# Best MLOps Platforms

## How Many MLOps Platforms Products Does G2 Track?

**Total Products under this Category:** 362

### Category Stats (Sep 2026)

- **Average Rating:** 4.51/5 (↑0.01 vs Aug 2026) The average rating of products in this category, based on all submitted ratings
- **Top Trending Product:** Anyscale (+4.16%) - 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 MLOps Platforms Products?

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

- 30 Analysts and Data Experts
- 7,800+ Authentic Reviews
- 362+ 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 MLOps Platforms
 ![G2 Grid® for MLOps Platforms plotting products by satisfaction and market presence](https://www.g2.com/categories/mlops-platforms/grids.png?focus%5B%5D=10470&focus%5B%5D=21469&focus%5B%5D=1333204&focus%5B%5D=1308795&focus%5B%5D=1191919&focus%5B%5D=125020&focus%5B%5D=52115&focus%5B%5D=10938)

Highlighted products: Databricks, Gemini Enterprise Agent Platform, Microsoft Fabric, IBM watsonx.ai, Vertex Explainable AI, Roboflow, Amazon SageMaker, and Snowflake.

Underlying data: [Grid® JSON](https://www.g2.com/categories/mlops-platforms/grids.json?focus%5B%5D=databricks&focus%5B%5D=gemini-enterprise-agent-platform&focus%5B%5D=microsoft-fabric&focus%5B%5D=ibm-watsonx-ai&focus%5B%5D=vertex-explainable-ai&focus%5B%5D=roboflow&focus%5B%5D=amazon-sagemaker&focus%5B%5D=snowflake)

**Sponsored**

### 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.

[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=1910&secure%5Bchosen_at%5D=2026-09-02T20%3A36%3A00Z&secure%5Bdisplayable_resource_id%5D=1910&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=1910&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=1886&secure%5Bresource_id%5D=1910&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fmlops-platforms&secure%5Btoken%5D=4111159ece33f3522863281c4a4bf0d41154f3123974f7870366de3e2bd36167&secure%5Burl%5D=https%3A%2F%2Fwww.cloudera.com%2Fproducts%2Fcloudera-data-platform%2Fcdp-demos.html%3Finternal_link%3Dp18%23get-started&secure%5Burl_type%5D=custom_url)

### [Databricks](https://www.g2.com/products/databricks/reviews)

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics, and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. Founded in 2013 by the original creators of Apache Spark™, Delta Lake, MLflow and Unity Catalog, Databricks is built on an open lakehouse architecture that brings data, analytics and AI together. The platform is used by data engineers, data scientists, analysts, developers, machine learning teams, AI teams and business users to collaborate across the full data and AI lifecycle. Key Databricks capabilities include: - Data engineering: Build, automate and manage reliable batch, streaming and real-time data pipelines. - Analytics and business intelligence: Run SQL analytics, create dashboards and enable business teams to explore data. - Data governance: Discover, secure and manage data and AI assets across teams, clouds and workloads. - Machine learning and AI: Develop models, build generative AI applications and create production-grade AI agents. - Data applications: Build and deploy data-driven applications using governed enterprise data. Available across AWS, Azure and Google Cloud, Databricks helps organizations work across clouds, reduce data silos and simplify collaboration across teams and tools. Customers use Databricks for use cases such as customer personalization, fraud detection, predictive maintenance, real-time analytics, cybersecurity, healthcare research, financial risk management, supply chain optimization and AI-powered decision-making. Databricks is used across industries including financial services, healthcare and life sciences, retail, manufacturing, energy and the public sector. Organizations use the platform to modernize data infrastructure, accelerate AI adoption and turn enterprise data into business value.

**Average Rating:** 4.6/5.0

**Total Reviews:** 1,326

#### How Do G2 Users Rate Databricks?

- **Ease of Use:** 8.8/10 (Category avg: 8.8/10)
- **Scalability:** 9.0/10 (Category avg: 9.0/10)
- **Metrics:** 8.8/10 (Category avg: 8.7/10)
- **Framework Flexibility:** 8.8/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Databricks?

- **Seller:** [Databricks Inc.](https://www.g2.com/sellers/databricks-inc)
- **Company Website:** databricks.com
- **Year Founded:** 2013
- **HQ Location:** San Francisco, CA
- **Twitter:** @databricks  
92,269 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=bddca64732f61b923d96364e8c8eb35711aab4f98797cb00ab071ff24fbdd392&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F3477522%2F&secure%5Burl_type%5D=linkedin_company_website)  
15,627 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Data Engineer, Data Analyst
- **Top Industries:** Information Technology and Services, Financial Services
- **Company Size:** 48% Large, 38% Medium

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

_AI-generated summary from verified user reviews_

##### Pros

- Users enjoy the **ease of use and extensive features** of Databricks, streamlining data warehousing and machine learning tasks.
- Users value the **seamless integrations with AWS services** that enhance efficiency and support diverse business needs.
- Users appreciate the **ease of use** of Databricks, enhancing their experience with its intuitive interface and efficient features.
- Users value the **seamless collaboration** provided by Databricks, enhancing teamwork on data projects and insights sharing.
- Users value the **effective data management features** of Databricks, simplifying their workflows and enhancing decision-making.

##### Cons

- Users face a **steep learning curve** with Databricks, as its complexity can be confusing for newcomers.
- Users note that the **cost of Databricks can be quite high** , particularly for large data projects and limited free options.
- Users express frustration over **missing features** in Databricks, limiting its effectiveness for complex deployments and custom setups.
- Users find the **steep learning curve** of Databricks challenging, particularly for those unfamiliar with big data tools.
- Users face **unintuitive UI issues** that lead to random errors and complicate the experience for non-technical users.

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

**["Databricks Streamlines ETL and Analytics with Scalable Notebooks"](https://www.g2.com/survey_responses/databricks-review-13181721)**

**Rating:** 5.0/5.0 stars

_— Diana C._

[Read full review](https://www.g2.com/survey_responses/databricks-review-13181721)

**["Reliable Platform for Building Scalable Data Pipelines"](https://www.g2.com/survey_responses/databricks-review-13198355)**

**Rating:** 5.0/5.0 stars

_— aravind k._

[Read full review](https://www.g2.com/survey_responses/databricks-review-13198355)

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

- [What does Databricks software do?](https://www.g2.com/discussions/what-does-databricks-software-do) - 3 comments, 1 upvote
- [What is Databricks unified analytics platform?](https://www.g2.com/discussions/what-is-databricks-unified-analytics-platform) - 3 comments
- [What is Lakehouse in Databricks?](https://www.g2.com/discussions/what-is-lakehouse-in-databricks) - 4 comments, 3 upvotes
- [What are the features of Databricks?](https://www.g2.com/discussions/what-are-the-features-of-databricks) - 4 comments, 2 upvotes

### [Gemini Enterprise Agent Platform](https://www.g2.com/products/gemini-enterprise-agent-platform/reviews)

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:** 728

#### How Do G2 Users Rate Gemini Enterprise Agent Platform?

- **Ease of Use:** 8.2/10 (Category avg: 8.8/10)
- **Scalability:** 8.8/10 (Category avg: 9.0/10)
- **Metrics:** 8.2/10 (Category avg: 8.7/10)
- **Framework Flexibility:** 8.3/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Gemini Enterprise Agent Platform?

