Best Data Science and Machine Learning Platforms for Small Business - Page 2

How Many Data Science and Machine Learning Platforms Products Does G2 Track?

Total Products under this Category: 1,682

Category Stats (Sep 2026)

  • Average Rating: 4.46/5 The average rating of products in this category, based on all submitted ratings
  • Top Trending Product: Anyscale (+4.14%) - Among all products in this category, Anyscale recorded the largest rating increase compared to last month

Last updated: September 01, 2026

How Does G2 Rank Data Science and Machine Learning Platforms Products?

Why You Can Trust G2's Software Rankings:

  • 30 Analysts and Data Experts
  • 14,400+ Authentic Reviews
  • 1,682+ 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 Data Science and Machine Learning Platforms

G2 Grid® for Data Science and Machine Learning Platforms plotting products by satisfaction and market presence

Highlighted products: Gemini Enterprise Agent Platform, Databricks, SAS Viya, Deepnote, Anaconda Core, Amazon SageMaker, IBM watsonx.data, and IBM watsonx.ai.

Underlying data: [Grid® JSON](https://www.g2.com/categories/data-science-and-machine-learning-platforms/grids.json?focus%5B%5D=gemini-enterprise-agent-platform&focus%5B%5D=databricks&focus%5B%5D=sas-sas-viya&focus%5B%5D=deepnote&focus%5B%5D=anaconda-core&focus%5B%5D=amazon-sagemaker&focus%5B%5D=ibm-watsonx-data&focus%5B%5D=ibm-watsonx-ai&segment=small-business)

Deep Learning VM Image

Deep Learning VM Images are pre-configured virtual machine images optimized for data science and machine learning tasks. These images come with essential machine learning frameworks and tools pre-installed, enabling users to deploy and scale machine learning models efficiently on Google Cloud's infrastructure. Key Features and Functionality: - Pre-installed Frameworks: Support for TensorFlow Enterprise, TensorFlow, PyTorch, and generic high-performance computing, catering to various machine learning needs. - Operating System Options: Based on Debian 11 and Ubuntu 22.04, providing flexibility and compatibility with different environments. - Comprehensive Python Environment: Includes Python 3.10 with a suite of libraries such as NumPy, SciPy, Matplotlib, Pandas, NLTK, Pillow, scikit-image, OpenCV, and scikit-learn, facilitating a robust development experience. - JupyterLab Integration: Offers JupyterLab notebook environments for rapid prototyping and interactive development. - GPU Acceleration: Equipped with the latest NVIDIA drivers and packages, including CUDA 11.x and 12.x, CuDNN, and NCCL, to leverage GPU capabilities for accelerated computation. Primary Value and User Solutions: Deep Learning VM Images streamline the setup process for machine learning projects by providing ready-to-use environments with pre-installed frameworks and tools. This reduces the time and effort required for configuration, allowing data scientists and machine learning practitioners to focus on model development and experimentation. The integration with Google Cloud's scalable infrastructure ensures that users can efficiently manage and scale their machine learning workloads, whether they require CPU or GPU resources. Regular updates and community support further enhance the reliability and performance of these VM images, making them a valuable resource for accelerating machine learning initiatives.

Average Rating: 4.4/5.0

Total Reviews: 63

How Do G2 Users Rate Deep Learning VM Image?

  • Application: 8.8/10 (Category avg: 8.5/10)
  • Managed Service: 8.4/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 8.6/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.8/10 (Category avg: 8.6/10)

Who Is the Company Behind Deep Learning VM Image?

  • 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?

  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 48% Small, 34% Medium

What Do G2 Reviewers Say About Deep Learning VM Image?

AI-generated summary from verified user reviews

Pros
  • Users value the pre-installed ML frameworks and tools of Deep Learning VM Image, enhancing efficiency in projects.
  • Users find the ease of use of Deep Learning VM Image beneficial, enabling focus on development without manual setup.
  • Users value the easy integrations with cloud services, which streamline deployment and enhance productivity seamlessly.
  • Users benefit from the fast processing capabilities of Deep Learning VM Image, enhancing efficiency in deep learning projects.
  • Users benefit from the exceptional speed of Deep Learning VM Image, significantly accelerating data processing and workflow efficiency.
Cons
  • Users note the high cost of Deep Learning VM Image compared to general-purpose options, impacting budget considerations.
  • Users highlight the high costs associated with Deep Learning VM Image, particularly for GPU/TPU usage and continuous operations.
  • Users face high computational costs and latency issues with Deep Learning VM Image, impacting overall performance and expenses.
  • Users find the difficult learning curve challenging, especially for beginners navigating the complex features of Deep Learning VM Image.
  • Users report a steep learning curve for Google Deep Learning VM, making it challenging for newcomers to adapt.

