Best Enterprise Machine Learning Software

How Many Machine Learning Software Products Does G2 Track?

Total Products under this Category: 1,247

Category Stats (Nov 2026)

  • Average Rating: 4.34/5 The average rating of products in this category, based on all submitted ratings
  • Top Trending Product: Modal Labs (+1.96%) - Among all products in this category, Modal Labs recorded the largest rating increase compared to last month

Last updated: November 01, 2026

How Does G2 Rank Machine Learning Software Products?

Why You Can Trust G2's Software Rankings:

  • 30 Analysts and Data Experts
  • 18,200+ Authentic Reviews
  • 1,247+ Products
  • Unbiased Rankings

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

G2 Grid® for Machine Learning Software

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

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

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

SAS Viya

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

Average Rating: 4.3/5.0

Total Reviews: 793

How Do G2 Users Rate SAS Viya?

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

Who Is the Company Behind SAS Viya?

  • Seller: SAS Institute
  • Company Website:
  • Year Founded: 1976
  • HQ Location: Cary, NC
  • LinkedIn® Page: www.linkedin.com
    15,122 employees on LinkedIn®
  • Phone: 1-800-727-0025

Who Uses This Product?

  • Who Uses This: Student, Biostatistician
  • Top Industries: Pharmaceuticals, Banking
  • Company Size: 34% Small, 33% Large

What Do G2 Reviewers Say About SAS Viya?

AI-generated summary from verified user reviews

Pros
  • Users enjoy the ease of use of SAS Viya, thanks to its simple syntax and integrated features for analytics.
  • Users commend SAS Viya for its powerful and sophisticated features that enhance data analysis and collaboration across teams.
  • Users value the powerful analytics and integration features of SAS Viya, significantly enhancing data analysis capabilities.
  • Users value the powerful data analysis capabilities of SAS Viya, enhancing efficiency and integration for various tasks.
  • Users value the modern, intuitive user interface of SAS Viya, enhancing productivity with seamless navigation and integration.
Cons
  • Users find the learning difficulty of SAS Viya challenging, especially for beginners due to its complexity and limited resources.
  • Users find SAS Viya has a steep learning curve, making it challenging for newcomers to grasp effectively.
  • Users find SAS Viya's complexity and steep learning curve challenging, hindering effective use and self-learning opportunities.
  • Users find the difficult learning curve of SAS Viya challenging, especially for beginners seeking easier comprehension.
  • Users find the licensing costs of SAS Viya to be prohibitively expensive, especially for features they don't use.

What Are Recent G2 Reviews of SAS Viya?

What Are G2 Users Discussing About SAS Viya?

IBM watsonx.ai

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

Average Rating: 4.4/5.0

Total Reviews: 149

How Do G2 Users Rate IBM watsonx.ai?

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

Who Is the Company Behind IBM watsonx.ai?

  • Seller: IBM
  • Company Website:
  • Year Founded: 1911
  • HQ Location: Armonk, New York, United States
  • LinkedIn® Page: www.linkedin.com
    344,328 employees on LinkedIn®
  • Ownership: SWX:IBM

Who Uses This Product?

  • Who Uses This: Consultant
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 42% Small, 34% Large

What Do G2 Reviewers Say About IBM watsonx.ai?

AI-generated summary from verified user reviews

Pros
  • Users find IBM watsonx.ai extremely user-friendly, appreciating its ease of setup and convenience for real enterprise needs.
  • Users appreciate the model variety in Watsonx.ai, enabling tailored experiences through customizable, user-friendly interfaces.
  • Users value the integrated platform of IBM watsonx.ai for simplifying enterprise-grade AI development and management.
  • Users appreciate the integrated studio for enterprise-grade AI, making model testing and experimentation user-friendly and efficient.
  • Users find IBM watsonx.ai impressive for its enterprise-grade AI capabilities that simplify building and managing AI models.
Cons
  • Users find the difficult learning curve of IBM watsonx.ai intimidating, especially for those new to the platform.
  • Users often experience a steep learning curve and complexity with IBM watsonx.ai, making it daunting for newcomers.
  • Users frequently face a steep learning curve with IBM watsonx.ai, finding initial setup and navigation overwhelming.
  • Users find the cost to be quite high, especially for small teams that may struggle with complexity.
  • Users note the need for improved onboarding and transparency in IBM watsonx.ai for a smoother experience.