- **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?

- **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 Enterprise Agent 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 Enterprise Agent Platform?

**["Easy AI Agent Creation"](https://www.g2.com/survey_responses/gemini-enterprise-agent-platform-review-13193916)**

**Rating:** 4.5/5.0 stars

_— Belhaje A._

[Read full review](https://www.g2.com/survey_responses/gemini-enterprise-agent-platform-review-13193916)

**["Helped us automate routine work and save hours every week"](https://www.g2.com/survey_responses/gemini-enterprise-agent-platform-review-13212825)**

**Rating:** 4.5/5.0 stars

_— Pavan Simhadri D._

[Read full review](https://www.g2.com/survey_responses/gemini-enterprise-agent-platform-review-13212825)

#### What Are G2 Users Discussing About Gemini Enterprise Agent Platform?

- [What is Google Cloud AI Platform used for?](https://www.g2.com/discussions/what-is-google-cloud-ai-platform-used-for) - 5 comments, 5 upvotes
- [What software libraries does cloud ML engine support?](https://www.g2.com/discussions/what-software-libraries-does-cloud-ml-engine-support) - 4 comments, 5 upvotes
- [How do I use Google cloud platform for machine learning?](https://www.g2.com/discussions/how-do-i-use-google-cloud-platform-for-machine-learning)
- [Is Google Cloud AI free?](https://www.g2.com/discussions/is-google-cloud-ai-free)
- [What is Google AI platform?](https://www.g2.com/discussions/what-is-google-ai-platform) - 3 comments, 3 upvotes

### [Microsoft Fabric](https://www.g2.com/products/microsoft-fabric/reviews)

Microsoft Fabric is a comprehensive, AI-powered data analytics platform that unifies various data management and analysis tools into a single, integrated environment. It combines the capabilities of Microsoft Power BI, Azure Synapse Analytics, and Azure Data Factory, offering a seamless experience for data integration, engineering, warehousing, real-time analytics, data science, and business intelligence. By centralizing these services, Fabric simplifies data management, enhances collaboration, and accelerates the transformation of raw data into actionable insights. Key Features and Functionality: - Unified Data Lake (OneLake): Fabric provides a single, AI-ready data lake that centralizes and curates all business data within a unified, governed hub, ensuring all teams access accurate datasets securely. - AI-Powered Tools: The platform offers AI-enhanced tools tailored for various data projects, enabling teams to innovate faster and derive near real-time insights that drive business impact. - Integrated Analytics Solutions: Fabric encompasses data integration, data engineering, data warehousing, real-time analytics, data science, and business intelligence, all hosted on a lake-centric SaaS solution for simplicity and to maintain a single source of truth. - Built-in Security and Governance: With robust data security, governance, and compliance features, Fabric ensures that data is managed responsibly and in accordance with industry standards. Primary Value and User Solutions: Microsoft Fabric addresses the complexities associated with managing disparate data systems by providing a unified platform that streamlines data workflows. It empowers organizations to harness the full potential of their data, facilitating informed decision-making and fostering innovation. By integrating various data services, Fabric reduces operational overhead, enhances productivity, and supports the development of AI-driven solutions, positioning businesses to thrive in a data-centric landscape.

**Average Rating:** 4.7/5.0

**Total Reviews:** 44

#### How Do G2 Users Rate Microsoft Fabric?

- **Ease of Use:** 9.1/10 (Category avg: 8.8/10)
- **Scalability:** 9.3/10 (Category avg: 9.0/10)
- **Metrics:** 8.9/10 (Category avg: 8.7/10)
- **Framework Flexibility:** 9.3/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Microsoft Fabric?

- **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:** Information Technology and Services, Insurance
- **Company Size:** 38% Large, 38% Medium

#### What Do G2 Reviewers Say About Microsoft Fabric?

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **ease of use** in Microsoft Fabric, enjoying seamless integration and quick learning for analysts.
- Users praise the **responsive and supportive customer service** of Microsoft Fabric, highlighting their dedication to resolving queries.
- Users find Microsoft Fabric to be **intuitive and easy to use** , enabling quick solutions without coding experience.
- Users highlight the **easy setup** of Microsoft Fabric, enabling quick utilization without coding experience required.
- Users value the **unified platform** of Microsoft Fabric, seamlessly integrating data engineering, analytics, and visualization for efficiency.

##### Cons

- Users face **formula limitations** with Microsoft Fabric, finding discrepancies compared to Excel that require adjustment and assistance.
- Users face a **steep learning curve** with Microsoft Fabric, particularly those transitioning from familiar tools like Excel.
- Users face **Excel compatibility issues** , making formula translation and usage challenging at times, though support is helpful.
- Users find the **learning curve steep** with Microsoft Fabric, especially for those transitioning from familiar tools like Excel.
- Users find that **training is required** to adjust to Microsoft Fabric's formula differences from Excel, but support is available.