What Are Recent G2 Reviews of Deep Learning VM Image?

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: 218

How Do G2 Users Rate Dataiku?

  • Application: 8.3/10 (Category avg: 8.5/10)
  • Managed Service: 8.2/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 7.8/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.0/10 (Category avg: 8.6/10)

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: 59% Large, 23% Medium

What Do G2 Reviewers Say About Dataiku?

AI-generated summary from verified user reviews

Pros
  • Users find Dataiku easy to use, simplifying ML development and helping detect opportunities and risks effortlessly.
  • Users appreciate how Dataiku simplifies ML development, enabling quick training, evaluation, and understanding of data easily.
  • 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 face slow performance with Dataiku when managing large datasets, impacting efficiency and productivity.
  • Users find the difficult learning curve challenging for beginners, impacting their ability to maximize the platform's potential.
  • 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?

Posit Team

Posit is a Public Benefit Corporation building open-source software and an enterprise data science platform. We created the RStudio IDE, Shiny, Positron, and Quarto — tools used by millions of data scientists, machine learning engineers, and researchers worldwide, including teams at 25% of the Fortune Global 100. Our commercial products help organizations put those tools into production: Posit Workbench provides centralized development environments supporting Positron, RStudio, VS Code, and Jupyter; Posit Connect handles publishing and deployment for Shiny, AI applications, Streamlit, Dash, FastAPI, Flask, Bokeh, and more; and Posit Package Manager provides security-compliant package management for R and Python.

Average Rating: 4.5/5.0

Total Reviews: 568

How Do G2 Users Rate Posit Team?

  • Application: 8.4/10 (Category avg: 8.5/10)
  • Managed Service: 8.3/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 8.6/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.3/10 (Category avg: 8.6/10)

Who Is the Company Behind Posit Team?

  • Seller: Posit
  • Year Founded: 2009
  • HQ Location: Boston, US
  • Twitter: @posit_pbc
    120,874 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    441 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Research Assistant, Graduate Research Assistant
  • Top Industries: Higher Education, Information Technology and Services
  • Company Size: 49% Large, 26% Medium

What Do G2 Reviewers Say About Posit Team?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of Posit Team, simplifying data analysis workflows and enhancing productivity.
  • Users praise Posit for its reliable performance and seamless integrations, enhancing productivity and simplifying workflows.
  • Users value Posit's commitment to open source software, enhancing productivity and integration with R programming.
  • Users appreciate the responsive and reliable customer support of Posit Team, enhancing their overall experience and productivity.
  • Users appreciate the easy integrations of Posit Team, enhancing their workflows with seamless compatibility with multiple tools.
Cons
  • Users experience slow performance with large datasets, which disrupts workflow and demands higher system requirements.
  • Users face a steep learning curve with Posit Team, making initial usage and advanced features challenging.
  • Users report performance issues with Posit Team, particularly during use with larger datasets and frequent crashes.
  • Users report a steep learning curve with Posit Team, making initial setup and advanced features challenging for newcomers.
  • Users face lagging performance with Posit Team, especially when handling large datasets, impacting overall productivity.

What Are Recent G2 Reviews of Posit Team?

What Are G2 Users Discussing About Posit Team?

Qlik Predict

Qlik AutoML (automated machine learning) brings AI-generated machine learning models and predictive analytics directly to your organization’s larger community of analytics users and teams, in a simple user experience focused on augmenting their intuition through machine intelligence. With AutoML, you can easily generate machine learning models, make predictions, and plan decisions – all within an intuitive, code-free user interface. Machine learning (ML) is a branch of artificial intelligence (AI) focused on the process of recognizing patterns in historical data to predict outcomes in the future. ML uses historically observed data as an input, applies a mathematical process against that data, and creates an output called a machine learning model based on patterns in historical data. This model can then be used to make future predictions and test scenarios.

Average Rating: 4.4/5.0

Total Reviews: 78

How Do G2 Users Rate Qlik Predict?

  • Application: 8.3/10 (Category avg: 8.5/10)
  • Managed Service: 8.2/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 7.8/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.7/10 (Category avg: 8.6/10)

Who Is the Company Behind Qlik Predict?

  • Seller: Qlik
  • Year Founded: 1993
  • HQ Location: Radnor, PA
  • Twitter: @qlik
    64,130 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    4,399 employees on LinkedIn®
  • Phone: 1 (888) 994-9854

Who Uses This Product?

  • Who Uses This: Data Analyst
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 38% Large, 31% Small

What Do G2 Reviewers Say About Qlik Predict?

