Best Machine Learning Software - Page 5

How Many Machine Learning Software Products Does G2 Track?

Total Products under this Category: 1,043

Category Stats (Oct 2026)

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

Last updated: October 13, 2026

How Does G2 Rank Machine Learning Software Products?

Why You Can Trust G2's Software Rankings:

  • 30 Analysts and Data Experts
  • 14,300+ Authentic Reviews
  • 1,043+ 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: Gemini Enterprise Agent Platform, SAS Viya, Azure OpenAI Service, IBM watsonx.ai, Google Cloud Recommendations AI, Alteryx, Amazon Personalize, and Dataiku.

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

Spotfire Analytics

Spotfire® is a visual data science platform designed to help organizations address complex, industry-specific challenges by effectively utilizing data. This solution offers a range of flexible packaging options tailored to meet the diverse needs of teams at various stages of their visual data science journey. Turn raw data into real-time decisions with powerful, interactive visual analytics with Spotfire® Analytics. Spotfire Analytics is designed for business agility, enabling every user to explore data visually, uncover patterns quickly, and make confident, data-driven decisions without writing a single line of code. As a self-service visual data science solution, it empowers teams across roles and departments to gain fast, actionable insights that drive impact. With its no-code interactive dashboards and rich visual exploration capabilities, Spotfire Analytics connects natively to hundreds of cloud, on-premises, and real-time data sources. Built-in geoanalytics extend the power of analysis with multi-layer mapping and seamless integration of spatial data, while data wrangling and transformation can be performed directly within the visual interface, making it easy to clean, shape, and blend data as you analyze. AI-assisted recommendations and anomaly detection help uncover hidden patterns, suggest the most meaningful visualizations, and accelerate the path to discovery. Customizable visualizations, workflows, and an intuitive interface ensure that insights are not only easier to create but also easier to share. With seamless collaboration features, Spotfire Analytics enables teams to work together, align on insights, and act decisively. Whether the goal is to analyze trends, detect anomalies, or unlock location-based intelligence, Spotfire Analytics delivers the speed, flexibility, and depth needed to make smarter decisions with confidence. Explore and understand your data visually, uncover hidden insights, and build powerful analytics applications - all without writing a single line of code. Spotfire Analytics combines advanced interactive visualizations and intuitive data wrangling in one environment. Connect to hundreds of data sources, from files to real-time streaming data, and transform messy data directly within your visuals. Built-in AI recommendations help you find patterns, anomalies, and trends faster. With flexible visualizations, spatial analytics, and custom applications, anyone can turn raw data into actionable insights in minutes. Designed for business agility, Spotfire Analytics empowers every user to explore, analyze, and share results confidently - turning questions into decisions. Best for: Analysts, data-savvy professionals, and teams looking to explore and share data visually with maximum flexibility.

Average Rating: 4.2/5.0

Total Reviews: 328

How Do G2 Users Rate Spotfire Analytics?

  • Has the product been a good partner in doing business?: 8.4/10 (Category avg: 8.7/10)
  • Ease of Use: 8.1/10 (Category avg: 8.5/10)
  • Quality of Support: 7.8/10 (Category avg: 8.4/10)
  • Ease of Admin: 7.8/10 (Category avg: 8.5/10)

Who Is the Company Behind Spotfire Analytics?

Who Uses This Product?

  • Who Uses This: Student, Manager
  • Top Industries: Oil & Energy, Information Technology and Services
  • Company Size: 52% Large, 26% Medium

What Do G2 Reviewers Say About Spotfire Analytics?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the powerful and flexible data visualization capabilities of Spotfire Analytics, enhancing their data exploration experience.
  • Users appreciate the ease of use of Spotfire Analytics, enabling quick insights and effective decision-making with complex data.
  • Users appreciate the easy integrations of Spotfire Analytics, enhancing accuracy and enabling robust AI-powered analytics seamlessly.
  • Users rave about Spotfire's powerful analytics capabilities, enabling advanced data handling and insightful visualizations seamlessly.
  • Users love the transformative interactive visualizations of Spotfire, simplifying complex data for clear understanding across teams.
Cons
  • Users find Spotfire's steep learning curve challenging, particularly for those unfamiliar with data modeling and scripting.
  • Users find the learning difficulty significant, especially for beginners navigating advanced features and options in Spotfire.
  • Users find the licensing costs high, making Spotfire Analytics less accessible for smaller organizations.
  • Users often face a steep learning curve with Spotfire Analytics, making initial use challenging for newcomers.
  • Users note that there are limitations in data comparison and features, affecting usability and clarity of Spotfire Analytics.

