creation with minimal coding.
  • Users appreciate the enterprise-grade AI of IBM watsonx.ai, which integrates seamlessly for practical, reliable business solutions.
Cons
  • Users find the difficult learning curve challenging, indicating the need for clearer documentation and better onboarding support.
  • Users find the complexity of IBM watsonx.ai challenging, especially for beginners and small teams seeking easier solutions.
  • Users find the steep learning curve of IBM watsonx.ai challenging, making it less approachable for non-technical teams.
  • Users express concerns about the high costs of IBM watsonx.ai, finding it challenging and not budget-friendly for small teams.
  • Users feel that improvement is needed in 3rd party integration and intelligent model optimization for better performance.

What Are Recent G2 Reviews of IBM watsonx.ai?

Gemini platform

Google Cloud's comprehensive platform for developers to build, scale, govern and optimize agents and models. It's a single destination for technical teams to build agents that can transform enterprise applications and workflows into powerful agentic systems.

Average Rating: 4.3/5.0

Total Reviews: 724

How Do G2 Users Rate Gemini platform?

  • Has the product been a good partner in doing business?: 8.3/10 (Category avg: 8.7/10)
  • Ease of Use: 8.2/10 (Category avg: 8.5/10)
  • Quality of Support: 8.2/10 (Category avg: 8.4/10)
  • Ease of Admin: 8.0/10 (Category avg: 8.5/10)

Who Is the Company Behind Gemini platform?

  • Seller: Google
  • Year Founded: 1998
  • HQ Location: Mountain View, CA
  • Twitter: @google
    31,899,995 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    301,144 employees on LinkedIn®
  • Ownership: NASDAQ:GOOG

Who Uses This Product?

  • Who Uses This: Software Engineer, Data Scientist
  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 42% Small, 29% Large

What Do G2 Reviewers Say About Gemini platform?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of the Gemini Enterprise Agent Platform, highlighting its beginner-friendly interface and intuitive design.
  • Users appreciate the multimodal capabilities of Gemini, enhancing productivity by understanding text, images, code, and documents together.
  • Users value the multimodal capabilities of Gemini, enhancing productivity in software development and automation projects.
  • Users value the multimodal capabilities of Gemini, enhancing productivity in software development and automation projects.
  • Users value the integrated platform of Gemini, enhancing productivity by combining various functionalities in a unified system.
Cons
  • Users find the platform expensive, especially when considering resource usage and challenging documentation.
  • Users find the complex pricing structure of Gemini Enterprise Agent Platform confusing and difficult to navigate.
  • Users find the learning curve steep with Gemini Enterprise Agent Platform, due to its numerous complex components and configurations.
  • Users find the complex pricing structure of Gemini Enterprise Agent challenging and suggest simplifying it for clarity.
  • Users find the difficult learning curve of Gemini Enterprise Agent Platform overwhelming, especially with advanced features and integrations.

What Are Recent G2 Reviews of Gemini platform?

What Are G2 Users Discussing About Gemini platform?

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Azure OpenAI Service

Azure OpenAI Service is a cloud-based platform that provides access to OpenAI's advanced artificial intelligence models, including GPT-3.5, Codex, and DALL·E 2. This service enables developers and businesses to integrate powerful AI capabilities into their applications, facilitating tasks such as natural language processing, code generation, and image creation. By leveraging Azure's enterprise-grade infrastructure, users benefit from enhanced security, compliance, and scalability, making it suitable for a wide range of industries and use cases. Key Features and Functionality: - Access to Advanced AI Models: Utilize state-of-the-art models like GPT-3.5 for natural language understanding, Codex for code generation, and DALL·E 2 for image creation. - Enterprise-Grade Security and Compliance: Benefit from Azure's robust security measures, ensuring data privacy and compliance with industry standards. - Scalability and Reliability: Deploy AI solutions at scale with high availability, leveraging Azure's global infrastructure. - Customization and Fine-Tuning: Tailor AI models to specific business needs through fine-tuning capabilities, enhancing performance for particular tasks. - Integrated Responsible AI Tools: Implement AI solutions responsibly with built-in tools designed to detect and mitigate harmful content, ensuring ethical AI usage. Primary Value and Solutions Provided: Azure OpenAI Service empowers organizations to accelerate innovation by integrating cutting-edge AI models into their products and services. It addresses challenges such as automating complex tasks, enhancing customer interactions through natural language understanding, and generating high-quality content efficiently. By providing a secure and scalable environment, the service enables businesses to harness the full potential of AI while maintaining control over their data and compliance requirements.