AI-generated summary from verified user reviews

Pros
  • Users value the automation features of Qlik Predict, enabling seamless machine learning model creation and integration without coding.
  • Users enjoy the ease of use of Qlik Predict, benefiting from a friendly no-code interface and intuitive automation.
  • Users value the intuitive AI integration of Qlik Predict, enabling quick, no-code machine learning model deployment.
  • Users appreciate the user-friendly, no-code approach of Qlik Predict, enabling accessible machine learning for everyone.
  • Users value the user-friendly AI capabilities of Qlik Predict, enabling easy deployment of predictive models without coding.
Cons
  • Users note the limited customization of Qlik Predict, which may hinder advanced users seeking more control over their models.
  • Users experience deployment issues due to limited model flexibility and integration options within Qlik Predict.
  • Users note the lack of features in Qlik Predict, particularly regarding customization and deployment flexibility.
  • Users find the required knowledge of data science a barrier, limiting optimizations and effective model interpretation.
  • Users note the limited flexibility of Qlik Predict, particularly due to its no-code approach and ecosystem restrictions.

What Are Recent G2 Reviews of Qlik Predict?

What Are G2 Users Discussing About Qlik Predict?

Alteryx

Alteryx, through it's Alteryx One platform, helps enterprises transform complex, disconnected data into a clean, AI-ready state. Whether you’re creating financial forecasts, analyzing supplier performance, segmenting customer data, analyzing employee retention, or building competitive AI applications from your proprietary data, Alteryx One makes it easy to cleanse, blend, and analyze data to unlock the unique insights that drive impactful decisions. AI-Guided Analytics Alteryx automates and simplifies every stage of data preparation and analysis, from validation and enrichment to predictive analytics and automated insights. Incorporate generative AI directly into your workflows to streamline complex data tasks and generate insights faster. Unmatched flexibility, whether you prefer code-free workflows, natural language commands, or low-code options, Alteryx adapts to your needs. Trusted. Secure. Enterprise-Ready. Alteryx is trusted by over half of the Global 2000 and 19 of the top 20 global banks. With built-in automation, governance, and security, your workflows can scale and maintain compliance while delivering consistent results. And it doesn’t matter if your systems are on-premises, hybrid, or in the cloud; Alteryx fits effortlessly into your infrastructure. Easy to Use. Deeply Connected. What truly sets Alteryx apart is our focus on efficiency and ease of use for analysts and our active community of 700,000 Alteryx users to support you at every step of your journey. With seamless integration to data everywhere including platforms like Databricks, Snowflake, AWS, Google, SAP, and Salesforce, our platform helps unify siloed data and accelerate getting to insights. Visit Alteryx.com for more information, and to start your free trial.

Average Rating: 4.6/5.0

Total Reviews: 863

How Do G2 Users Rate Alteryx?

  • Application: 8.7/10 (Category avg: 8.5/10)
  • Managed Service: 7.9/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 7.9/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.3/10 (Category avg: 8.6/10)

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: 63% 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?

IBM Watson Studio

IBM Watson Studio on IBM Cloud Pak for Data is a leading data science and machine learning solution that helps enterprises accelerate AI-powered digital transformation. It allows businesses to scale trustworthy AI and optimize decisions. Build, run, and manage AI models on any cloud through an automated end-to-end AI lifecycle--simplifying experimentation and deployment, speeding up data exploration and preparation, and improving model development and training. Govern and monitor models to mitigate drift and bias, and manage model risk. Build a ModelOps practice that synchronizes application and model pipelines to operationalize responsible, explainable AI across your enterprise. As a key offering of IBM Cloud Pak for Data, a unified data and AI platform, Watson Studio integrates seamlessly with data management services, data privacy and security capabilities, AI application tooling, open source frameworks, and a robust technology ecosystem. It unites teams and empowers businesses to build the modern information architecture that AI requires and infuse it across the organization. IBM Watson Studio is code-optional, allowing both data scientists and business analysts to work on the same platform by providing the best of open source tools along with visual, drag-and-drop capabilities. It enables organizations to tap into data assets and inject predictions into business processes and modern applications—helping them maximize their business value. It's suited for hybrid multicloud environments that demand mission-critical performance, security, and governance. Features include: • AutoAI that eliminates time-consuming, repetitive tasks by automating data preparation, model development, feature engineering and hyperparameter optimization. • Text Analytics for uncovering insights from unstructured data • Drag-and-drop visual model-building with SPSS Modeler • Broad data access – flat files, spreadsheets, major relational databases • Sophisticated graphics engine for building stunning visualizations • Support for Python 3 Notebooks Watson Studio is available via several deployment options: • IBM Cloud Pak for Data – An open, extensible data and AI platform that runs on any cloud • IBM Cloud Pak for Data System – A hybrid cloud, on-premises platform-in-a-box • IBM Cloud Pak for Data as a Service – A set of IBM Cloud Pak for Data platform services fully managed on the IBM Cloud

Average Rating: 4.2/5.0

Total Reviews: 164

How Do G2 Users Rate IBM Watson Studio?

