Your comprehensive go-to hub for exploring, discovering, and comparing the best machine learning tools available in the industry
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curated list of top AI Tools.
| Tool Name | Website Link | Open Source/Cloud/Both | About |
| Tool Name | Website Link | Open Source / Cloud / Both | About |
|---|---|---|---|
| TensorFlow | 🔗 | Open Source | Tensorflow has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications. |
| MLFlow | 🔗 | Open Source | MLFlow is a platform to streamline machine learning development, including tracking experiments, packaging code into reproducible runs, and sharing and deploying models. |
| KubeFlow | 🔗 | Open Source | Kubeflow translates steps in your data science workflow into Kubernetes jobs, providing the cloud-native interface for your ML libraries, frameworks, pipelines and notebooks. |
| Seldon | 🔗 | Open Source | Seldon handles scaling to thousands of production machine learning models and provides advanced machine learning capabilities out of the box including Advanced Metrics, Request Logging, Explainers, Outlier Detectors, A/B Tests, Canaries and more. |
| BentoML | 🔗 | Open Source | BentoML provides a standardized structure for packaging and exporting trained models, along with all of the dependencies required to run them, making it easy to share and deploy these models in a reproducible way. |
| AWS Sagemaker | 🔗 | Open Source Cloud | Amazon SageMaker is a fully-managed service that enables data scientists and developers to quickly and easily build, train, and deploy machine learning models at any scale. |
| Torchserve | 🔗 | Open Source | PyTorch is a fully featured framework for building deep learning models, which is a type of machine learning that's commonly used in applications like image recognition and language processing. |
| Docker | 🔗 | Open Source | Docker is a software platform that allows you to build, test, and deploy applications quickly. Docker packages software into standardized units called containers that have everything the software needs to run including libraries, system tools, code, and runtime. |
| Gradio | 🔗 | Open Source | Gradio is a Python package that allows you to quickly create easy-to-use, customizable UI components for your ML model, any API, or even an arbitrary Python function using a few lines of code. |
| Kubernetes | 🔗 | Open Source | Kubernetes automates operational tasks of container management and includes built-in commands for deploying applications, rolling out changes to your applications, scaling your applications up and down to fit changing needs, monitoring your applications, and more—making it easier to manage applications. |
| OctoML | 🔗 | Both | It helps to optimize and package your trained model in minutes so you can deploy it to any hardware target for faster, more cost-efficient inference. |
| Clear ML | 🔗 | Open Source | ClearML gives data scientists tools to manage experiments, orchestrate workloads, and manage data, all in a simple open-source tool that integrates with whatever toolchain a team is using already. |
| NVIDIA Triton Inference Server | 🔗 | Open Source | Triton Inference Server, part of the NVIDIA AI platform, streamlines and standardizes AI inference by enabling teams to deploy, run, and scale trained AI models from any framework on any GPU- or CPU-based infrastructure. |
| Modzy | 🔗 | NA | Modzy is the MLOps platform for enterprise and edge, with unmatched features for explainability, enterprise security, infrastructure cost management, and powerful integrations. |
| Barbara IoT | 🔗 | Open Source | Barbara is empowering ML Teams with the compliance, security and low latency that cloud cannot provide by helping to deploy, monitor and maintain Edge AI at scale. |
| DataRobot | 🔗 | Open Source | DataRobot is a machine learning platform for automating, assuring, and empowering our predictive analytics consulting, helping data scientists and analysts build and deploy accurate predictive models in a fraction of the time required by other solutions. |
| UbiOps | 🔗 | NA | UbiOps is a powerful MLOps platform for deploying and managing machine learning models and data science workflows, with a focus on scalability, reliability, and security. UbiOps helps teams deploy their machine learning models and algorithms in a production environment, where they can be integrated with existing applications and processes. |
| Iguazio | 🔗 | Open Source | The Iguazio MLOps Platform transforms AI projects into real-world business outcomes. Accelerate and scale development, deployment and management of your AI applications with end-to-end automation of machine (and deep) learning pipelines. |
| Dask - ML | 🔗 | Open Source | Dask-ML provides scalable machine learning in Python using Dask alongside popular machine learning libraries like Scikit-Learn, XGBoost, and others. |