What Are Recent G2 Reviews of Spotfire Analytics?

What Are G2 Users Discussing About Spotfire Analytics?

Mathematica

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

Average Rating: 4.1/5.0

Total Reviews: 86

How Do G2 Users Rate Mathematica?

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

Who Is the Company Behind Mathematica?

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

Who Uses This Product?

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

What Are Recent G2 Reviews of Mathematica?

What Are G2 Users Discussing About Mathematica?

DecisionTree.jl

DecisionTree.jl is a Julia classifier with the implimentation of the ID3 algorithm with post pruning (pessimistic pruning), parallelized bagging (random forests), adaptive boosting (decision stumps), cross validation (n-fold) and support for mixed nominal and numerical data.

Average Rating: 4.0/5.0

Total Reviews: 11

How Do G2 Users Rate DecisionTree.jl?

  • Has the product been a good partner in doing business?: 8.3/10 (Category avg: 8.7/10)
  • Ease of Use: 7.4/10 (Category avg: 8.5/10)
  • Quality of Support: 6.9/10 (Category avg: 8.4/10)
  • Ease of Admin: 6.7/10 (Category avg: 8.5/10)

Who Is the Company Behind DecisionTree.jl?

Who Uses This Product?

  • Company Size: 36% Medium, 36% Small

What Are Recent G2 Reviews of DecisionTree.jl?

What Are G2 Users Discussing About DecisionTree.jl?

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Mahout

Apache Mahout is a software that build an environment for quickly creating scalable performant machine learning applications, it provides three major features: A simple and extensible programming environment and framework for building scalable algorithms, A wide variety of premade algorithms for Scala + Apache Spark, H2O, Apache Flink and Samsara, a vector math experimentation environment with R-like syntax which works at scale

Average Rating: 4.2/5.0

Total Reviews: 13

How Do G2 Users Rate Mahout?

  • Has the product been a good partner in doing business?: 8.6/10 (Category avg: 8.7/10)
  • Ease of Use: 7.1/10 (Category avg: 8.5/10)
  • Quality of Support: 8.8/10 (Category avg: 8.4/10)
  • Ease of Admin: 7.6/10 (Category avg: 8.5/10)

Who Is the Company Behind Mahout?

Who Uses This Product?

  • Company Size: 46% Medium, 31% Large

What Are Recent G2 Reviews of Mahout?

What Are G2 Users Discussing About Mahout?

PyTorch

PyTorch is an open-source machine learning framework that accelerates the transition from research prototyping to production deployment. Developed by Meta AI and now governed by the PyTorch Foundation under the Linux Foundation, PyTorch is widely used for applications in computer vision, natural language processing, and more. Its dynamic computation graph and intuitive Python interface make it a preferred choice for researchers and developers aiming to build and deploy deep learning models efficiently. Key Features and Functionality: - Dynamic Computation Graph: Allows for flexible and efficient model building, enabling changes to the network architecture during runtime. - Tensors and Autograd: Utilizes tensors as fundamental data structures, similar to NumPy arrays, with support for automatic differentiation to streamline the computation of gradients. - Neural Network API: Provides a modular framework for constructing neural networks with pre-defined layers, activation functions, and loss functions, facilitating the creation of complex models. - Distributed Training: Offers native support for distributed training, optimizing performance across multiple GPUs and nodes, which is essential for scaling large models. - TorchScript: Enables the transition from eager execution to graph execution, allowing models to be serialized and optimized for deployment in production environments. - TorchServe: A tool for deploying PyTorch models at scale, supporting features like multi-model serving, logging, metrics, and RESTful endpoints for application integration. - Mobile Support (Experimental): Extends PyTorch capabilities to mobile platforms, allowing models to be deployed on iOS and Android devices. - Robust Ecosystem: Supported by an active community, PyTorch offers a rich ecosystem of tools and libraries for various domains, including computer vision and reinforcement learning. - ONNX Support: Facilitates exporting models in the Open Neural Network Exchange (ONNX) format for compatibility with other platforms and runtimes. Primary Value and User Solutions: PyTorch's primary value lies in its ability to provide a seamless path from research to production. Its dynamic computation graph and user-friendly interface allow for rapid prototyping and experimentation, enabling researchers to iterate quickly on model designs. For developers, PyTorch's support for distributed training and tools like TorchServe simplify the deployment of models at scale, reducing the time and complexity associated with bringing machine learning models into production. Additionally, the extensive ecosystem and community support ensure that users have access to a wide range of resources and tools to address various machine learning challenges.