#### What Are Recent G2 Reviews of Microsoft Fabric?

**["Finally got our data stack in one place, but costs need attention"](https://www.g2.com/survey_responses/microsoft-fabric-review-12740895)**

**Rating:** 4.0/5.0 stars

_— rishabh m._

[Read full review](https://www.g2.com/survey_responses/microsoft-fabric-review-12740895)

**["Great platform for data analytics development and workflow management"](https://www.g2.com/survey_responses/microsoft-fabric-review-10981663)**

**Rating:** 4.5/5.0 stars

_— Amr a._

[Read full review](https://www.g2.com/survey_responses/microsoft-fabric-review-10981663)

### [IBM watsonx.ai](https://www.g2.com/products/ibm-watsonx-ai/reviews)

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:** 142

#### How Do G2 Users Rate IBM watsonx.ai?

- **Ease of Use:** 8.8/10 (Category avg: 8.8/10)
- **Scalability:** 8.8/10 (Category avg: 9.0/10)
- **Metrics:** 9.1/10 (Category avg: 8.7/10)
- **Framework Flexibility:** 8.7/10 (Category avg: 8.7/10)

#### Who Is the Company Behind IBM watsonx.ai?

- **Seller:** [IBM](https://www.g2.com/sellers/ibm)
- **Company Website:** www.ibm.com
- **Year Founded:** 1911
- **HQ Location:** Armonk, New York, United States
- **Twitter:** @IBMSecurity  
74,660 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=14b544adaece4fdbc987f1d7f7028048c22259946811200cc751263825586af9&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1009%2F&secure%5Burl_type%5D=linkedin_company_website)  
328,202 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 AI studio** of IBM watsonx.ai, enabling efficient chatbot creation with minimal coding.
- Users appreciate the **user-friendly platform** that simplifies building and deploying AI models efficiently and effectively.
- 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 find the **complex setup** of IBM watsonx.ai challenging, especially for newcomers and small teams seeking ease of use.

#### What Are Recent G2 Reviews of IBM watsonx.ai?

**["Unified, Governed AI Studio with Strong Performance and Seamless IBM Integrations"](https://www.g2.com/survey_responses/ibm-watsonx-ai-review-13184421)**

**Rating:** 4.0/5.0 stars

_— Manan S._

[Read full review](https://www.g2.com/survey_responses/ibm-watsonx-ai-review-13184421)

**["IBM watsonx.ai Makes It Easy to Bring Foundation Models into Real Business Workflows"](https://www.g2.com/survey_responses/ibm-watsonx-ai-review-13271627)**

**Rating:** 4.5/5.0 stars

_— Balaji S._

[Read full review](https://www.g2.com/survey_responses/ibm-watsonx-ai-review-13271627)

### [Roboflow](https://www.g2.com/products/roboflow/reviews)

Roboflow has everything you need to build and deploy computer vision applications. Over 1,000,000 users from businesses of every size — from startups to public companies — use the company's end-to-end platform for image and video collection, organization, annotation, preprocessing, model training, and deployment. Roboflow provides tools for each step in the computer vision deployment lifecycle and integrates with your existing solutions so you can tailor your pipeline to meet your needs.

**Average Rating:** 4.7/5.0

**Total Reviews:** 159

#### How Do G2 Users Rate Roboflow?

- **Ease of Use:** 9.3/10 (Category avg: 8.8/10)
- **Scalability:** 10.0/10 (Category avg: 9.0/10)
- **Metrics:** 10.0/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Roboflow?

- **Seller:** [Roboflow](https://www.g2.com/sellers/roboflow)
- **Year Founded:** 2019
- **HQ Location:** Remote, US
- **Twitter:** @roboflow  
13,577 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=660f87d85fdd82e0f1cecfe2354a16103bb5a6f5508134496575ec655201678c&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F36096640&secure%5Burl_type%5D=linkedin_company_website)  
144 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Founder, Researcher
- **Top Industries:** Computer Software, Research
- **Company Size:** 78% Small, 14% Medium

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

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **ease of use** of Roboflow, enabling efficient model training and collaboration with a user-friendly interface.
- Users highlight Roboflow's **efficiency** in dataset management, streamlining tasks and significantly saving time and reducing errors.
- Users value the **annotation efficiency** of Roboflow, enjoying time savings and reduced errors in dataset management.
- Users love how Roboflow's **data labeling** simplifies collaboration, annotation, and export processes, saving time and reducing errors.
- Users appreciate the **powerful and versatile features** of Roboflow, making it ideal for academic and large-scale projects.

##### Cons

- Users find the **cost prohibitive** for advanced features, especially students needing budget-friendly options.
- Users note the **limited features** of Roboflow, as some advanced options require higher-tier plans and constraints exist.
- Users experience **limited functionality** in Roboflow, particularly with advanced features and flexibility for complex tasks.
- Users find **annotation issues** with Roboflow, especially in auto-labeling and polygon marking for complex images.
- Users find **inefficient labeling** processes cumbersome, especially in team environments with a lack of automation and shortcuts.

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

**["Roboflow Makes Computer Vision Projects Easy to Build, Train, and Deploy"](https://www.g2.com/survey_responses/roboflow-review-12984362)**

**Rating:** 5.0/5.0 stars

_— noah r._

[Read full review](https://www.g2.com/survey_responses/roboflow-review-12984362)

**["Great for AI annotation, Easy to use, Need more API flexibility"](https://www.g2.com/survey_responses/roboflow-review-13383117)**

**Rating:** 4.5/5.0 stars

_— Tejas K._

[Read full review](https://www.g2.com/survey_responses/roboflow-review-13383117)

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

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.

**Average Rating:** 4.3/5.0

**Total Reviews:** 54

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

- **Ease of Use:** 8.4/10 (Category avg: 8.8/10)
- **Scalability:** 9.6/10 (Category avg: 9.0/10)
- **Metrics:** 9.4/10 (Category avg: 8.7/10)
- **Framework Flexibility:** 8.8/10 (Category avg: 8.7/10)

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

- **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, Computer Software
- **Company Size:** 33% Large, 33% Medium

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

_AI-generated summary from verified user reviews_

##### Pros

- Users find the **ease of use** of Amazon SageMaker exceptional, allowing quick adaptation and straightforward model training.
- Users value the **seamless AI integration** of Amazon SageMaker, streamlining the entire machine learning lifecycle efficiently.
- Users appreciate the **superior computing power** of Amazon SageMaker, significantly reducing model training time and enhancing productivity.
- Users praise Amazon SageMaker for its **efficient training process** , drastically reducing model training time and simplifying functionality.
- Users highlight the **fast processing** of Amazon SageMaker, significantly reducing model training time and enhancing productivity.

##### Cons

- Users find that Amazon SageMaker can become **expensive** , particularly with long-running jobs and complex pricing structures.
- Users find the **complex pricing structure** of Amazon SageMaker can lead to unexpected costs and confusion.
- Users find the **complexity of pricing** in SageMaker challenging, often leading to unexpected costs and confusion.
- Users find the **steep learning curve** for Amazon SageMaker challenging, particularly for those new to AWS services.
- Users find a **difficult learning curve** during the initial setup of Amazon SageMaker, impacting usability.