Average Rating: 4.6/5.0

Total Reviews: 58

How Do G2 Users Rate Azure OpenAI Service?

  • Has the product been a good partner in doing business?: 9.4/10 (Category avg: 8.7/10)
  • Ease of Use: 9.0/10 (Category avg: 8.5/10)
  • Quality of Support: 9.0/10 (Category avg: 8.4/10)
  • Ease of Admin: 8.9/10 (Category avg: 8.5/10)

Who Is the Company Behind Azure OpenAI Service?

  • Seller: Microsoft
  • Year Founded: 1975
  • HQ Location: Redmond, Washington
  • Twitter: @microsoft
    13,091,739 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    232,750 employees on LinkedIn®
  • Ownership: MSFT

Who Uses This Product?

  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 34% Large, 32% Small

What Do G2 Reviewers Say About Azure OpenAI Service?

AI-generated summary from verified user reviews

Pros
  • Users find the ease of use of Azure OpenAI Service enhances their experience, simplifying integration and implementation processes.
  • Users value the seamless integration with Azure tools, enhancing workflow and scaling capabilities within the ecosystem.
  • Users value the scalability of Azure OpenAI Service for effectively managing enterprise-wide data infrastructure and AI integration.
  • Users value the reliability of Azure OpenAI Service, appreciating its seamless integration and smooth, consistent performance.
  • Users value the seamless integration and security of Azure OpenAI Service for deploying advanced AI models effectively.
Cons
  • Users find the cost can become expensive with extensive use, complicating budget considerations for the Azure OpenAI Service.
  • Users find the complex setup of Azure OpenAI Service challenging, requiring extensive knowledge of networking and security.
  • Users find the limited features of Azure OpenAI Service restrict creativity and flexibility in their projects.
  • Users struggle with the complexity of rate limiting, which complicates daily operations and leads to frustrating errors.
  • Users find the time consumption in approval processes and feature rollouts frustrating, slowing down experimentation and usage.

What Are Recent G2 Reviews of Azure OpenAI Service?

Dataiku

Dataiku is the Platform for AI Success: the AI orchestration layer where enterprises build, deploy, and govern analytics, models, and agents at scale. It sits on top of the data platforms, clouds, and AI services you already use, working across all of them without locking you into any one. Dataiku expands who can build production AI, putting the right tools in the hands of data scientists and domain experts alike, from fraud analysts to demand planners. It orchestrates machine learning, rules, LLMs, and agents as one governed system, built on more than a decade of running production AI. Governance is part of the build rather than something bolted on afterward, so teams ship faster while keeping performance, cost, and risk under control. The result: AI that moves from experimentation to trusted, measurable execution now, not in 18 months.

Average Rating: 4.4/5.0

Total Reviews: 253

How Do G2 Users Rate Dataiku?

  • Has the product been a good partner in doing business?: 8.6/10 (Category avg: 8.7/10)
  • Ease of Use: 8.6/10 (Category avg: 8.5/10)
  • Quality of Support: 8.5/10 (Category avg: 8.4/10)
  • Ease of Admin: 8.0/10 (Category avg: 8.5/10)

Who Is the Company Behind Dataiku?

  • Seller: Dataiku
  • Company Website:
  • Year Founded: 2013
  • HQ Location: New York, NY
  • Twitter: @dataiku
    22,917 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    1,605 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Scientist, Data Analyst
  • Top Industries: Financial Services, Pharmaceuticals
  • Company Size: 58% Large, 23% Medium

What Do G2 Reviewers Say About Dataiku?

AI-generated summary from verified user reviews

Pros
  • Users appreciate how Dataiku simplifies ML development, enabling quick training, evaluation, and understanding of data easily.
  • Users find Dataiku easy to use, simplifying ML development and helping detect opportunities and risks effortlessly.
  • Users value the ease of use in Dataiku, enabling collaboration and simplifying complex data processes for all skill levels.
  • Users appreciate the easy integrations of Dataiku, facilitating collaboration across diverse analytics tools and skill sets.
  • Users commend the productivity improvement brought by Dataiku’s visual recipes and robust tools for analytics projects.
Cons
  • Users find the learning curve steep, making it challenging for beginners to fully utilize Dataiku's advanced features.
  • Users find the steep learning curve challenging, especially for beginners navigating Dataiku's advanced features.
  • Users find the difficult learning curve challenging for beginners, impacting their ability to maximize the platform's potential.
  • Users face slow performance with Dataiku when managing large datasets, impacting efficiency and productivity.
  • Users find the pricing high for small companies and students, impacting accessibility for basic projects.