What Are Recent G2 Reviews of IBM watsonx.ai?

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: 256

How Do G2 Users Rate Dataiku?

  • Has the product been a good partner in doing business?: 8.6/10 (Category avg: 8.7/10)
  • Ease of Use: 8.6/10 (Category avg: 8.5/10)
  • Quality of Support: 8.5/10 (Category avg: 8.4/10)
  • Ease of Admin: 7.9/10 (Category avg: 8.5/10)

Who Is the Company Behind Dataiku?

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

Who Uses This Product?

  • Who Uses This: Data Scientist, Data Analyst
  • Top Industries: Financial Services, Pharmaceuticals
  • Company Size: 58% Large, 22% Medium

What Do G2 Reviewers Say About Dataiku?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use in Dataiku, facilitating intuitive workflows for both coders and non-coders alike.
  • Users value the intuitive AI features of Dataiku, enhancing collaboration and streamlining data workflows effectively.
  • Users appreciate the intuitive usability of Dataiku, enhancing collaboration and speeding up AI project delivery.
  • Users value the easy integrations of Dataiku, enhancing collaboration and streamlining workflows effectively.
  • Users value the productivity improvement in Dataiku, enjoying streamlined AI project workflows and enhanced collaboration.
Cons
  • Users find the steep learning curve of Dataiku daunting, especially for first-time and non-technical users.
  • Users find the steep learning curve of Dataiku challenging, especially for smaller teams or simpler projects.
  • Users experience slow performance when managing large datasets, which impacts efficiency and overall user satisfaction.
  • Users find the difficult learning experience due to Dataiku's overwhelming features and steep learning curve for newcomers.
  • Users find Dataiku expensive, with high costs deterring small companies and limiting accessibility for individual users.

What Are Recent G2 Reviews of Dataiku?

What Are G2 Users Discussing About Dataiku?

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Gemini platform

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

Average Rating: 4.3/5.0

Total Reviews: 870

How Do G2 Users Rate Gemini platform?

  • Has the product been a good partner in doing business?: 8.4/10 (Category avg: 8.7/10)
  • Ease of Use: 8.4/10 (Category avg: 8.5/10)
  • Quality of Support: 8.3/10 (Category avg: 8.4/10)
  • Ease of Admin: 8.1/10 (Category avg: 8.5/10)

Who Is the Company Behind Gemini platform?

  • Seller: Google
  • Year Founded: 1998
  • HQ Location: Mountain View, CA
  • LinkedIn® Page: www.linkedin.com
    301,144 employees on LinkedIn®
  • Ownership: NASDAQ:GOOG
  • Phone: +1 (650) 253-0000

Who Uses This Product?

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

What Do G2 Reviewers Say About Gemini platform?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of the Gemini platform, enhancing productivity and streamlining workflows significantly.
  • Users praise the model variety of Gemini, finding it essential for seamless integration and productivity in projects.
  • Users value the multimodal capabilities of Gemini, seamlessly integrating text, images, code, and documents for enhanced productivity.
  • Users appreciate the multimodal capabilities of Gemini, enhancing productivity in software development and automation tasks.
  • Users value the easy integrations of Gemini, enhancing workflow efficiency through seamless connectivity with various platforms.
Cons
  • Users find the Gemini platform to be expensive due to unclear cost tracking and potential for overspending.
  • Users find the learning curve steep with Gemini, as navigating its complexities can be overwhelming for new users.
  • Users find the complexity of the Gemini platform challenging, especially with IAM roles and numerous configuration options.
  • Users find the complexity issues of Vertex AI daunting, particularly during project setup and resource management.
  • Users find the difficult learning curve of Gemini platform overwhelming, especially with configuration and cost management challenges.