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

**["End-to-End ML Platform That Streamlines the Full Lifecycle"](https://www.g2.com/survey_responses/amazon-sagemaker-review-13180609)**

**Rating:** 4.5/5.0 stars

_— Atharva P._

[Read full review](https://www.g2.com/survey_responses/amazon-sagemaker-review-13180609)

**["Fully Managed End-to-End ML in AWS with Powerful Distributed Training"](https://www.g2.com/survey_responses/amazon-sagemaker-review-12853074)**

**Rating:** 4.0/5.0 stars

_— Hem J._

[Read full review](https://www.g2.com/survey_responses/amazon-sagemaker-review-12853074)

#### What Are G2 Users Discussing About Amazon SageMaker?

- [What is Amazon SageMaker used for?](https://www.g2.com/discussions/what-is-amazon-sagemaker-used-for)
- [Is AWS SageMaker good?](https://www.g2.com/discussions/is-aws-sagemaker-good) - 1 upvote
- [Who uses SageMaker?](https://www.g2.com/discussions/who-uses-sagemaker)
- [How do you use Amazon SageMaker?](https://www.g2.com/discussions/how-do-you-use-amazon-sagemaker)
- [What does Amazon SageMaker do?](https://www.g2.com/discussions/what-does-amazon-sagemaker-do)

### [Vertex Explainable AI](https://www.g2.com/products/vertex-explainable-ai/reviews)

Understand AI output and build trust. Explainable AI is a set of tools and frameworks to help you understand and interpret predictions made by your machine learning models, natively integrated with a number of Google's products and services. With it, you can debug and improve model performance, and help others understand your models' behavior. You can also generate feature attributions for model predictions in AutoML Tables, BigQuery ML and Vertex AI, and visually investigate model behavior using the What-If Tool.

**Average Rating:** 4.7/5.0

**Total Reviews:** 14

#### How Do G2 Users Rate Vertex Explainable AI?

- **Ease of Use:** 8.8/10 (Category avg: 8.8/10)
- **Scalability:** 10.0/10 (Category avg: 9.0/10)
- **Metrics:** 9.7/10 (Category avg: 8.7/10)
- **Framework Flexibility:** 9.3/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Vertex Explainable AI?

- **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:** 36% Large, 36% Small

#### What Do G2 Reviewers Say About Vertex Explainable AI?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **collaboration capabilities** of Vertex Explainable AI, enhancing teamwork and shared insights effectively.
- Users recognize **cost savings** from using Vertex Explainable AI, enhancing efficiency while managing budgetary constraints.
- Users feel the need for improved **data management capabilities** in Vertex Explainable AI for enhanced explainability.
- Users find **easy access** to Vertex Explainable AI beneficial for understanding AI model outputs efficiently.
- Users note the **easy integrations** of Vertex Explainable AI, allowing seamless connections with existing systems.

#### What Are Recent G2 Reviews of Vertex Explainable AI?

**["Powerful AI Transparency and Trust-Building Tool for Machine Learning Models"](https://www.g2.com/survey_responses/vertex-explainable-ai-review-13341769)**

**Rating:** 5.0/5.0 stars

_— Khushal M._

[Read full review](https://www.g2.com/survey_responses/vertex-explainable-ai-review-13341769)

**["Clear, Visual Model Explanations That Fit Seamlessly into Vertex AI Workflows"](https://www.g2.com/survey_responses/vertex-explainable-ai-review-13225263)**

**Rating:** 4.5/5.0 stars

_— Muhammed A._

[Read full review](https://www.g2.com/survey_responses/vertex-explainable-ai-review-13225263)

### [Snowflake](https://www.g2.com/products/snowflake/reviews)

Snowflake makes enterprise AI easy, efficient and trusted. Thousands of companies around the globe, including hundreds of the world’s largest, use Snowflake’s AI Data Cloud to share data, build applications, and power their business with AI. The era of enterprise AI is here. Learn more at snowflake.com (NYSE: SNOW).

**Average Rating:** 4.6/5.0

**Total Reviews:** 714

#### How Do G2 Users Rate Snowflake?

- **Ease of Use:** 9.0/10 (Category avg: 8.8/10)
- **Scalability:** 9.4/10 (Category avg: 9.0/10)
- **Metrics:** 8.9/10 (Category avg: 8.7/10)
- **Framework Flexibility:** 9.5/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Snowflake?

- **Seller:** [Snowflake, Inc.](https://www.g2.com/sellers/snowflake-inc)
- **Company Website:** www.snowflake.com
- **Year Founded:** 2012
- **HQ Location:** 135 Constitution Drive, Menlo Park CA
- **Twitter:** @SnowflakeDB  
278 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=ad18ff73a9b8bb34dd1b98a6ba1c6be57f7364939ad352612ecc483aba05d2b2&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fsnowflake-computing%2F&secure%5Burl_type%5D=linkedin_company_website)  
11,308 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Data Engineer, Data Analyst
- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 45% Medium, 43% Large

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

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **ease of use** of Snowflake, which simplifies data sharing and enhances productivity across teams.
- Users value the **reliable features and user-friendly interface** of Snowflake, enhancing data management and analytics efficiency.
- Users value the **seamless scalability** of Snowflake, enabling efficient handling of large datasets and workload changes without performance loss.
- Users value the **fast and efficient data processing** capabilities of Snowflake, enhancing their analysis experience significantly.

##### Cons

- Users highlight the **high costs** of Snowflake, making it less accessible for smaller businesses with limited budgets.
- Users find **feature limitations** in Snowflake, such as lack of code blocks and restricted permissions, frustrating.
- Users often struggle with **high costs** due to unoptimized queries and inadequate cost control measures in Snowflake.
- Users find the **cost structure challenging** , requiring time to optimize for efficient use of Snowflake.
- Users find Snowflake's **limited features** in dynamic scripts and monitoring hinder flexibility and usability.

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

**["Snowflake Simplifies Data Management at Scale"](https://www.g2.com/survey_responses/snowflake-review-12898129)**

**Rating:** 4.0/5.0 stars

_— Harshil A._

[Read full review](https://www.g2.com/survey_responses/snowflake-review-12898129)

**["Elastic Scaling and Fast Analytics with Snowflake"](https://www.g2.com/survey_responses/snowflake-review-13129003)**

**Rating:** 4.5/5.0 stars

_— Ravindra N._

[Read full review](https://www.g2.com/survey_responses/snowflake-review-13129003)

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

- [What is Snowflake used for?](https://www.g2.com/discussions/what-is-snowflake-used-for) - 2 comments, 1 upvote

### [SAS Viya](https://www.g2.com/products/sas-sas-viya/reviews)

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:** 4.3/5.0

**Total Reviews:** 775

#### How Do G2 Users Rate SAS Viya?

- **Ease of Use:** 8.2/10 (Category avg: 8.8/10)
- **Scalability:** 8.2/10 (Category avg: 9.0/10)
- **Metrics:** 8.7/10 (Category avg: 8.7/10)
- **Framework Flexibility:** 8.5/10 (Category avg: 8.7/10)

#### Who Is the Company Behind SAS Viya?

- **Seller:** [SAS Institute Inc.](https://www.g2.com/sellers/sas-institute-inc-df6dde22-a5e5-4913-8b21-4fa0c6c5c7c2)
- **Company Website:** www.sas.com
- **Year Founded:** 1976
- **HQ Location:** Cary, NC
- **Twitter:** @SASsoftware  
60,863 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=64db42c044af5bbad79bd9677a620a6c31a8ff1abf4e7b2a6f1d6ed9561d105d&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1491%2F&secure%5Burl_type%5D=linkedin_company_website)  
18,638 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 value the **powerful data visualization** capabilities of SAS Viya, enhancing insights and decision-making in their organizations.