Average Rating: 4.6/5.0

Total Reviews: 22

How Do G2 Users Rate PyTorch?

  • Has the product been a good partner in doing business?: 9.2/10 (Category avg: 8.7/10)
  • Ease of Use: 8.4/10 (Category avg: 8.5/10)
  • Quality of Support: 8.1/10 (Category avg: 8.4/10)
  • Ease of Admin: 9.2/10 (Category avg: 8.5/10)

Who Is the Company Behind PyTorch?

  • Seller: Jetware
  • Year Founded: 2017
  • HQ Location: Roma, IT
  • Twitter: @jetware_io
    25 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    2 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Computer Software
  • Company Size: 43% Medium, 43% Small

What Do G2 Reviewers Say About PyTorch?

AI-generated summary from verified user reviews

Pros
  • Users value the intuitive nature of PyTorch, enhancing their development experience with easy experimentation and debugging.
  • Users appreciate the extensive documentation of PyTorch, facilitating easy experimentation and debugging for developers.
  • Users find PyTorch's intuitive interface excellent for experimentation, bolstered by a supportive community and great documentation.
  • Users find PyTorch highly intuitive, benefiting from its dynamic graph that simplifies experimentation and debugging.
  • Users value the intuitive problem-solving capabilities of PyTorch, enabling easier experimentation and debugging for developers.
Cons
  • Users find the complexity in deploying models with PyTorch can hinder scaling and require extra tools and setup.
  • Users find the difficult learning curve for PyTorch's advanced features a barrier, especially for production deployments.
  • Users find difficult navigation in PyTorch, often needing extra tools and setups for effective deployment and scaling.

What Are Recent G2 Reviews of PyTorch?

What Are G2 Users Discussing About PyTorch?

Patern Recognition and Machine Learning Toolbox

Pattern Recognition and Machine Learning is a Matlab implementation of the algorithms.

Average Rating: 4.0/5.0

Total Reviews: 11

How Do G2 Users Rate Patern Recognition and Machine Learning Toolbox?

  • Has the product been a good partner in doing business?: 8.3/10 (Category avg: 8.7/10)
  • Ease of Use: 7.6/10 (Category avg: 8.5/10)
  • Quality of Support: 7.6/10 (Category avg: 8.4/10)
  • Ease of Admin: 8.9/10 (Category avg: 8.5/10)

Who Is the Company Behind Patern Recognition and Machine Learning Toolbox?

Who Uses This Product?

  • Company Size: 45% Small, 27% Medium

What Are Recent G2 Reviews of Patern Recognition and Machine Learning Toolbox?

Vowpal Wabbit

Vowpal Wabbit is a machine learning system that pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.

Average Rating: 4.3/5.0

Total Reviews: 13

How Do G2 Users Rate Vowpal Wabbit?

  • Ease of Use: 8.8/10 (Category avg: 8.5/10)
  • Quality of Support: 8.0/10 (Category avg: 8.4/10)
  • Ease of Admin: 6.7/10 (Category avg: 8.5/10)

Who Is the Company Behind Vowpal Wabbit?

Who Uses This Product?

  • Company Size: 46% Medium, 31% Large

What Are Recent G2 Reviews of Vowpal Wabbit?

What Are G2 Users Discussing About Vowpal Wabbit?

Ganitha

Ganitha is an open-source library (derived from the Sanskrit word for mathematics, or science of computation) is a Scalding library with a focus on machine-learning and statistical analysis.

Average Rating: 4.3/5.0

Total Reviews: 11

How Do G2 Users Rate Ganitha?

  • Has the product been a good partner in doing business?: 8.3/10 (Category avg: 8.7/10)
  • Ease of Use: 6.8/10 (Category avg: 8.5/10)
  • Quality of Support: 6.5/10 (Category avg: 8.4/10)
  • Ease of Admin: 8.3/10 (Category avg: 8.5/10)

Who Is the Company Behind Ganitha?