What Are Recent G2 Reviews of Gemini platform?

What Are G2 Users Discussing About Gemini platform?

Azure OpenAI Service

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

Average Rating: 4.6/5.0

Total Reviews: 57

How Do G2 Users Rate Azure OpenAI Service?

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

Who Is the Company Behind Azure OpenAI Service?

  • Seller: Microsoft
  • Year Founded: 1975
  • HQ Location: Redmond, Washington
  • LinkedIn® Page: www.linkedin.com
    232,750 employees on LinkedIn®
  • Ownership: MSFT
  • Phone: +1 (877) 276-2464

Who Uses This Product?

  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 34% Large, 33% Small

What Do G2 Reviewers Say About Azure OpenAI Service?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the intuitive ease of use of Azure OpenAI Service, simplifying tasks with seamless Azure integration.
  • Users appreciate the seamless integrations of Azure OpenAI Service with other Azure services, enhancing usability and efficiency.
  • Users value the scalability of Azure OpenAI Service, enabling effective management of enterprise-wide data infrastructure securely.
  • Users value the reliability of Azure OpenAI Service, praising its seamless integration and strong security features.
  • Users appreciate the seamless integration and strong security of Azure OpenAI Service for enterprise AI deployment.
Cons
  • Users find the pricing confusing and feel that it complicates their ability to experiment effectively.
  • Users find the setup process overly complex, requiring advanced knowledge of Azure networking and security protocols.
  • Users feel the limited features of Azure OpenAI Service restrict their experience and access to newer models.
  • Users find the complexity of Azure OpenAI Service poses significant challenges in usage and management, causing frustration.
  • Users face time consumption issues due to slow quota approvals and regional feature rollouts impacting experimentation.

What Are Recent G2 Reviews of Azure OpenAI Service?

Alteryx

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

Average Rating: 4.6/5.0

Total Reviews: 932

How Do G2 Users Rate Alteryx?

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

Who Is the Company Behind Alteryx?

  • Seller: Alteryx
  • Company Website:
  • Year Founded: 1997
  • HQ Location: Irvine, CA
  • LinkedIn® Page: www.linkedin.com
    2,312 employees on LinkedIn®
  • Ownership: Private

Who Uses This Product?

  • Who Uses This: Data Analyst, Analyst
  • Top Industries: Financial Services, Accounting
  • Company Size: 61% Large, 22% Medium

What Do G2 Reviewers Say About Alteryx?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of Alteryx, enabling them to work efficiently without coding expertise.
  • Users appreciate the automation capabilities of Alteryx, enabling efficient workflows and streamlined data processing.
  • Users find Alteryx to be super-intuitive, making complex data analysis and migration tasks significantly easier.
  • Users find Alteryx to be super-intuitive and easy to learn, greatly simplifying their data analysis processes.
  • Users commend Alteryx for its efficiency, with quick workflows and time savings in data preparation and automation.
Cons
  • Users find the expensive licensing costs of Alteryx a barrier for wider adoption and utilization.
  • Users find the learning curve steep, requiring time to grasp all the tools effectively.
  • Users are frustrated with missing features like improved email notifications and bugs in tools during transitions.
  • Users find that mastering advanced tools in Alteryx requires time, affecting overall ease of use.
  • Users experience slow performance with large workflows on Alteryx, impacting efficiency and usability significantly.

What Are Recent G2 Reviews of Alteryx?

machine-learning in Python

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

Average Rating: 4.6/5.0

Total Reviews: 48

How Do G2 Users Rate machine-learning in Python?

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

Who Is the Company Behind machine-learning in Python?

Who Uses This Product?