##### Cons

- Users find SAS Viya **difficult for non-technical users** to navigate, impacting ease of access to reports and dashboards.
- Users find the **visualization complexity** of SAS Viya challenging, especially for those without technical expertise.
- Users find the **learning curve challenging** , especially for non-technical individuals navigating reports and dashboards.
- 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?

**["Powerful Data Management with a Steep Learning Curve"](https://www.g2.com/survey_responses/sas-viya-review-13385143)**

**Rating:** 4.0/5.0 stars

_— Joel B._

[Read full review](https://www.g2.com/survey_responses/sas-viya-review-13385143)

**["Effective Data Analysis with SAS Viya"](https://www.g2.com/survey_responses/sas-viya-review-11872818)**

**Rating:** 4.5/5.0 stars

_— Fungai J._

[Read full review](https://www.g2.com/survey_responses/sas-viya-review-11872818)

#### What Are G2 Users Discussing About SAS Viya?

- [What is SAS Visual Data Mining and Machine Learning used for?](https://www.g2.com/discussions/what-is-sas-visual-data-mining-and-machine-learning-used-for) - 2 comments

### [Weights & Biases](https://www.g2.com/products/weights-biases/reviews)

Weights & Biases is the AI developer platform to build AI applications and models with confidence. ML engineers and AI developers use W&B Weave and W&B Models to coordinate all LLMops and MLops processes, including evaluating, debugging, training, fine-tuning, and deploying. W&B Weave helps developers evaluate, monitor and iterate on their AI applications to continuously improve quality, latency, cost, and safety. W&B Models boosts experiment speed and team collaboration among ML teams, helping them bring models to production faster while ensuring performance, data reliability, and security. W&B also serves as the system of record for all ML and AI activities.

**Average Rating:** 4.5/5.0

**Total Reviews:** 60

#### How Do G2 Users Rate Weights & Biases?

- **Ease of Use:** 8.6/10 (Category avg: 8.8/10)
- **Scalability:** 8.4/10 (Category avg: 9.0/10)
- **Metrics:** 9.0/10 (Category avg: 8.7/10)
- **Framework Flexibility:** 8.7/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Weights & Biases?

- **Seller:** [CoreWeave](https://www.g2.com/sellers/coreweave)
- **Year Founded:** 2017
- **HQ Location:** New York, US
- **Twitter:** @CoreWeave  
23,758 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=8dc6fb72f750b09440d04ea4332dc85d5858c061be8cb5e2539ff9987d0c7aee&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fcoreweave%2F&secure%5Burl_type%5D=linkedin_company_website)  
2,289 employees on LinkedIn®
- **Ownership:** NASDAQ:CRWV

#### Who Uses This Product?

- **Top Industries:** Computer Software, Research
- **Company Size:** 51% Small, 33% Medium

#### What Do G2 Reviewers Say About Weights & Biases?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **ease of use** in Weights & Biases, enjoying seamless tracking and sharing of training runs.
- Users appreciate the **seamless integration and ease of use** of Weights & Biases, enhancing their research and teaching experiences.
- Users appreciate the **setup ease** of Weights & Biases, enabling effortless integration and quick result management.
- Users commend the **responsive and knowledgeable customer support** of Weights & Biases, enhancing their overall experience.
- Users appreciate the **customization flexibility** of Weights & Biases, enabling tailored logging and insightful model comparisons.

##### Cons

- Users find the **limited documentation on basic functionality** of Weights & Biases frustrating and unhelpful.
- Users find the **lack of guidance** frustrating when seeking basic functionalities due to inadequate documentation in W&B.
- Users highlight the **lack of tools** for effectively managing and discarding non-useful runs in Weights & Biases.
- Users desire more flexibility with **missing features** like global normalization and better window management upon reload.
- Users find the **poor documentation** of Weights & Biases frustrating when seeking basic functionalities.

#### What Are Recent G2 Reviews of Weights & Biases?

**["Effortless MLOps and Experiment Tracking with Powerful Real-Time Dashboards"](https://www.g2.com/survey_responses/weights-biases-review-13347960)**

**Rating:** 4.5/5.0 stars

_— Arpit C._

[Read full review](https://www.g2.com/survey_responses/weights-biases-review-13347960)

**["Seamless ML Experiment Tracking with a Clean UI and Effortless Integrations"](https://www.g2.com/survey_responses/weights-biases-review-13358049)**

**Rating:** 4.5/5.0 stars

_— Anson T._

[Read full review](https://www.g2.com/survey_responses/weights-biases-review-13358049)

#### What Are G2 Users Discussing About Weights & Biases?

- [What is Weights & Biases used for?](https://www.g2.com/discussions/what-is-weights-biases-used-for) - 2 comments

### [Azure Machine Learning](https://www.g2.com/products/microsoft-azure-machine-learning/reviews)

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?

- **Ease of Use:** 8.5/10 (Category avg: 8.8/10)
- **Scalability:** 9.2/10 (Category avg: 9.0/10)
- **Metrics:** 8.3/10 (Category avg: 8.7/10)
- **Framework Flexibility:** 9.2/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Azure Machine Learning?

- **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?

- **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?