  • Seller: Tresata
  • Year Founded: 2011
  • HQ Location: Charlotte, NC
  • LinkedIn® Page: www.linkedin.com
    29 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Marketing and Advertising
  • Company Size: 75% Medium, 25% Small

What Do G2 Reviewers Say About Ganitha?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the efficiency of handling large data volumes with Ganitha, simplifying complex workflows significantly.
  • Users appreciate the ease of use of Ganitha, enjoying an intuitive interface that simplifies complex data handling.
  • Users value the model variety in Ganitha, benefiting from diverse machine learning algorithms for complex data tasks.
  • Users value Ganitha's seamless integrations with other tools, enhancing efficiency in complex data workflows and analysis.
  • Users value the flexibility of Ganitha, enabling efficient handling of large data volumes and complex analyses.
Cons
  • Users find the poor documentation of Ganitha frustrating, lacking practical examples and detailed tutorials for better understanding.
  • Users face difficult learning curves with Ganitha, needing more practical examples and tutorials to ease the process.
  • Users find the steep learning curve of Ganitha challenging, especially those new to Scalding.
  • Users find Ganitha has limited customization options, which may hinder advanced analysis and integration for experienced users.
  • Users find Ganitha's features limited for advanced analysis and feel the documentation is insufficient for deeper customization.

What Are Recent G2 Reviews of Ganitha?

What Are G2 Users Discussing About Ganitha?

Beeze

Breeze is a numerical processing library for Scala.

Average Rating: 4.4/5.0

Total Reviews: 12

How Do G2 Users Rate Beeze?

  • Has the product been a good partner in doing business?: 6.7/10 (Category avg: 8.7/10)
  • Ease of Use: 7.3/10 (Category avg: 8.5/10)
  • Quality of Support: 7.1/10 (Category avg: 8.4/10)
  • Ease of Admin: 7.9/10 (Category avg: 8.5/10)

Who Is the Company Behind Beeze?

  • Seller: ScalaNLP
  • HQ Location: N/A
  • Twitter: @ScalaNLP
    191 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    1 employees on LinkedIn®

Who Uses This Product?

  • Company Size: 67% Medium, 33% Small

What Are Recent G2 Reviews of Beeze?

What Are G2 Users Discussing About Beeze?

Vivas.AI

Vivas.AI is a one-stop marketplace to access a wide range of AI models for various use cases across industries. Vivas.AI shifts the balance of power from ML engineers toward application engineers. Application developers are no longer burdened to develop models in-house but simply use them to build their favorite app by simply dragging and dropping them in their low code platform of choice. Users can validate the models with sample data and access the model cards, best practices, and limitations to ensure the customers have complete transparency and trust in the models they choose. Vivas.AI's business model is inclusive and strives to provide a marketplace where multiple vendors can offer their models. This makes the Vivas.AI marketplace much more inclusive and broad. In short, Vivas.AI aspires to be the ‘Uber’ of the AI/ML marketplace.

Average Rating: 4.2/5.0

Total Reviews: 12

How Do G2 Users Rate Vivas.AI?

  • Has the product been a good partner in doing business?: 8.3/10 (Category avg: 8.7/10)
  • Ease of Use: 8.8/10 (Category avg: 8.5/10)
  • Quality of Support: 8.3/10 (Category avg: 8.4/10)
  • Ease of Admin: 9.2/10 (Category avg: 8.5/10)

Who Is the Company Behind Vivas.AI?

  • Seller: Vivas.AI
  • Year Founded: 2022
  • HQ Location: Chennai, IN
  • Twitter: @vivas_ai
    5 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    2 employees on LinkedIn®

Who Uses This Product?

  • Company Size: 50% Medium, 50% Small

What Are Recent G2 Reviews of Vivas.AI?

DagsHub

DagsHub is a platform that allows you to easily create high-quality datasets for better model performance A single AI platform to curate vision, audio, and document data - automate labeling workflows, and evaluate models. Enterprises with sensitive data, can run on their own infrastructure on-prem and get a full AI platform. Data curation - create the very best datasets. Data annotation - annotate your vision, audio, and document data. Auto labeling - automate your annotation flow with pre-built templates and active learning. Data versioning - version your datasets for reproducibility. Experiment tracking - track your experiment progress, understand trends, and compare results. Model registry - manage your models and deployments in one place. The top data scientists build AI with DagsHub including teams at: Google, Harvard Medicine, Beewise, Macso, and Mana.bio

Average Rating: 4.8/5.0

Total Reviews: 14

How Do G2 Users Rate DagsHub?