  • Application: 9.2/10 (Category avg: 8.5/10)
  • Managed Service: 9.3/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 8.9/10 (Category avg: 8.3/10)
  • Ease of Admin: 7.7/10 (Category avg: 8.6/10)

Who Is the Company Behind IBM Watson Studio?

  • Seller: IBM
  • 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®
  • Ownership: SWX:IBM

Who Uses This Product?

  • Who Uses This: Software Engineer, CEO
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 49% Large, 31% Small

What Do G2 Reviewers Say About IBM Watson Studio?

AI-generated summary from verified user reviews

Pros
  • Users admire the Auto AI capability of IBM Watson Studio, significantly reducing manual work and streamlining data projects.
  • Users appreciate the Auto AI capability of IBM Watson Studio, significantly reducing time spent on manual data tasks.
  • Users appreciate the user-friendly interface of IBM Watson Studio, facilitating seamless integration and efficient project collaboration.
  • Users appreciate the Auto AI capability of IBM Watson Studio, significantly reducing manual work in data preprocessing.
  • Users appreciate the easy AI integration in IBM Watson Studio, significantly enhancing their data science and ML workflows.
Cons
  • Users find the high cost of IBM Watson Studio challenging, especially for individuals and small startups.
  • Users find the steep learning curve of IBM Watson Studio challenging, making it difficult for beginners to navigate.
  • Users experience a steep learning curve with IBM Watson Studio, making it challenging for beginners to navigate its features.
  • Users find the complex interface of IBM Watson Studio challenging, particularly for those just starting out.
  • Users find the steep learning curve of IBM Watson Studio challenging, particularly for beginners navigating its complex features.

What Are Recent G2 Reviews of IBM Watson Studio?

What Are G2 Users Discussing About IBM Watson Studio?

Cloudera

Cloudera is the only hybrid data and AI platform company that large organizations trust to bring AI to their data anywhere it lives. Unlike other providers, Cloudera delivers a consistent cloud experience that converges public clouds, on-prem data centers, and the edge, leveraging a proven open-source foundation. As the pioneer in big data, Cloudera empowers businesses to apply AI and assert control over 100% of their data, in all forms, improving security, governance, and real-time and predictive insights. The world’s largest brands across all industries rely on Cloudera to transform decision-making and ultimately boost bottom lines, safeguard against threats, and save lives. The Cloudera data and AI platform includes: Cloudera AI: Deploy and scale any AI model, anywhere. Cloudera brings compute to governed data where it lives for Private AI anywhere by design. Complete control, security, and governance of mission-critical data, models, agents, and inference ensure faster sovereign AI deployments. Cloudera Data-in-Motion: Make fast decisions from real-time data anywhere. Move data with any structure from any source to any destination seamlessly across hybrid environments, enabling in-the-moment business-critical decisions by processing and analyzing real-time data anywhere, from the edge to AI, as business happens. Cloudera Open Data Lakehouse: Process any data, anywhere, for actionable insights. Make smart decisions with an open data lakehouse powered by Apache Iceberg that delivers trusted, reliable, and unified data to fuel agents, AI applications, and analytics, improving collaboration, breaking silos, and simplifying sharing. Cloudera Unified Data Fabric: Unify security and governance across the entire data estate. Move beyond fragmented data management: Break down silos and connect disparate data sources intelligently and securely to provide a unified view of all organizational data and centralized end-to-end control across complex hybrid data environments.

Average Rating: 4.2/5.0

Total Reviews: 188

How Do G2 Users Rate Cloudera?

  • Application: 9.5/10 (Category avg: 8.5/10)
  • Managed Service: 9.2/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 9.8/10 (Category avg: 8.3/10)
  • Ease of Admin: 7.9/10 (Category avg: 8.6/10)

Who Is the Company Behind Cloudera?

  • Seller: Cloudera
  • Company Website:
  • Year Founded: 2008
  • HQ Location: Santa Clara, CA
  • Twitter: @cloudera
    106,442 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    3,505 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Engineer, Software Engineer
  • Top Industries: Information Technology and Services, Banking
  • Company Size: 39% Large, 35% Small

What Do G2 Reviewers Say About Cloudera?