What Are Recent G2 Reviews of Dataiku?

What Are G2 Users Discussing About Dataiku?

Alteryx

Alteryx is the agentic analytics and automation company that helps organizations turn complex data into trusted insights, decisions, and action. Built for the people closest to the business, the Alteryx One platform is designed to work across an organization’s existing data and technology ecosystem. It enables business users to produce AI-ready datasets and define, maintain, and update business logic into visual workflows that AI uses to automate operations and insights. This business logic stays visible, understandable, repeatable, and auditable (VURA), so that teams can automate data-intensive workflows without coding. Alteryx closes the last-mile gap between data platforms and the decisions and operations that run the business—giving AI the trusted business context it needs to deliver reliable results. Over 8,000 customers worldwide, including more than half of the Global 2000, rely on Alteryx to improve revenue performance, manage costs, increase operational efficiency, and reduce risk. Collectively, they run more than 380 million workflows on Alteryx each year.

Average Rating: 4.6/5.0

Total Reviews: 920

How Do G2 Users Rate Alteryx?

  • Has the product been a good partner in doing business?: 8.8/10 (Category avg: 8.7/10)
  • Ease of Use: 8.7/10 (Category avg: 8.5/10)
  • Quality of Support: 8.5/10 (Category avg: 8.4/10)
  • Ease of Admin: 8.3/10 (Category avg: 8.5/10)

Who Is the Company Behind Alteryx?

  • Seller: Alteryx
  • Company Website:
  • Year Founded: 1997
  • HQ Location: Irvine, CA
  • Twitter: @alteryx
    26,149 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    2,312 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Analyst, Analyst
  • Top Industries: Financial Services, Accounting
  • Company Size: 61% Large, 21% Medium

What Do G2 Reviewers Say About Alteryx?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use in Alteryx, finding it simple to automate tasks with drag and drop functionality.
  • Users value the automation capabilities of Alteryx, streamlining data processes and enhancing analytical efficiency.
  • Users find Alteryx to be very intuitive, making it easy for non-technical users to learn and utilize.
  • Users find that Alteryx's interface makes learning technology easy for everyone, even those without a tech background.
  • Users value Alteryx for its efficiency in managing data, streamlining workflows, and enhancing overall productivity.
Cons
  • Users highlight the expensive pricing of Alteryx, making it difficult for small teams or startups to afford licenses.
  • Users face a steep learning curve with Alteryx, requiring time to master its complex features.
  • Users find that Alteryx suffers from missing features, such as lack of direct database access and limited reporting tools.
  • Users find the learning difficulty of Alteryx steep, especially for those unfamiliar with RegEx and SQL.
  • Users experience slow performance with Alteryx, particularly when handling large workflows and during data wrangling tasks.

What Are Recent G2 Reviews of Alteryx?

machine-learning in Python

The "machine-learning" project by jeff1evesque is a Python-based web interface and REST API designed for performing classification and regression tasks. It provides a user-friendly platform for implementing machine learning models, making it accessible for both beginners and experienced practitioners. Key Features and Functionality: - Web Interface: Offers an intuitive graphical user interface for managing datasets, training models, and visualizing results. - REST API: Enables seamless integration with other applications, allowing for automated machine learning workflows. - Classification and Regression: Supports a variety of algorithms to handle both classification and regression problems effectively. - Documentation: Comprehensive guides and resources are available to assist users in understanding and utilizing the platform's capabilities. Primary Value and User Solutions: This project simplifies the process of deploying machine learning models by providing a cohesive environment that combines data management, model training, and result analysis. It addresses common challenges in machine learning implementation, such as the need for coding expertise and integration complexities, thereby enabling users to focus on deriving insights and making data-driven decisions.

Average Rating: 4.6/5.0

Total Reviews: 48

How Do G2 Users Rate machine-learning in Python?