**["Cost-Efficient Medical Data Integration Backed by Great Support"](https://www.g2.com/survey_responses/azure-machine-learning-review-12845990)**

**Rating:** 5.0/5.0 stars

_— Giridharan U._

[Read full review](https://www.g2.com/survey_responses/azure-machine-learning-review-12845990)

**["An Enterprise-Grade Way to Operationalize ML"](https://www.g2.com/survey_responses/azure-machine-learning-review-12853548)**

**Rating:** 4.0/5.0 stars

_— Vytas J._

[Read full review](https://www.g2.com/survey_responses/azure-machine-learning-review-12853548)

#### What Are G2 Users Discussing About Azure Machine Learning?

- [What is Azure Machine Learning Studio used for?](https://www.g2.com/discussions/what-is-azure-machine-learning-studio-used-for) - 1 comment
- [What type of data analysis is azure machine learning studio intended for?](https://www.g2.com/discussions/what-type-of-data-analysis-is-azure-machine-learning-studio-intended-for)
- [What are the key features of Azure Machine Learning?](https://www.g2.com/discussions/what-are-the-key-features-of-azure-machine-learning)
- [How do I use Microsoft Azure for machine learning?](https://www.g2.com/discussions/how-do-i-use-microsoft-azure-for-machine-learning)
- [What is Azure Machine Learning Studio?](https://www.g2.com/discussions/what-is-azure-machine-learning-studio)

### [Replicate](https://www.g2.com/products/cloudflare-inc-replicate/reviews)

Replicate runs and fine-tune open-source models. Deploy custom models at scale. All with one line of code.

**Average Rating:** 4.5/5.0

**Total Reviews:** 17

#### How Do G2 Users Rate Replicate?

- **Ease of Use:** 9.0/10 (Category avg: 8.8/10)
- **Scalability:** 9.5/10 (Category avg: 9.0/10)
- **Metrics:** 9.4/10 (Category avg: 8.7/10)
- **Framework Flexibility:** 9.3/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Replicate?

- **Seller:** [Cloudflare, Inc.](https://www.g2.com/sellers/cloudflare-inc)
- **Year Founded:** 2009
- **HQ Location:** San Francisco, California
- **Twitter:** @Cloudflare  
286,254 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=9ff5cfe687bc4033753bbb82d49b4ac651d4582458542d4a881a39a74fc7cad2&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F407222%2F&secure%5Burl_type%5D=linkedin_company_website)  
7,190 employees on LinkedIn®
- **Ownership:** NYSE: NET

#### Who Uses This Product?

- **Top Industries:** Information Technology and Services
- **Company Size:** 63% Small, 37% Medium

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

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **straightforward API integration** and the extensive selection of AI models available on Replicate.
- Users find the **ease of use** of Replicate remarkable, thanks to its straightforward API integration and AI model selection.

##### Cons

- Users find the **limited output options** of Replicate restrictive, hindering creativity and flexibility in generating multiple images.

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

**["Effortless Model Deployment with a Clean UI and Reliable Performance"](https://www.g2.com/survey_responses/replicate-review-13387549)**

**Rating:** 4.5/5.0 stars

_— Anson T._

[Read full review](https://www.g2.com/survey_responses/replicate-review-13387549)

**["Makes AI model deployment surprisingly easy"](https://www.g2.com/survey_responses/replicate-review-13373458)**

**Rating:** 4.5/5.0 stars

_— Varun S._

[Read full review](https://www.g2.com/survey_responses/replicate-review-13373458)

### [Dataiku](https://www.g2.com/products/dataiku/reviews)

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:** 219

#### How Do G2 Users Rate Dataiku?

- **Ease of Use:** 8.7/10 (Category avg: 8.8/10)
- **Scalability:** 9.1/10 (Category avg: 9.0/10)
- **Metrics:** 8.7/10 (Category avg: 8.7/10)
- **Framework Flexibility:** 8.6/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Dataiku?

- **Seller:** [Dataiku](https://www.g2.com/sellers/dataiku)
- **Company Website:** Dataiku.com
- **Year Founded:** 2013
- **HQ Location:** New York, NY
- **Twitter:** @dataiku  
22,917 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=e59ec8fccc02ecc4f883419e54da56d3f6fc8b1e556153f0cc01cd05e3b77faa&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fdataiku%2F&secure%5Burl_type%5D=linkedin_company_website)  
1,619 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?

**["Straightforward Visual ML Workflows with Flexible Python and SQL Options"](https://www.g2.com/survey_responses/dataiku-review-13373792)**

**Rating:** 5.0/5.0 stars

_— INDRAYUDH B._

[Read full review](https://www.g2.com/survey_responses/dataiku-review-13373792)

**["All-in-One Data Science Platform That Streamlines Workflows and Collaboration"](https://www.g2.com/survey_responses/dataiku-review-13384737)**

**Rating:** 5.0/5.0 stars

_— Rythm G._

[Read full review](https://www.g2.com/survey_responses/dataiku-review-13384737)

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

- [Is Dataiku an ETL tool?](https://www.g2.com/discussions/is-dataiku-an-etl-tool)
- [Is Dataiku web based?](https://www.g2.com/discussions/is-dataiku-web-based)
- [What is DSS Dataiku?](https://www.g2.com/discussions/what-is-dss-dataiku)
- [What is Dataiku DSS used for?](https://www.g2.com/discussions/what-is-dataiku-dss-used-for)

### [SuperAnnotate](https://www.g2.com/products/superannotate/reviews)

SuperAnnotate bridges the gap between cutting-edge AI innovation and the high-quality human data that powers it - helping advanced AI teams build more intelligent models. With a global network of thousands of rigorously vetted experts, ethical and scalable managed operations, precise talent matching, and purpose‑built technology, SuperAnnotate delivers full project visibility and unmatched data quality. SuperAnnotate powers complex annotation, evaluation, and reinforcement learning workflows to build, evaluate and align frontier AI. Trusted by innovators like Databricks, IBM and ServiceNow - and backed by NVIDIA, Dell Technologies Capital, Databricks Ventures, Cox Enterprises, and Lionel Messi’s Play Time VC - SuperAnnotate enables the world’s top AI teams to build responsible and state‑of‑the‑art models with human data.

**Average Rating:** 4.8/5.0

**Total Reviews:** 356

#### How Do G2 Users Rate SuperAnnotate?

- **Ease of Use:** 9.5/10 (Category avg: 8.8/10)
- **Scalability:** 9.9/10 (Category avg: 9.0/10)
- **Metrics:** 9.7/10 (Category avg: 8.7/10)
- **Framework Flexibility:** 9.9/10 (Category avg: 8.7/10)

#### Who Is the Company Behind SuperAnnotate?

- **Seller:** [SuperAnnotate](https://www.g2.com/sellers/superannotate)
- **Company Website:** superannotate.com
- **Year Founded:** 2018
- **HQ Location:** San Francisco, CA
- **Twitter:** @superannotate  
720 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=ed4d3a394b0ca2eaac6c63041f9bd1bf14ee26538d356cd977a2b0f50c15f4d1&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F18999422%2F&secure%5Burl_type%5D=linkedin_company_website)  
361 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Student, Data Trainer
- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 57% Small, 23% Medium

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

_AI-generated summary from verified user reviews_

##### Pros

- Users enjoy the **intuitive interface** of SuperAnnotate, which simplifies large-scale annotation projects and boosts collaboration.
- Users enjoy the **user-friendly interface** of SuperAnnotate, facilitating efficient and accurate annotations with powerful tools.
- Users praise the **annotation efficiency** of SuperAnnotate, appreciating its time-saving features and user-friendly interface.
- Users highlight the **efficiency** of SuperAnnotate, enabling quick, high-quality annotations with user-friendly tools and collaboration features.
- Users value the **high-quality annotations** provided by SuperAnnotate, enhancing efficiency and ensuring consistency across projects.