| Superwise | 🔗 | Open Source | Superwise.ai enables business and operational teams to take ownership of the health of their AI environments. Its AI Assurance platform includes AI performance management, bias detection, explainability and AI analytics capabilities |
| Domino Data Labs | 🔗 | Open Source | Domino Data Lab accelerates research, speeds model deployment, and increases collaboration for code-first data science teams at scale, all in one platform. |
| KFServing | 🔗 | Open source, Cloud native | KFServing provides a simple yet complete story for production ML inference serving. It is compatible with different ML frameworks-Tensorflow, XGBoost, ScikitLearn, and ONNX. |
| Multi Model Server | 🔗 | Open Source | Multi Model Server (MMS) is a flexible and easy to use tool for serving deep learning models trained using any ML/DL framework. |
| Seldon Core | 🔗 | Open Source | Seldon Core makes it easier and faster to deploy our machine learning models and experiments at scale on Kubernetes which serves models built in any open-source or commercial model building framework. |
| ForestFlow | 🔗 | NA | ForestFlow is an LF AI Foundation incubation project licensed under the Apache 2.0 license. It is a scalable policy-based cloud-native machine learning model server for easily deploying and managing ML models. |
| DeepSparse | 🔗 | Open Source | DeepSparse is an inference runtime offering GPU-class performance on CPUs and APIs to integrate ML into your application. |
| Deep Detect | 🔗 | Open Source | DeepDetect is a deep learning API and server written in C++11, along with a pure Web Platform for training and managing models. |
| ONNX | 🔗 | Open Source | The Open Neural Network Exchange is an open-source artificial intelligence ecosystem of technology companies and research organizations that establish open standards for representing machine learning algorithms and software tools to promote innovation and collaboration in the AI sector. |
| Tool Name | Website Link | Open Source / Cloud / Both | About |
|---|---|---|---|
| Arize | 🔗 | NA | Arize provides production ML analytics and workflows to quickly catch model and data issues, diagnose the root cause, and continuously improve performance for your products and business. |
| WhyLabs | 🔗 | Open Source | WhyLabs is an AI observability platform that prevents model performance degradation by allowing you to monitor your machine learning models in production. |
| Fiddler | 🔗 | Open Source | The Fiddler tool helps you debug web applications by capturing network traffic between the Internet and test computers. |
| New Relic | 🔗 | Open Source | New Relic is a Software as a Service offering that focuses on performance and availability monitoring. It uses a standardized Apdex (application performance index) score to set and rate application performance across the environment in a unified manner. |
| Qualdo | 🔗 | Open Source | Qualdo™ helps you to monitor mission-critical data errors, drifts and quality in your favorite modern databases & ML ecosystem. |
| Aporia | 🔗 | NA | Aporia is a full-stack ML observability platform that enables data science and ML teams to monitor, explain, and improve their ML models. |
| Arthur | 🔗 | NA | An AI Performance Company that works with enterprise teams to monitor, measure, and improve machine learning models for better results across accuracy, explainability, and fairness. |
| Evidently AI | 🔗 | Open Source | Evidently AI is a monitoring tool that offers open-source Python library for data scientists and ML engineers to evaluate, test, and monitor machine learning models. |
| Mona Labs | 🔗 | NA | Mona Lab's performance monitoring platform for production AI systems, enabling data and engineer teams to resolve model underperformance issues. |
| Censius | 🔗 | Open Source | Censius is an AI Observability Platform that assists enterprises in continuously monitoring, analyzing, and explaining their production models. |
| Prometheus | 🔗 | Open Source | Prometheus is an open-source systems monitoring and alerting toolkit originally built at SoundCloud. |
| Grafana Labs | 🔗 | Open Source | Grafana Labs is an open source software platform built to support monitoring, visualization, and metric analytics. |
| Accel Data | 🔗 | Open Source | Acceldata offers a comprehensive data observability platform which allows data-driven enterprises to streamline their operations. |
| Truera | 🔗 | Open Source | TruEra provides AI quality management solutions that test, optimize, and monitor machine learning models. |
| Zabbix | 🔗 | Open Source | Zabbix is an open source monitoring software tool for diverse IT components, including networks, servers, virtual machines (VMs) and cloud services. |
| Tool Name | Website Link | Open Source / Cloud / Both | About |
|---|---|---|---|
| DataBricks | 🔗 | Open Source Apache Spark framework | Databricks is used to process, store, clean, share, analyze, model, and monetize their datasets with solutions from BI to machine learning. |