AI-generated summary from verified user reviews

Pros
  • Users praise the user-friendly interface of Cloudera, highlighting its simplicity in managing big data efficiently.
  • Users value the easy scalability of Cloudera, enabling efficient management of large amounts of data effortlessly.
  • Users value the robust security features of Cloudera, ensuring safe and reliable data management across platforms.
  • Users value the comprehensive suite of tools in Cloudera for effective data management and analytics.
  • Users find Cloudera's scalability and centralized administration invaluable for efficient monitoring and management of data processes.
Cons
  • Users express concerns over the high costs of Cloudera, noting it's expensive for its complexity and maintenance.
  • Users find Cloudera's database to be complex, making it challenging for inexperienced professionals to utilize effectively.
  • Users find Cloudera's setup difficult to learn, particularly challenging for beginners without adequate tutorials or guidance.
  • Users find the poor documentation of Cloudera frustrating, complicating navigation and setup for complex data configurations.
  • Users often face access issues with Cloudera, particularly with unauthorized errors in Airflow tasks and limited documentation.

What Are Recent G2 Reviews of Cloudera?

What Are G2 Users Discussing About Cloudera?

RapidCanvas

RapidCanvas takes enterprise AI from concept to production to scale. Our Hybrid Approach™ pairs elite human experts with a purpose-built agentic platform. We partner to create custom solutions that are human-led, agent-executed, and built to deliver real outcomes from day one. Most enterprise AI breaks because it fails to solve key problems of context and execution. RapidCanvas is built around solving both. Every engagement starts with your own Enterprise Context Engine™: a living intelligence at the heart of your business. It unifies your data, maps your workflows, and learns from every use case. The more you build, the smarter it gets. Every iteration feeds the engine, and the intelligence compounds, making successful execution at an enterprise scale possible. RapidCanvas serves industry leaders in manufacturing, retail and consumer goods, financial services, supply chain, and infrastructure. Solutions are enterprise-grade, scalable from the start, and compliant with the highest standards for security and privacy. Future-proof by design. Outcome-led by default.

Average Rating: 4.8/5.0

Total Reviews: 38

How Do G2 Users Rate RapidCanvas?

  • Application: 9.5/10 (Category avg: 8.5/10)
  • Managed Service: 9.2/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 8.6/10 (Category avg: 8.3/10)
  • Ease of Admin: 9.3/10 (Category avg: 8.6/10)

Who Is the Company Behind RapidCanvas?

  • Seller: RapidCanvas
  • Company Website:
  • Year Founded: 2021
  • HQ Location: Austin, Texas
  • Twitter: @rapidcanvas
    86 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    124 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 42% Small, 37% Medium

What Do G2 Reviewers Say About RapidCanvas?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of RapidCanvas, enabling quick data visualization without needing advanced technical skills.
  • Users value RapidCanvas for its time-saving features, enabling quick data visualization and streamlined report sharing.
  • Users praise the intuitive user interface of RapidCanvas for making data visualization quick and easy.
  • Users value the AI integration of RapidCanvas, enabling effective solutions and enhancing digital transformation capabilities.
  • Users value the excellent customer support of RapidCanvas, highlighting its responsiveness and helpfulness during their projects.
Cons
  • Users experience slow performance with RapidCanvas when handling large datasets, impacting efficiency during heavy data tasks.
  • Users find that customization options are limited, affecting their overall experience especially for advanced needs.
  • Users struggle with the complexity of setup, facing challenges in data extraction and AI training for accurate feedback.
  • Users struggle with the difficult setup process, finding it complex to extract data and train the AI effectively.
  • Users note insufficient learning resources for advanced use cases, hindering the ability to fully utilize RapidCanvas.

What Are Recent G2 Reviews of RapidCanvas?

Clarifai

Clarifai is a leader in AI orchestration and development, helping organizations, teams, and developers build, deploy, orchestrate, and operationalize AI at scale. Clarifai’s cutting-edge AI workflow orchestration platform leverages today's modern AI technologies like Large Language Models (LLMs), Large Vision Models (LVMs), and Retrieval Augmented Generation (RAG), data labeling, inference, and more, and is available in cloud, on-premises, or hybrid environments. Founded in 2013, Clarifai has been used to build more than 1.5 million AI models with more than 400,000 users in 170 countries. Learn more at www.clarifai.com.

Average Rating: 4.3/5.0

Total Reviews: 73

How Do G2 Users Rate Clarifai?

  • Application: 8.3/10 (Category avg: 8.5/10)
  • Managed Service: 8.1/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 8.8/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.7/10 (Category avg: 8.6/10)

Who Is the Company Behind Clarifai?

  • Seller: Clarifai
  • Year Founded: 2013
  • HQ Location: Wilmington, Delaware
  • Twitter: @clarifai
    10,922 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    48 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 62% Small, 28% Medium

What Do G2 Reviewers Say About Clarifai?