  • Has the product been a good partner in doing business?: 8.6/10 (Category avg: 8.7/10)
  • Ease of Use: 8.9/10 (Category avg: 8.5/10)
  • Quality of Support: 8.6/10 (Category avg: 8.4/10)
  • Ease of Admin: 8.9/10 (Category avg: 8.5/10)

Who Is the Company Behind machine-learning in Python?

Who Uses This Product?

  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 40% Small, 34% Large

What Do G2 Reviewers Say About machine-learning in Python?

AI-generated summary from verified user reviews

Pros
  • Users value the rich ecosystem of libraries in Python, enhancing efficiency in machine learning model development and experimentation.
  • Users find the ease of use of machine learning in Python enhances their learning and project development experience.
  • Users appreciate the model variety offered by Python's libraries, enabling versatile and effective machine learning solutions.
  • Users appreciate the intuitive nature of Python for machine learning, simplifying model development and experimentation.
  • Users highlight the powerful libraries in Python, enhancing productivity and ease in machine learning development.
Cons
  • Users find that difficult learning is a barrier, as mastering the basics of machine learning and Python takes time.
  • Users often face dependency issues with version conflicts among libraries, complicating the machine learning experience in Python.
  • Users experience slow performance with Python machine learning, especially when handling large datasets or integrating libraries.
  • Users find that machine learning in Python can be slow, especially on local machines due to being interpreted.
  • Users note that performance limitations arise in Python for large-scale or compute-intensive machine learning tasks.

What Are Recent G2 Reviews of machine-learning in Python?

What Are G2 Users Discussing About machine-learning in Python?

Amazon Forecast

Amazon Forecast is a fully managed service that uses machine learning to deliver highly accurate forecasts.

Average Rating: 4.3/5.0

Total Reviews: 102

How Do G2 Users Rate Amazon Forecast?

  • Has the product been a good partner in doing business?: 8.9/10 (Category avg: 8.7/10)
  • Ease of Use: 8.4/10 (Category avg: 8.5/10)
  • Quality of Support: 8.7/10 (Category avg: 8.4/10)
  • Ease of Admin: 7.9/10 (Category avg: 8.5/10)

Who Is the Company Behind Amazon Forecast?

  • Seller: Amazon Web Services (AWS)
  • Year Founded: 2006
  • HQ Location: Seattle, WA
  • Twitter: @awscloud
    2,232,483 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    148,266 employees on LinkedIn®
  • Ownership: NASDAQ: AMZN

Who Uses This Product?

  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 49% Small, 37% Medium

What Do G2 Reviewers Say About Amazon Forecast?

AI-generated summary from verified user reviews

Pros
  • Users find Amazon Forecast to be user-friendly, offering accurate predictions without requiring machine learning expertise.
  • Users value the high forecasting accuracy of Amazon Forecast, leveraging advanced ML to produce dependable predictions effortlessly.
  • Users value the high accuracy of Amazon Forecast, benefiting from reliable results through advanced machine learning technology.
  • Users appreciate the high accuracy and ease of use of Amazon Forecast, leveraging advanced ML for reliable predictions.
  • Users value the high accuracy of Amazon Forecast, benefiting from reliable results powered by advanced ML technology.
Cons
  • Users express concern over the high costs of Amazon Forecast, particularly with large datasets and frequent predictions.
  • Users find Amazon Forecast's complexity in setup and use frustrating, particularly affecting those unfamiliar with AWS services.
  • Users find the steep learning curve of Amazon Forecast challenging, especially for those not familiar with AWS.
  • Users express concern over the high costs of Amazon Forecast, especially when scaling for larger datasets.
  • Users find that the cost escalates quickly with large datasets and frequent model retraining, impacting budget management.

What Are Recent G2 Reviews of Amazon Forecast?