  • Has the product been a good partner in doing business?: 9.4/10 (Category avg: 8.7/10)
  • Ease of Use: 9.2/10 (Category avg: 8.5/10)
  • Quality of Support: 9.3/10 (Category avg: 8.4/10)
  • Ease of Admin: 9.2/10 (Category avg: 8.5/10)

Who Is the Company Behind DagsHub?

Who Uses This Product?

  • Top Industries: Computer Software
  • Company Size: 50% Small, 43% Medium

What Do G2 Reviewers Say About DagsHub?

AI-generated summary from verified user reviews

Pros
  • Users value the effective data management of DagsHub, enhancing reproducibility and collaboration in ML projects.
  • Users appreciate the seamless integration of data, code, and experiments in DagsHub, boosting their productivity and collaboration.
  • Users value the seamless collaboration DagsHub facilitates, enhancing team efficiency in managing data and experiments.
  • Users value the seamless data and experiment integration of DagsHub, enhancing reproducibility and collaboration in ML projects.
  • Users value the integrated platform of DagsHub for streamlining data management, experimentation, and model tracking efficiently.
Cons
  • Users find limited functionality in DagsHub, particularly in team capacity and model extension options.
  • Users often experience error handling issues on DagsHub, particularly when pushing files or loading projects.
  • Users find DagsHub to be expensive due to strict limitations on the free plan and inaccessible academic options.
  • Users find the limited customization in DagsHub restrictive, particularly with the constraints of the free plan.
  • Users find the strict limitations of the free plan restrictive, impacting team collaboration and accessibility.

What Are Recent G2 Reviews of DagsHub?

Genpact Orchestration AI Suite

Genpact Cora: Artificial intelligence for the real world

Average Rating: 4.2/5.0

Total Reviews: 9

How Do G2 Users Rate Genpact Orchestration AI Suite?

  • Has the product been a good partner in doing business?: 9.2/10 (Category avg: 8.7/10)
  • Ease of Use: 8.1/10 (Category avg: 8.5/10)
  • Quality of Support: 8.1/10 (Category avg: 8.4/10)
  • Ease of Admin: 8.3/10 (Category avg: 8.5/10)

Who Is the Company Behind Genpact Orchestration AI Suite?

  • Seller: Genpact
  • Year Founded: 1997
  • HQ Location: New York, NY
  • Twitter: @Genpact
    23,941 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    154,961 employees on LinkedIn®
  • Ownership: NYSE:G

Who Uses This Product?

  • Company Size: 50% Small, 40% Medium

What Do G2 Reviewers Say About Genpact Orchestration AI Suite?

AI-generated summary from verified user reviews

Pros
  • Users value the integrated analytics in Genpact Orchestration AI Suite, enhancing decision-making and operational efficiency.
  • Users value the integration of AI, automation, and analytics in a single, customizable, and user-friendly platform.
  • Users value the business growth benefits of Genpact Orchestration AI Suite, enhancing decision-making and streamlining operations.
  • Users value the customization options of Genpact Orchestration AI Suite, tailoring it to specific business needs.
  • Users value the intuitive interface of Genpact Cora, making it easy to navigate and customize for their needs.
Cons
  • Users criticize the high implementation cost of Genpact Orchestration AI Suite, making it less accessible for some businesses.

What Are Recent G2 Reviews of Genpact Orchestration AI Suite?

MLKit

MLKit is a machine learning framework written in Swift that features machine learning algorithms that deal with the topic of regression to provide developers with a toolkit to create products that can learn from data.

Average Rating: 4.4/5.0

Total Reviews: 12

How Do G2 Users Rate MLKit?

  • Ease of Use: 9.3/10 (Category avg: 8.5/10)
  • Quality of Support: 9.2/10 (Category avg: 8.4/10)

Who Is the Company Behind MLKit?

Who Uses This Product?

  • Company Size: 46% Small, 31% Medium

What Are Recent G2 Reviews of MLKit?

Encord

Encord is the universal data layer for AI. The platform helps AI teams train and run their models with the right data - managing, curating, annotating, and aligning data across the full AI lifecycle. Encord works with over 300 leading AI teams, including Woven by Toyota, Zipline, AXA, and Flock Safety. Confidentially build production AI with rich multimodal data. Encord is SOC 2, AICPA SOC, HIPAA, and GDPR compliant.