AI-generated summary from verified user reviews

Pros
  • Users appreciate Clarifai for its impressive models and flexibility, enhancing image and video recognition effectively.
  • Users value the easy AI tools of Clarifai, enabling fast and accurate image and video recognition effortlessly.
  • Users value the model variety in Clarifai, enabling tailored solutions with impressive flexibility and ease of integration.
  • Users appreciate the cutting-edge AI integration of Clarifai, enabling accurate image and video recognition through customizable models.
  • Users appreciate the cutting-edge AI capabilities of Clarifai, especially for image and video recognition tasks.
Cons
  • Users find the platform expensive for small-scale developers, as costs can accumulate quickly with usage.
  • Users find the complexity of setup and documentation challenging, especially for newcomers to the platform.
  • Users find the learning curve steep for Clarifai, particularly for those new to machine learning platforms.
  • Users face a lack of resources, hindering accessibility for small-scale developers and non-profits seeking affordable options.
  • Users often find the poor documentation of Clarifai lacking detail, hindering their ability to maximize its features.

What Are Recent G2 Reviews of Clarifai?

Altair AI Studio

Altair AI Studio (formerly RapidMiner Studio) is a data science tool that anyone can use to design and prototype highly explainable AI and machine learning models that help build trust throughout an organization. Altair AI Studio includes: - Full generative AI functionality with access to hundreds of large language models (LLMs). - Intuitive and powerful drag-and-drop canvases that give users code-like control without complexity. - Award-winning auto ML with automated clustering, predictive modeling, feature engineering, and time series forecasting. - Data connectivity, exploration, and preparation. - Deploy and manage AI projects and models at enterprise scale. - Collaborate with team members in the same environment without having to worry about overwriting each other's work. - Unify the entire data science lifecycle from data exploration and machine learning to model operations and visualization and deploy in the cloud. Altair AI Studio helps users make powerful insights accessible to the entire organization and can scale seamlessly for users and enterprises. Altair AI studio enables organizations to derive significant value from AI with minimal cost and operational impact.

Average Rating: 4.6/5.0

Total Reviews: 506

How Do G2 Users Rate Altair AI Studio?

  • Application: 8.3/10 (Category avg: 8.5/10)
  • Managed Service: 8.2/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 7.6/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.5/10 (Category avg: 8.6/10)

Who Is the Company Behind Altair AI Studio?

  • Seller: Altair
  • Company Website:
  • Year Founded: 1985
  • HQ Location: Troy, MI
  • LinkedIn® Page: www.linkedin.com
    2,630 employees on LinkedIn®
  • Ownership: NASDAQ:ALTR

Who Uses This Product?

  • Who Uses This: Student, Professor
  • Top Industries: Higher Education, Education Management
  • Company Size: 42% Small, 31% Large

What Do G2 Reviewers Say About Altair AI Studio?

AI-generated summary from verified user reviews

Pros
  • Users praise the ease of use of Altair AI Studio, finding its interface intuitive and beneficial for data tasks.
  • Users value the no-code machine learning capabilities of Altair AI Studio, facilitating easy model creation and analysis.
  • Users value the seamless AI integration of Altair AI Studio, enhancing decision-making and improving efficiency across organizations.
  • Users appreciate the advanced machine learning and data analytics in Altair AI Studio for smarter decision-making and efficiency.
  • Users value the automation capabilities of Altair AI Studio, enhancing efficiency in data processing and decision making.
Cons
  • Users find the complexity of Altair AI Studio challenging, particularly with language support and integrating legacy systems.
  • Users experience slower performance when handling large datasets in Altair AI Studio, affecting their efficiency and experience.
  • Users experience slow performance when handling large datasets, leading to slowdowns or freezing during usage.
  • Users find the complexity issues of Altair AI Studio frustrating, especially due to limited support resources.
  • Users find the complex usage of Altair AI Studio challenging, especially due to limited documentation and steep learning curve.

What Are Recent G2 Reviews of Altair AI Studio?

What Are G2 Users Discussing About Altair AI Studio?