Automation Anywhere Agentic Process Automation

Automation Anywhere Agentic Process Automation (APA) is an enterprise platform that orchestrates AI agents, RPA bots, APIs, documents, and human expertise as a single governed system of work. APA transforms what is possible with automation — orchestrating every instrument of work across every system, with execution grounded in process expertise, and end-to-end process governance across every agent, every step, and every decision. It turns individual capabilities into compounded business transformation. With the APA platform, you can optimize what already runs your business and expand into what has never been feasible before. What's inside the platform Process Reasoning Engine (PRE) — the decision layer. Goal-driven AI agents plan, act, adapt, and self-correct in real time as conditions change. Mozart Orchestrator — a unified composer that manages decisions, dependencies, context, and exceptions across agents, automations, documents, and APIs. AI Agent Studio — a low-code workspace for building AI agents on foundational models from Amazon Bedrock, Google Vertex AI, Azure OpenAI, OpenAI, and others. Automator AI — generative AI–powered automation development across any application, cloud or on-premises. Document Automation — processes unstructured documents at over 95% accuracy, and 5x faster with Cloud Extraction Service for large-scale extraction. Process Discovery — surfaces bottlenecks and identifies what to automate next. Automation Co-Pilot — triggers multi-step agentic workflows in natural language, inside the applications teams already use. Governance built in, not bolted on Every agent, action, and decision runs inside enterprise controls: fine-grained role-based access control (RBAC), AES-256 encryption at rest, TLS in transit, native audit logs with SIEM integration, and human-in-the-loop oversight. Automation Anywhere maintains SOC 1 Type 2, SOC 2 Type 2, ISO 27001, ISO 22301, and HITRUST certifications, and supports GDPR compliance. Proven in production 1,500+ live APA deployments, 400M+ automations run per year, and 1.8M+ unique AI agent executions across 26 global regions. Bancolombia — 1,300% ROI in the first year and a 50% increase in customer service efficiency JBS — $1M and 125,000 hours saved in IT Granite Telecom — $635,000 in monthly savings and 15,000 hours saved per month Ricoh — 500 days of operational time saved per month SoftBank Corp. — 85% reduction in recruitment hours Who it's for Enterprise operations, IT, finance, HR, customer service, and shared services teams in banking, insurance, healthcare, life sciences, manufacturing, telecommunications, and the public sector — wherever complex, cross-system work has to run reliably and be governed. Learn more at https://www.automationanywhere.com.

Average Rating: 4.5/5.0

Total Reviews: 4,162

How Do G2 Users Rate Automation Anywhere Agentic Process Automation?

  • Has the product been a good partner in doing business?: 8.7/10 (Category avg: 8.7/10)
  • Ease of Use: 8.9/10 (Category avg: 8.5/10)
  • Quality of Support: 8.7/10 (Category avg: 8.4/10)
  • Ease of Admin: 8.4/10 (Category avg: 8.5/10)

Who Is the Company Behind Automation Anywhere Agentic Process Automation?

  • Seller: Automation Anywhere
  • Company Website:
  • Year Founded: 2003
  • HQ Location: San Jose, CA
  • Twitter: @AutomationAnywh
    55,050 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    2,327 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: RPA Developer, Software Engineer
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 58% Large, 23% Medium

What Do G2 Reviewers Say About Automation Anywhere Agentic Process Automation?

AI-generated summary from verified user reviews

Pros
  • Users praise the ease of use in Automation Anywhere Agentic Process Automation for simplifying RPA bot creation and management.
  • Users value the ease of automating repetitive tasks with Automation Anywhere, enhancing productivity and efficiency effortlessly.
  • Users appreciate the efficiency of Automation Anywhere, highlighting its ease of use and significant impact on productivity.
  • Users value the automation ease of Automation Anywhere, enabling non-coders to effortlessly build bots and streamline tasks.
  • Users appreciate the intuitive interface of Automation Anywhere, making automation easy and enhancing overall efficiency.
Cons
  • Users find Automation Anywhere's pricing model to be expensive and complex, which can be challenging for small teams.
  • Users find the steep learning curve challenging, especially for beginners navigating advanced features and debugging workflows.
  • Users find the missing features of Automation Anywhere Agentic Process Automation frustrating, limiting their workflow capabilities.
  • Users experience software bugs causing issues like errors in automation and problems with browser extensions.
  • Users often face bot issues including complex debugging and integration challenges, affecting overall usability and performance.

What Are Recent G2 Reviews of Automation Anywhere Agentic Process Automation?

What Are G2 Users Discussing About Automation Anywhere Agentic Process Automation?

Weka

Weka is a machine learning algorithms for data mining tasks that can either be applied directly to a dataset or called from own Java code, it contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization and well-suited for developing new machine learning schemes.

Average Rating: 4.3/5.0

Total Reviews: 13

How Do G2 Users Rate Weka?