| Pachyderm | 🔗 | NA | Pachyderm is data-agnostic, supporting both unstructured data such as videos and images as well as tabular data from data warehouses. |
| Liquibase | 🔗 | Open Source | Liquibase allows you to specify the database change you want using SQL or several different database-agnostic formats, including XML, YAML, and JSON. |
| Terminus DB | 🔗 | Open Source | TerminusDB allows you to link JSON documents in a knowledge graph through a document API. TerminusDB is available as a standalone server, or you can use our headless content and knowledge management system TerminusCMS. |
| lakeFS | 🔗 | Open Source | akeFS is an open-source tool that transforms your object storage into a Git-like repository. It enables you to manage your data lake the way you manage your code. |
| Dolt Hub | 🔗 | Open Source | Dolt is a SQL database that you can fork, clone, branch, merge, push and pull just like a Git repository. |
| Valohai | 🔗 | Both | Valohai automatically tracks every asset from code and data to logs and hyperparameters, offering full lineage of how the dataset were generated and models were trained. |
| Comet ML | 🔗site/ | NA | Comet's machine learning platform integrates with your existing infrastructure and tools so you can manage, visualize, and optimize models—from training runs to production monitoring. |
| Arrikto | 🔗 | NA | Arrikto enables MLOps teams to accelerate machine learning models to market 30-times faster than traditional ML platforms. |
| Weights & Biases | 🔗site) | Both hosted and on-premises setup | Weights & Biases (WandB) is a python package that allows us to monitor our training in real-time. |
| BlazingSQL | 🔗BlazingDB/blazingsql) | Open Source | BlazingSQL is a distributed GPU-accelerated SQL engine with data lake integration, where data lakes are huge quantities of raw data that are stored in a flat architecture. |
| Delta Lake | 🔗 | Open Source | Delta Lake is an open-source storage layer designed to run on top of an existing data lake and improve its reliability, security, and performance. |
| Data Version Control | 🔗 | Open Source | DVC is built to make ML models shareable and reproducible. It is designed to handle large files, data sets, machine learning models, and metrics as well as code. |
| Git Large File Storage (LFS) | 🔗 | Open Source | Git Large File Storage (LFS) replaces large files such as audio samples, videos, datasets, and graphics with text pointers inside Git, while storing the file contents on a remote server like GitHub.com or GitHub Enterprise. |
| Marquez | 🔗 | Open Source | Marquez maintains data provenance, shows how datasets are consumed and produced, provides global visibility into job runtimes, centralizes dataset lifecycle management, and much more. |
| Milvus | 🔗 | Open Source | Milvus is an open-source vector database built to power embedding similarity search and AI applications. |
| Pinecone | 🔗 | Close Source | The Pinecone vector database makes it easy to build high-performance vector search applications. Developer-friendly, fully managed, and easily scalable without infrastructure hassles. |
| Qdrant | 🔗 | Open Source | Qdrant is a vector similarity engine & vector database. It deploys as an API service providing search for the nearest high-dimensional vectors. |
| Quilt Data | 🔗 | Unified Source | Quilt is a unified source of information for everyone who needs to make decisions based on data. |
| Tool Name | Website Link | Open Source / Cloud / Both | About |
|---|---|---|---|
| Banana Dev | 🔗 | NA | Banana provides inference hosting for ML models & allows to run custom models with a single line of code. |
| GraphPipe | 🔗 | NA | GraphPipe is a protocol and collection of software designed to simplify machine learning model deployment and decouple it from framework-specific model implementations. |
| Hydrosphere.io | 🔗 | Open Source | Hydrosphere.io automates deployment and serving ML models, monitoring and profiling of production traffic, monitoring of models performance, data subsampling and model retraining. |
| MLEM | 🔗 | Open Source | MLEM is a tool that automatically extracts meta information like environment and frameworks from models and standardizes that information into a human-readable format within Git. |
| Apache PredictionIO | 🔗 | Open Source | Apache PredictionIO is an open source Machine Learning Server built on top of a state-of-the-art open source stack for developers and data scientists to create predictive engines for any machine learning task. |
| Quix | 🔗 | Open Source | Quix is the platform to quickly build, test and run real-time data pipelines that power next-gen apps. |
| Streamlit | 🔗 | Open Source | Streamlit is a free and open-source framework to rapidly build and share beautiful machine learning and data science web apps. |
| Vespa | 🔗 | Open Source | Vespa is a fully featured search engine that supports vector search (ANN), lexical search, and search in structured data, all in the same query. |
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