Azure Machine Learning

Azure Machine Learning is an enterprise-grade service that facilitates the end-to-end machine learning lifecycle, enabling data scientists and developers to build, train, and deploy models efficiently. Key Features and Functionality: - Data Preparation: Quickly iterate data preparation on Apache Spark clusters within Azure Machine Learning, interoperable with Microsoft Fabric. - Feature Store: Increase agility in shipping your models by making features discoverable and reusable across workspaces. - AI Infrastructure: Take advantage of purpose-built AI infrastructure uniquely designed to combine the latest GPUs and InfiniBand networking. - Automated Machine Learning: Rapidly create accurate machine learning models for tasks including classification, regression, vision, and natural language processing. - Responsible AI: Build responsible AI solutions with interpretability capabilities. Assess model fairness through disparity metrics and mitigate unfairness. - Model Catalog: Discover, fine-tune, and deploy foundation models from Microsoft, OpenAI, Hugging Face, Meta, Cohere, and more using the model catalog. - Prompt Flow: Design, construct, evaluate, and deploy language model workflows with prompt flow. - Managed Endpoints: Operationalize model deployment and scoring, log metrics, and perform safe model rollouts. Primary Value and Solutions Provided: Azure Machine Learning accelerates time to value by streamlining prompt engineering and machine learning model workflows, facilitating faster model development with powerful AI infrastructure. It streamlines operations by enabling reproducible end-to-end pipelines and automating workflows with continuous integration and continuous delivery (CI/CD). The platform ensures confidence in development through unified data and AI governance with built-in security and compliance, allowing compute to run anywhere for hybrid machine learning. Additionally, it promotes responsible AI by providing visibility into models, evaluating language model workflows, and mitigating fairness, biases, and harm with built-in safety systems.

Average Rating: 4.3/5.0

Total Reviews: 87

How Do G2 Users Rate Azure Machine Learning?

  • Application: 8.8/10 (Category avg: 8.5/10)
  • Managed Service: 8.9/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 8.7/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.3/10 (Category avg: 8.6/10)

Who Is the Company Behind Azure Machine Learning?

  • 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?

  • Who Uses This: Software Engineer
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 40% Large, 33% Small

What Do G2 Reviewers Say About Azure Machine Learning?

AI-generated summary from verified user reviews

Pros
  • Users find Azure Machine Learning's ease of use beneficial for implementing and managing machine learning projects effectively.
  • Users appreciate the scalability and integration of Azure Machine Learning, enhancing deployment and management of models seamlessly.
  • Users value the excellent customer support of Azure Machine Learning, appreciating the comprehensive documentation and community assistance.
  • Users appreciate the ease of use and robust data management features that help in organizing and analyzing data effectively.
  • Users value the efficient environment of Azure Machine Learning for launching and monitoring machine learning jobs seamlessly.
Cons
  • Users report a challenging learning curve with Azure Machine Learning, requiring time to master its tools and interface.
  • Users find Azure Machine Learning's difficult navigation frustrating, often struggling to locate options and understand workflows.
  • Users find the disordered user interface of Azure Machine Learning frustrating, complicating their navigation and task completion.
  • Users find the complex interface of Azure Machine Learning challenging, particularly due to non-intuitive navigation and missing features.
  • Users find the difficult learning aspect challenging, especially those new to Azure or machine learning concepts.

What Are Recent G2 Reviews of Azure Machine Learning?

What Are G2 Users Discussing About Azure Machine Learning?

BigML

Enjoy the power of Programmatic Machine Learning

Average Rating: 4.7/5.0

Total Reviews: 24

How Do G2 Users Rate BigML?

  • Application: 8.3/10 (Category avg: 8.5/10)
  • Managed Service: 9.2/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 9.2/10 (Category avg: 8.3/10)
  • Ease of Admin: 9.3/10 (Category avg: 8.6/10)

Who Is the Company Behind BigML?

  • Seller: BigML
  • Year Founded: 2011
  • HQ Location: Corvallis, OR
  • Twitter: @bigmlcom
    6,077 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    28 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Software Engineer, Senior Software Engineer
  • Top Industries: Computer Software
  • Company Size: 88% Small, 8% Medium

What Are Recent G2 Reviews of BigML?

DataRobot

DataRobot’s enterprise AI platform democratizes data science with end-to-end automation for building, deploying, and managing machine learning models. This platform maximizes business value by delivering AI at scale and continuously optimizing performance over time. The company’s proven combination of cutting edge software and world-class AI implementation, training, and support services, empowers any organization – regardless of size, industry, or resources – to drive better business outcomes with AI.

Average Rating: 4.4/5.0

Total Reviews: 41

How Do G2 Users Rate DataRobot?

  • Application: 5.0/10 (Category avg: 8.5/10)
  • Managed Service: 1.7/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 5.0/10 (Category avg: 8.3/10)
  • Ease of Admin: 7.7/10 (Category avg: 8.6/10)

Who Is the Company Behind DataRobot?

  • Seller: DataRobot
  • Year Founded: 2012
  • HQ Location: Boston, Massachusetts
  • Twitter: @DataRobot
    19,225 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    886 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Computer Software, Financial Services
  • Company Size: 41% Medium, 41% Small

What Are Recent G2 Reviews of DataRobot?

Domino Enterprise AI Platform

Domino powers model-driven businesses with its leading Enterprise AI platform that accelerates the development and deployment of data science work while increasing collaboration and governance. More than 20 percent of the Fortune 100 count on Domino to help scale data science, turning it into a competitive advantage. Founded in 2013, Domino is backed by Sequoia Capital and other leading investors.