  • Has the product been a good partner in doing business?: 8.1/10 (Category avg: 8.7/10)
  • Ease of Use: 8.2/10 (Category avg: 8.5/10)
  • Quality of Support: 7.9/10 (Category avg: 8.4/10)
  • Ease of Admin: 9.0/10 (Category avg: 8.5/10)

Who Is the Company Behind Weka?

  • Seller: Weka
  • Year Founded: 1964
  • HQ Location: Hamilton, NZ
  • Twitter: @WekaMOOC
    1,458 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    3,719 employees on LinkedIn®

Who Uses This Product?

  • Company Size: 77% Large, 23% Medium

What Are Recent G2 Reviews of Weka?

BMC AMI DevX

BMC AMI DevX is a mainframe DevOps platform for IBM Z environments that helps development and platform engineering teams increase release velocity, reduce change risk, and build a sustainable mainframe developer workforce. Whether the priority is attracting the next generation of mainframe talent, safely evolving decades of business-critical code, accelerating release velocity, or demonstrating development ROI to leadership — BMC AMI DevX is designed to address all on a single platform. Teams can connect existing tools and adopt capabilities incrementally using an open-borders integration approach. A 2025 Forrester Total Economic Impact study found that customers using BMC AMI DevX onboarded developers 50% faster, completed code changes 33% faster, increased release frequency by 50%, and reduced change failure rate by 33%. Key capabilities: - Modern IDE integration (VS Code, Eclipse) with a unified development environment that reduces context switching - AI-powered code analysis including dependency mapping, impact analysis, and runtime execution path visualization - Automated unit, functional, integration, and performance testing with code coverage analysis - Git-compatible CI/CD integration with event-driven webhooks and an open plug-in library - DORA metrics and DevOps KPI tracking with AI/ML anomaly detection across the mainframe SDLC

Average Rating: 4.2/5.0

Total Reviews: 89

How Do G2 Users Rate BMC AMI DevX?

  • Has the product been a good partner in doing business?: 8.6/10 (Category avg: 8.7/10)
  • Ease of Use: 8.3/10 (Category avg: 8.5/10)
  • Quality of Support: 8.4/10 (Category avg: 8.4/10)
  • Ease of Admin: 8.5/10 (Category avg: 8.5/10)

Who Is the Company Behind BMC AMI DevX?

  • Seller: BMC Software
  • Company Website:
  • Year Founded: 1980
  • HQ Location: Houston, TX
  • Twitter: @BMCSoftware
    47,946 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    8,646 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Software Engineer
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 44% Large, 28% Medium

What Do G2 Reviewers Say About BMC AMI DevX?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of BMC AMI DevX, navigating data and edits effortlessly with intelligent features.
  • Users value the industry benchmarking feature in BMC AMI DevX for its insightful performance comparisons and reporting assistance.
  • Users find bug detection features in BMC AMI DevX vital for tracking and improving software quality over time.
  • Users appreciate the excellent customer support provided by BMC AMI DevX, enhancing their overall experience.
  • Users value the smooth integration of Machine Learning in BMC AMI DevX, enhancing KPI management effectively.
Cons
  • Users face complexity and limitations in customization with BMC AMI DevX, hindering their ability to tailor experiences.
  • Users find the limited customization of BMC AMI DevX frustrating, hindering tailored experiences for unique organizational needs.
  • Users face compatibility issues when using BMC AMI DevX with non-BMC tools, limiting its effectiveness and integration.
  • Users find the complex setup of BMC AMI DevX challenging, facing difficulties with customization and understanding data schemas.
  • Users experience configuration issues due to limited customization options and a steep learning curve for tailoring dashboards.

What Are Recent G2 Reviews of BMC AMI DevX?

What Are G2 Users Discussing About BMC AMI DevX?

scikit-learn

Scikit-learn is a software machine learning library for the Python programming language that has a various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.

Average Rating: 4.8/5.0

Total Reviews: 60

How Do G2 Users Rate scikit-learn?

  • Has the product been a good partner in doing business?: 9.2/10 (Category avg: 8.7/10)
  • Ease of Use: 9.6/10 (Category avg: 8.5/10)
  • Quality of Support: 9.4/10 (Category avg: 8.4/10)
  • Ease of Admin: 9.4/10 (Category avg: 8.5/10)

Who Is the Company Behind scikit-learn?