##### Cons

- Users have noted **performance issues** with SuperAnnotate, including slow loading times for large projects and technical glitches.
- Users often face **slow performance** , experiencing lag and hanging when cropping images and labeling tasks on SuperAnnotate.
- Users find the **difficult learning curve** challenging, particularly with advanced features and large datasets requiring time to master.
- Users find the **complexity for new users** of SuperAnnotate challenging, especially with advanced tools and features.
- Users find the **lack of guidance** challenging, making the learning curve steep for new users of SuperAnnotate.

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

**["Efficient and User-Friendly Data Annotation Tool"](https://www.g2.com/survey_responses/superannotate-review-13350481)**

**Rating:** 5.0/5.0 stars

_— Aggunuru V._

[Read full review](https://www.g2.com/survey_responses/superannotate-review-13350481)

**["Easy-to-Use Data Organization and Powerful Image-Splitting Tools"](https://www.g2.com/survey_responses/superannotate-review-13146852)**

**Rating:** 5.0/5.0 stars

_— Doniaa K._

[Read full review](https://www.g2.com/survey_responses/superannotate-review-13146852)

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

- [What is your experience with SuperAnnotate for data annotation, and what would you like to see improved?](https://www.g2.com/discussions/what-is-your-experience-with-superannotate-for-data-annotation-and-what-would-you-like-to-see-improved) - 1 comment
- [How do I annotate an image in OpenCV?](https://www.g2.com/discussions/how-do-i-annotate-an-image-in-opencv)
- [Is SuperAnnotate free?](https://www.g2.com/discussions/is-superannotate-free)
- [How do you use SuperAnnotate?](https://www.g2.com/discussions/how-do-you-use-superannotate)
- [What is SuperAnnotate?](https://www.g2.com/discussions/what-is-superannotate) - 1 comment, 2 upvotes

### [Apache Airflow](https://www.g2.com/products/apache-airflow/reviews)

Apache Airflow is an open-source platform designed for authoring, scheduling, and monitoring complex workflows. Developed in Python, it enables users to define workflows as code, facilitating dynamic pipeline generation and seamless integration with various technologies. Airflow's modular architecture and message queue system allow it to scale efficiently, managing workflows from single machines to large-scale distributed systems. Its user-friendly web interface provides comprehensive monitoring and management capabilities, offering clear insights into task statuses and execution logs. Key Features: - Pure Python: Workflows are defined using standard Python code, allowing for dynamic pipeline generation and easy integration with existing Python libraries. - User-Friendly Web Interface: A robust web application enables users to monitor, schedule, and manage workflows without the need for command-line interfaces. - Extensibility: Users can define custom operators and extend libraries to fit their specific environment, enhancing the platform's flexibility. - Scalability: Airflow's modular architecture and use of message queues allow it to orchestrate an arbitrary number of workers, making it ready to scale as needed. - Robust Integrations: The platform offers numerous plug-and-play operators for executing tasks across various cloud platforms and third-party services, facilitating easy integration with existing infrastructure. Primary Value and Problem Solving: Apache Airflow addresses the challenges of managing complex data workflows by providing a scalable and dynamic platform for workflow orchestration. By defining workflows as code, it ensures reproducibility, version control, and collaboration among teams. The platform's extensibility and robust integrations allow organizations to adapt it to their specific needs, reducing operational overhead and improving efficiency in data processing tasks. Its user-friendly interface and monitoring capabilities enhance transparency and control over workflows, leading to improved data quality and reliability.

**Average Rating:** 4.4/5.0

**Total Reviews:** 128

#### How Do G2 Users Rate Apache Airflow?

- **Ease of Use:** 8.5/10 (Category avg: 8.8/10)
- **Scalability:** 9.1/10 (Category avg: 9.0/10)
- **Metrics:** 8.5/10 (Category avg: 8.7/10)
- **Framework Flexibility:** 9.0/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Apache Airflow?

- **Seller:** [The Apache Software Foundation](https://www.g2.com/sellers/the-apache-software-foundation)
- **Year Founded:** 1999
- **HQ Location:** Wakefield, MA
- **Twitter:** @TheASF  
66,168 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=b8484c4bb31e87bc0ba9e683d86f2af14309539343a063507c88bcdcff98434d&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F215982%2F&secure%5Burl_type%5D=linkedin_company_website)  
2,470 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Data Engineer
- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 45% Medium, 31% Large

#### What Do G2 Reviewers Say About Apache Airflow?

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **ease of use** of Apache Airflow, facilitating seamless workflow design, scheduling, and monitoring.
- Users appreciate the **intuitive web UI** of Apache Airflow, which facilitates easy monitoring and debugging of workflows.
- Users appreciate the **flexibility** of Apache Airflow, enabling customizable workflows and seamless integration with various services.
- Users appreciate the **automation capabilities** of Apache Airflow, enabling efficient scheduling and management of workflow jobs.
- Users appreciate the **easy integrations** of Apache Airflow, which enhance its versatility for managing complex workflows.

##### Cons

- Users find the **difficult setup** of Apache Airflow challenging, particularly for newcomers and complex configurations.
- Users face a **challenging learning curve** with Airflow, finding it complicated to master operators and scheduling.
- Users find Apache Airflow has a **steep learning curve** , complicating initial setup and configuration for beginners.
- Users face a **learning difficulty** with Apache Airflow, finding the interface and debugging overly complicated.
- Users find the **user interface outdated** , hindering the efficiency and experience of using Apache Airflow.