Average Rating: 4.3/5.0

Total Reviews: 28

How Do G2 Users Rate Domino Enterprise AI Platform?

  • Application: 8.5/10 (Category avg: 8.5/10)
  • Managed Service: 8.2/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 8.2/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.1/10 (Category avg: 8.6/10)

Who Is the Company Behind Domino Enterprise AI Platform?

  • Seller: Domino Data Lab
  • Year Founded: 2013
  • HQ Location: San Francisco, CA
  • Twitter: @DominoDataLab
    7,974 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    269 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 46% Large, 39% Small

What Do G2 Reviewers Say About Domino Enterprise AI Platform?

AI-generated summary from verified user reviews

Pros
  • Users find the ease of use in Domino Enterprise AI Platform exceptional, streamlining the entire AI lifecycle.
  • Users value the easy integrations with multiple cloud providers, streamlining the AI lifecycle and enhancing collaboration.
  • Users value the seamless integrations of Domino Enterprise AI Platform, enhancing efficiency and collaboration across projects.
  • Users rave about the exceptional training efficiency of Domino, significantly simplifying the AI lifecycle and collaboration.
  • Users appreciate how Domino's platform streamlines the AI lifecycle, significantly reducing overhead and enhancing collaboration and operational efficiency.
Cons
  • As an Indian customer, I find the pricing to be on the higher side, making it less accessible.
  • Users find the difficult setup of Domino Enterprise AI Platform frustrating and time-consuming for efficient use.
  • Users find the pricing to be on the higher side, which impacts their overall perception of Domino Enterprise AI Platform.
  • Users feel the platform lacks guidance for beginners, making it challenging to navigate and fully utilize its features.
  • Users express frustration over the missing features like easy coding IDE and CV video task capabilities in Domino.

What Are Recent G2 Reviews of Domino Enterprise AI Platform?

What Are G2 Users Discussing About Domino Enterprise AI Platform?

H2O

H2O.ai is the leading AI Cloud company, on a mission to democratize AI and drive an open AI movement around the world. They focus on drawing insights from structured and unstructured data like video and documents with their award-winning products like Hydrogen Torch and Document AI. Customers use the H2O AI Cloud to rapidly solve complex business problems and accelerate the discovery of new ideas. H2O.ai is the trusted AI provider to more than 20,000 global organizations, millions of data scientists and over half of the Fortune 500, including AT&T, Commonwealth Bank of Australia, Citi, GlaxoSmithKline, Hitachi, Kaiser Permanente, Procter & Gamble, PayPal, PwC, Reckitt, Unilever, Goldman Sachs, NVIDIA, and Wells Fargo are not only customers and partners, but strategic investors in the company. More than 30 Kaggle Grandmasters (the community of best-in-the-world machine learning practitioners and data scientists) are makers at H2O.ai. A strong AI for Good ethos to make the world a better place and Responsible AI drive the company’s purpose. Please join our movement at www.h2o.ai. H2O.ai offers enterprise customers with multiple platforms for AI and machine learning, including the open source distributed machine learning platform H2O-3, automatic machine learning platform H2O Driverless AI, and the recently announced H2O Q, an AI platform for business users: H2O-3 is an open source, scalable and distributed in-memory AI and machine learning platform. H2O-3 also has a strong AutoML functionality and supports the most widely used statistical and machine learning algorithms including gradient boosted machines, generalized linear models, deep learning, XGBoost and more. H2O Driverless AI empowers data scientists to work on projects faster and more efficiently by using automation to accomplish tasks quickly with automatic feature engineering, model tuning, model tuning, model selection, model validation and machine learning interpretability, custom recipes, time-series and automatic deployment pipeline generation for model scoring. H2O Q is a new AI platform that provides the essential building blocks to make AI apps and will bring the power of AI to millions of business users. It delivers automatic insights and predictions for “in the moment” business questions and is ideal for data analysts, citizen data scientists and all business users.

Average Rating: 4.5/5.0

Total Reviews: 22

How Do G2 Users Rate H2O?

  • Application: 7.0/10 (Category avg: 8.5/10)
  • Managed Service: 6.9/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 8.3/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.3/10 (Category avg: 8.6/10)

Who Is the Company Behind H2O?

  • Seller: H2O.ai
  • Year Founded: 2012
  • HQ Location: Mountain View, CA
  • Twitter: @h2oai
    25,222 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    372 employees on LinkedIn®

Who Uses This Product?

  • Company Size: 54% Small, 29% Large

What Are Recent G2 Reviews of H2O?

What Are G2 Users Discussing About H2O?