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

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

AI-generated summary from verified user reviews

Pros
  • Users appreciate the efficiency and support of machine learning in Python, benefiting from its extensive libraries for model building.
  • Users appreciate the ease of use in machine learning with Python, enjoying seamless integration with various libraries.
  • Users value the model variety offered by machine learning in Python, appreciating the rich ecosystem of libraries.
  • Users appreciate the intuitive nature of Python, which simplifies the learning and implementation of machine learning projects.
  • Users appreciate the high-quality libraries in Python for machine learning, which enhance model building and data handling.
Cons
  • Users find the difficult learning curve challenging, requiring time and effort to master the essentials of machine learning.
  • Users struggle with dependency issues that complicate coordination and performance in machine learning with Python.
  • Users experience slow performance with Python's machine learning, particularly when handling big data and dependencies.
  • Users often find slow performance in machine learning with Python, impacting the efficiency of their projects.
  • Users note that performance limitations of Python can hinder large-scale machine learning tasks compared to lower-level languages.

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

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

Amazon Forecast

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

Average Rating: 4.3/5.0

Total Reviews: 102

How Do G2 Users Rate Amazon Forecast?

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

Who Is the Company Behind Amazon Forecast?

Who Uses This Product?

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

What Do G2 Reviewers Say About Amazon Forecast?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of Amazon Forecast, enabling accurate predictions without needing deep machine learning knowledge.
  • Users value the high accuracy of Amazon Forecast, leveraging advanced ML for reliable time-series predictions and insightful planning.
  • Users appreciate the high accuracy of Amazon Forecast, enabling reliable and efficient time-series predictions without ML expertise.
  • Users appreciate the high accuracy powered by machine learning in Amazon Forecast, enabling reliable and insightful predictions.
  • Users appreciate the high accuracy of Amazon Forecast, enabling reliable forecasts without deep ML expertise.
Cons
  • Users find Amazon Forecast expensive for large datasets or frequent predictions, particularly challenging for smaller businesses to manage.
  • Users find the complexity of Amazon Forecast daunting, particularly during setup and configuration for new users.
  • Users struggle with the steep learning curve of Amazon Forecast, making it challenging for non-AWS users to adapt.
  • Users warn about the high costs associated with scaling Amazon Forecast, especially with large datasets and frequent retraining.
  • Users find that handling large datasets can lead to high costs, requiring careful management to avoid budget issues.

What Are Recent G2 Reviews of Amazon Forecast?

Automation Anywhere Agentic Process Automation

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

Average Rating: 4.5/5.0

Total Reviews: 4,181

How Do G2 Users Rate Automation Anywhere Agentic Process Automation?

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

Who Is the Company Behind Automation Anywhere Agentic Process Automation?

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

Who Uses This Product?

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

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

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use in Automation Anywhere, highlighting its intuitive interface and helpful features for automation.
  • Users appreciate the ease of use of Automation Anywhere, highlighting its intuitive interface and reliable automation capabilities.
  • Users value the efficiency of Automation Anywhere, noting significant reductions in manual work and boosted productivity.
  • Users value the automation ease of Automation Anywhere, noting its user-friendly features that simplify bot creation and management.
  • Users highly value the intuitive interface of Automation Anywhere, which simplifies bot creation and enhances productivity.
Cons
  • Users feel that the pricing of Automation Anywhere can be expensive, limiting accessibility for smaller teams and startups.
  • Users find a steep learning curve in Automation Anywhere, complicating onboarding and impacting initial setup and debugging.
  • Users note a lack of information in solutions, which can hinder the overall effectiveness of Automation Anywhere.
  • Users often face software bugs that hinder smooth operation and complicate bot deployment and debugging processes.
  • Users experience challenges with bot issues, including complex UI and slow performance during automation processes.

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

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

Weka

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

Average Rating: 4.3/5.0

Total Reviews: 13

How Do G2 Users Rate Weka?

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

Who Is the Company Behind Weka?

  • Seller: Weka
  • Year Founded: 1964
  • HQ Location: Hamilton, NZ
  • LinkedIn® Page: www.linkedin.com
    3,719 employees on LinkedIn®

Who Uses This Product?

  • Company Size: 77% Large, 23% Medium

What Are Recent G2 Reviews of Weka?