#### What Are Recent G2 Reviews of Apache Airflow?

**["Powerful for complex ML pipelines, but comes with a steep infrastructure learning curve"](https://www.g2.com/survey_responses/apache-airflow-review-12935519)**

**Rating:** 5.0/5.0 stars

_— Sachin G._

[Read full review](https://www.g2.com/survey_responses/apache-airflow-review-12935519)

**["Scalable Workflows with Apache Airflow, Best data Engineering tool for Orchestrator,Easy Deployment"](https://www.g2.com/survey_responses/apache-airflow-review-12703177)**

**Rating:** 4.5/5.0 stars

_— Rajesh K._

[Read full review](https://www.g2.com/survey_responses/apache-airflow-review-12703177)

#### What Are G2 Users Discussing About Apache Airflow?

- [What is Apache Airflow used for?](https://www.g2.com/discussions/what-is-apache-airflow-used-for)
- [What is airflow technology?](https://www.g2.com/discussions/what-is-airflow-technology) - 1 comment
- [Is airflow a framework?](https://www.g2.com/discussions/is-airflow-a-framework) - 1 comment
- [Is Apache airflow an ETL tool?](https://www.g2.com/discussions/is-apache-airflow-an-etl-tool) - 1 comment
- [Who is using Apache airflow?](https://www.g2.com/discussions/who-is-using-apache-airflow) - 1 comment

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[Browse MLOps Platforms Themes](/categories/mlops-platforms/themes)

 ![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

Machine learning operationalization (MLOps) platforms allow users to manage, monitor, and deploy machine learning models as they are integrated into business applications, automating deployment, tracking model health and accuracy, and enabling teams to scale machine learning across the organization for tangible business impact.

### Core Capabilities of MLOps Platforms

To qualify for inclusion in the MLOps Platforms category, a product must:

- Offer a platform to monitor and manage machine learning models
- Allow users to integrate models into business applications across a company
- Track the health and performance of deployed machine learning models
- Provide a holistic management tool to better understand all models deployed across a business

### Common Use Cases for MLOps Platforms

Data science and ML engineering teams use MLOps platforms to operationalize models and maintain their performance over time. Common use cases include:

- Automating the deployment pipeline for ML models built by data scientists into production applications
- Monitoring model drift, accuracy degradation, and performance anomalies in deployed models
- Managing experiment tracking, model versioning, and security governance across the ML lifecycle

### How MLOps Platforms Differ from Other Tools

MLOps platforms focus on the maintenance and monitoring of deployed models rather than initial model development, distinguishing them from [data science and machine learning platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms), which focus on model building and training. Some MLOps solutions offer centralized management of all models across the business in a single location, and may be language-agnostic or optimized for specific languages like Python or R.

### Insights from G2 on MLOps Platforms

Based on category trends on G2, model monitoring and experiment tracking stand out as the most valued capabilities. Improved model reliability and faster iteration cycles stand out as primary benefits of adoption.

Top Tools at a Glance

| Product | Best for | User Review |
| --- | --- | --- |
| [![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/large_detail/large_detail_a6c205d533dba77b318af96d91beb2ac/databricks.jpeg "Product Avatar Image")](https://www.g2.com/products/databricks/reviews)[Databricks](https://www.g2.com/products/databricks/reviews)[4.6/5(1,357)](https://www.g2.com/products/databricks/reviews) | Unified lakehouse for ML and data engineering | "Databricks Streamlines ETL and Analytics with Scalable Notebooks" |
| [![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/large_detail/large_detail_aeae116c52945fdecd7ed16d621cb315/gemini-enterprise-agent-platform.png "Product Avatar Image")](https://www.g2.com/products/gemini-enterprise-agent-platform/reviews)[Gemini Enterprise Agent Platform](https://www.g2.com/products/gemini-enterprise-agent-platform/reviews)[4.3/5(739)](https://www.g2.com/products/gemini-enterprise-agent-platform/reviews) | End-to-end ML lifecycle on Google Cloud | "Easy AI Agent Creation" |
| [![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/large_detail/large_detail_10e5841519b4608dd7454b21976fbe8e/microsoft-fabric.png "Product Avatar Image")](https://www.g2.com/products/microsoft-fabric/reviews)[Microsoft Fabric](https://www.g2.com/products/microsoft-fabric/reviews)[4.7/5(45)](https://www.g2.com/products/microsoft-fabric/reviews) | Unified data-to-analytics pipelines inside Microsoft ecosystem | "Great platform for data analytics development and workflow management" |
| [![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/large_detail/large_detail_24bb2b0b5af8e7d875ea09d767bcb097/ibm-watsonx-ai.jpg "Product Avatar Image")](https://www.g2.com/products/ibm-watsonx-ai/reviews)[IBM watsonx.ai](https://www.g2.com/products/ibm-watsonx-ai/reviews)[4.4/5(153)](https://www.g2.com/products/ibm-watsonx-ai/reviews) | Enterprise AI governance with foundation model deployment | "IBM watsonx.ai Makes It Easy to Bring Foundation Models into Real Business Workflows" |
| [![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/large_detail/large_detail_32d733a305a4eebad1e1ed85ca724f92/roboflow.jpg "Product Avatar Image")](https://www.g2.com/products/roboflow/reviews)[Roboflow](https://www.g2.com/products/roboflow/reviews)[4.7/5(159)](https://www.g2.com/products/roboflow/reviews) | Computer vision dataset annotation to deployment | "Great for AI annotation, Easy to use, Need more API flexibility" |
| [![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/large_detail/large_detail_b3390b4cc3d92e87d570895f7358c003/amazon-sagemaker.jpg "Product Avatar Image")](https://www.g2.com/products/amazon-sagemaker/reviews)[Amazon SageMaker](https://www.g2.com/products/amazon-sagemaker/reviews)[4.3/5(57)](https://www.g2.com/products/amazon-sagemaker/reviews) | End-to-end ML workflows inside AWS ecosystem | "End-to-End ML Platform That Streamlines the Full Lifecycle" |
| [![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/large_detail/large_detail_2b00e05c107c3273cea5264090c3c1d0/snowflake.jpg "Product Avatar Image")](https://www.g2.com/products/snowflake/reviews)[Snowflake](https://www.g2.com/products/snowflake/reviews)[4.6/5(763)](https://www.g2.com/products/snowflake/reviews) | ML pipelines on centralized multi-source data | "Snowflake Simplifies Data Management at Scale" |
| [![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/large_detail/large_detail_c3e4922bb6835a32854c1dead2cda2bb/sas-sas-viya.jpg "Product Avatar Image")](https://www.g2.com/products/sas-sas-viya/reviews)[SAS Viya](https://www.g2.com/products/sas-sas-viya/reviews)[4.3/5(818)](https://www.g2.com/products/sas-sas-viya/reviews) | Enterprise ML governance with SAS code continuity | "Powerful Data Management with a Steep Learning Curve" |

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