Average Rating: 4.8/5.0

Total Reviews: 65

How Do G2 Users Rate Encord?

  • Has the product been a good partner in doing business?: 9.5/10 (Category avg: 8.7/10)
  • Ease of Use: 9.5/10 (Category avg: 8.5/10)
  • Quality of Support: 9.9/10 (Category avg: 8.4/10)
  • Ease of Admin: 8.1/10 (Category avg: 8.5/10)

Who Is the Company Behind Encord?

  • Seller: Encord
  • Year Founded: 2020
  • HQ Location: San Francisco, US
  • Twitter: @encord_team
    1,014 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    220 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Computer Software, Hospital & Health Care
  • Company Size: 51% Small, 40% Medium

What Do G2 Reviewers Say About Encord?

AI-generated summary from verified user reviews

Pros
  • Users praise Encord for its responsive customer support, ensuring quick solutions and seamless collaboration during projects.
  • Users commend Encord for its annotation efficiency, appreciating the smooth workflow and intuitive interface that enhances productivity.
  • Users value the intuitive interface and powerful AI features of Encord, enhancing their data annotation efficiency significantly.
  • Users value the efficiency of Encord, experiencing smooth workflows and quick data integration that accelerates their processes.
  • Users value the intuitive interface and comprehensive features of Encord, enhancing efficiency in data curation and annotation.
Cons
  • Users find that custom workflows can be challenging, but support from the team helps mitigate the difficulties.
  • Users find it challenging to keep up with frequent updates from Encord, despite support from their customer success team.
  • Users find it challenging to keep up with best practices due to frequent feature updates from Encord.

What Are Recent G2 Reviews of Encord?

Keysight Eggplant

Keysight Eggplant is a leading intelligent test automation platform that uses ML/AI to test the entire user journey — identifying and predicting any potential defects along the way. Unlike other testing tools, Eggplant can test any technology, platform, or device, no matter the complexity. Because Eggplant is non-invasive, it does not require access to source code, making it the best solution for black box testing in secure environments. Eggplant delivers the coverage you need to optimize the user experience, speed up release cycles, and improve your quality assurance process. Discover a fast, secure, and easy-to-use solution that tests any software on any platform or device.

Average Rating: 4.2/5.0

Total Reviews: 87

How Do G2 Users Rate Keysight Eggplant?

  • Has the product been a good partner in doing business?: 8.8/10 (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: 7.7/10 (Category avg: 8.5/10)

Who Is the Company Behind Keysight Eggplant?

  • Seller: Keysight Technologies
  • Year Founded: 2014
  • HQ Location: Santa Rosa, California, United States
  • Twitter: @Keysight
    13,585 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    13,900 employees on LinkedIn®
  • Ownership: NYSE: KEYS

Who Uses This Product?

  • Who Uses This: Software Engineer, Test Automation Engineer
  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 44% Large, 35% Small

What Do G2 Reviewers Say About Keysight Eggplant?

AI-generated summary from verified user reviews

Pros
  • Users find Eggplant's ease of use remarkable, with a low learning curve and intuitive interface enhancing automation efforts.
  • Users value the ease of automation with Eggplant, appreciating its user-friendly interface and quick implementation.
  • Users value the ease of use in automation support of Keysight Eggplant, facilitating quick and effective test implementation.
  • Users find automation easy with Keysight Eggplant, appreciating its quick setup and low learning curve for scripting.
  • Users value the outstanding customer support from Keysight Eggplant, enhancing the overall user experience significantly.
Cons
  • Users face challenges with browser compatibility, which can hinder testing effectiveness across various platforms.
  • Users face compatibility challenges with various technologies and applications, impacting the effectiveness of Eggplant Functional.
  • Users face recurring OCR issues in Keysight Eggplant, leading to frequent test case failures during complex scenarios.
  • Users often face significant compatibility challenges with various technologies and specific applications when using Keysight Eggplant.
  • Users find the complexity of Keysight Eggplant challenging, particularly in managing logs and file conversions effectively.

What Are Recent G2 Reviews of Keysight Eggplant?

What Are G2 Users Discussing About Keysight Eggplant?

Shalaka Joshi
SJ
Researched and written by Shalaka Joshi
Updated April 9, 2026