BMC AMI DevX

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

Average Rating: 4.3/5.0

Total Reviews: 95

How Do G2 Users Rate BMC AMI DevX?

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

Who Is the Company Behind BMC AMI DevX?

  • Seller: BMC Software
  • Company Website:
  • Year Founded: 1980
  • HQ Location: Houston, TX
  • LinkedIn® Page: www.linkedin.com
    8,646 employees on LinkedIn®
  • Phone: 713 918 8800

Who Uses This Product?

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

What Do G2 Reviewers Say About BMC AMI DevX?

AI-generated summary from verified user reviews

Pros
  • Users find BMC AMI DevX to be easy to use, facilitating seamless implementation and efficient performance monitoring.
  • Users value the industry benchmarking feature of BMC AMI DevX, enhancing performance comparisons and executive reporting.
  • Users value the effective bug detection capabilities of BMC AMI DevX, enhancing modernization and operational performance insights.
  • Users value the excellent customer support provided by BMC AMI DevX, enhancing their overall experience.
  • Users praise the smooth integration of Machine Learning in BMC AMI DevX, enhancing DevOps KPIs effectively.
Cons
  • Users face complexity and limitations in customization that hinder their ability to tailor the BMC AMI DevX to their needs.
  • Users find limited customization challenging, making it difficult to tailor dashboards to their specific organizational needs.
  • Users experience compatibility issues with BMC AMI DevX when integrating non-BMC tools, hindering effective activity monitoring.
  • Users struggle with the complex setup of BMC AMI DevX due to limited customization and a steep learning curve.
  • Users face configuration issues due to limited customization and a steep learning curve for tailored setups.

What Are Recent G2 Reviews of BMC AMI DevX?

What Are G2 Users Discussing About BMC AMI DevX?

scikit-learn

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

Average Rating: 4.8/5.0

Total Reviews: 60

How Do G2 Users Rate scikit-learn?

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

Who Is the Company Behind scikit-learn?

Who Uses This Product?

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

What Do G2 Reviewers Say About scikit-learn?

AI-generated summary from verified user reviews

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

What Are Recent G2 Reviews of scikit-learn?

What Are G2 Users Discussing About scikit-learn?

Wolfram Mathematica

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

Average Rating: 4.1/5.0

Total Reviews: 86

How Do G2 Users Rate Wolfram Mathematica?

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

Who Is the Company Behind Wolfram Mathematica?

Who Uses This Product?

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

What Are Recent G2 Reviews of Wolfram Mathematica?

What Are G2 Users Discussing About Wolfram Mathematica?

SAS Model Manager

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

Average Rating: 4.6/5.0

Total Reviews: 56

How Do G2 Users Rate SAS Model Manager?

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

Who Is the Company Behind SAS Model Manager?

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

Who Uses This Product?

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

What Do G2 Reviewers Say About SAS Model Manager?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the simplicity and automation of SAS Model Manager, enhancing collaboration and efficiency in model management.
  • Users appreciate the variety of models available in SAS Model Manager, making collaboration and efficiency seamless.
  • Users appreciate the simplicity and efficiency of SAS Model Manager for managing classical ML models effectively.
  • Users value the automation capabilities of SAS Model Manager, significantly reducing time and effort in model management.
  • Users value the collaboration capabilities of SAS Model Manager, enhancing teamwork and model sharing efficiency.
Cons
  • Users experience a steep learning curve with SAS Model Manager due to the difficulty in navigating documentation effectively.
  • Users find the complexity of SAS Model Manager challenging, often hindering their ability to effectively utilize the tool.
  • Users often struggle with complexity issues in SAS Model Manager, making the software challenging to navigate effectively.
  • Users find the difficult learning curve frustrating, especially with parameter tuning options and searching for specific adjustments.
  • Users find the difficult navigation of SAS Model Manager frustrating, hindering access to essential documentation and details.

What Are Recent G2 Reviews of SAS Model Manager?

Shalaka Joshi
SJ
Researched and written by Shalaka Joshi
Updated