  • Seller: scikit-learn
  • Year Founded: 2018
  • HQ Location: N/A
  • Twitter: @scikit_learn
    22,807 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    18 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Machine Learning Engineer, Senior Software Engineer
  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 40% Large, 32% Medium

What Do G2 Reviewers Say About scikit-learn?

AI-generated summary from verified user reviews

Pros
  • Users find scikit-learn's ease of use perfect for beginners, allowing focus on training and outputs effortlessly.
  • Users appreciate the clean and user-friendly API of scikit-learn, making it ideal for learning machine learning concepts.
  • Users find scikit-learn to have a clean and user-friendly API, making it ideal for machine learning beginners.
Cons
  • Users experience lagging issues when using scikit-learn with heavy models, impacting their overall performance and output.
  • Users experience limited customization options in scikit-learn, making algorithm control challenging for advanced needs.
  • Users find time consumption significant due to the steep learning curve and limited customization in scikit-learn.

What Are Recent G2 Reviews of scikit-learn?

What Are G2 Users Discussing About scikit-learn?

Mathematica

Mathematica is a computational software program based on symbolic mathematics, developed by Wolfram Research.

Average Rating: 4.1/5.0

Total Reviews: 86

How Do G2 Users Rate Mathematica?

  • Has the product been a good partner in doing business?: 5.8/10 (Category avg: 8.7/10)
  • Ease of Use: 7.3/10 (Category avg: 8.5/10)
  • Quality of Support: 7.9/10 (Category avg: 8.4/10)
  • Ease of Admin: 9.2/10 (Category avg: 8.5/10)

Who Is the Company Behind Mathematica?

  • Seller: Wolfram Research
  • Year Founded: 1987
  • HQ Location: Champaign, US
  • Twitter: @WolframResearch
    68,699 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    629 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Research Assistant
  • Top Industries: Research, Information Technology and Services
  • Company Size: 45% Large, 31% Small

What Are Recent G2 Reviews of Mathematica?

What Are G2 Users Discussing About Mathematica?

SAS Model Manager

SAS® Model Manager is a web-based application that enables organizations to register, modify, track, score, publish, and report on analytical models. Organizations can store models within folders or projects, develop and validate candidate models, and assess candidate models for champion model selection. They can then publish and monitor champion models. All model development and model maintenance personnel, including data modelers, validation testers, scoring officers, and analysts can use SAS Model Manager.

Average Rating: 4.6/5.0

Total Reviews: 56

How Do G2 Users Rate SAS Model Manager?

  • Has the product been a good partner in doing business?: 7.9/10 (Category avg: 8.7/10)
  • Ease of Use: 8.0/10 (Category avg: 8.5/10)
  • Quality of Support: 8.8/10 (Category avg: 8.4/10)
  • Ease of Admin: 7.3/10 (Category avg: 8.5/10)

Who Is the Company Behind SAS Model Manager?

  • Seller: SAS Institute
  • Year Founded: 1976
  • HQ Location: Cary, NC
  • Twitter: @SASsoftware
    60,863 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    15,122 employees on LinkedIn®
  • Phone: 1-800-727-0025

Who Uses This Product?

  • Who Uses This: Inside Sales Manager
  • Top Industries: Computer Software
  • Company Size: 59% Large, 27% Small

What Do G2 Reviewers Say About SAS Model Manager?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the simplicity and efficiency of Model Management, enabling seamless collaboration and automated processes for ML models.
  • Users appreciate the variety of model management features in SAS Model Manager that enhance collaboration and simplify workflows.
  • Users value the simplicity and efficiency of SAS Model Manager for managing classical ML models and analytics processes.
  • Users appreciate the automation capabilities of SAS Model Manager, significantly reducing time and effort in modeling processes.
  • Users value the collaboration features of SAS Model Manager, facilitating seamless sharing and teamwork on models.
Cons
  • Users often struggle with a steep learning curve due to navigational challenges in the documentation and resources.
  • Users find the complexity of SAS Model Manager challenging, affecting their ability to use it effectively.
  • Users face significant complexity issues with SAS Model Manager, making navigation and usability a challenge.
  • Users find difficult learning due to non-intuitive parameter tuning options and challenges in finding specific tweaks.
  • Users often struggle with difficult navigation in SAS Model Manager, making it challenging to locate necessary documentation.

What Are Recent G2 Reviews of SAS Model Manager?

Shalaka Joshi
SJ
Researched and written by Shalaka Joshi
Updated