Best AI Development Platforms for Linux

Developers can integrate advanced generative AI features—such as chatbots, text generation, and content retrieval—into .NET projects with minimal setup. The toolkit extends functionality to various tasks, including natural language processing, translation, and structured data extraction. Engineered for both speed and security, it supports on-device AI inference using hybrid CPU and GPU acceleration. This approach ensures rapid local processing of complex models while maintaining data privacy and robust performance. Regular updates incorporate the latest advancements, offering the flexibility and control needed to build secure, high-performance AI-powered applications. Its versatile capabilities streamline development and enable efficient integration of sophisticated AI functions.

An end-to-end open source machine learning platform. TensorFlow is an end-to-end open source platform for machine learning. It 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. Build and train ML models easily using intuitive high-level APIs like Keras with eager execution, which makes for immediate model iteration and easy debugging. Easily train and deploy models in the cloud, on-prem, in the browser, or on-device no matter what language you use. A simple and flexible architecture to take new ideas from concept to code, to state-of-the-art models, and to publication faster. Build, deploy, and experiment easily with TensorFlow.

Mistral AI is a pioneering artificial intelligence startup specializing in open-source generative AI. The company offers a range of customizable, enterprise-grade AI solutions deployable across various platforms, including on-premises, cloud, edge, and devices. Flagship products include "Le Chat," a multilingual AI assistant designed to enhance productivity in both personal and professional contexts, and "La Plateforme," a developer platform that enables the creation and deployment of AI-powered applications. Committed to transparency and innovation, Mistral AI positions itself as a leading independent AI lab, contributing significantly to open-source AI and policy development.

Cloobot X is a Next Gen No-Code platform built for Enterprises having in-house IT teams with the below value proposition: 1. Overcome limitations of existing No-Code Platforms (Scalability, Vendor lock-in, etc) 2. Support problem solvers including consultants, domain experts, product managers, designers and end users at every stage of the Software development lifecycle 3. Cutting down time to delivery by 10x with instant deliverables in the form of Prototypes, MVP, Workflow Apps & Codebase (In a programming language of choice) using just prompts. 4. Enable Enterprises to adapt Gen AI while addressing the concerns around it (Platform can be deployed on-premise, Can run on custom LLMs, code is generated by proprietary algorithm and not by Code-based LLMs)

Transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe. Scalable distributed training and performance optimization in research and production is enabled by the torch-distributed backend. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more. PyTorch is well supported on major cloud platforms, providing frictionless development and easy scaling. Select your preferences and run the install command. Stable represents the most currently tested and supported version of PyTorch. This should be suitable for many users. Preview is available if you want the latest, not fully tested and supported, 1.10 builds that are generated nightly. Please ensure that you have met the prerequisites (e.g., numpy), depending on your package manager. Anaconda is our recommended package manager since it installs all dependencies.

ClearML is the leading open source MLOps and AI platform that helps data science, ML engineering, and DevOps teams easily develop, orchestrate, and automate ML workflows at scale. Our frictionless, unified, end-to-end MLOps suite enables users and customers to focus on developing their ML code and automation. ClearML is used by more than 1,300 enterprise customers to develop a highly repeatable process for their end-to-end AI model lifecycle, from product feature exploration to model deployment and monitoring in production. Use all of our modules for a complete ecosystem or plug in and play with the tools you have. ClearML is trusted by more than 150,000 forward-thinking Data Scientists, Data Engineers, ML Engineers, DevOps, Product Managers and business unit decision makers at leading Fortune 500 companies, enterprises, academia, and innovative start-ups worldwide within industries such as gaming, biotech , defense, healthcare, CPG, retail, financial services, among others.

The Intel® Distribution of OpenVINO™ toolkit is an open-source AI development toolkit that accelerates inference across Intel hardware platforms. Designed to streamline AI workflows, it allows developers to deploy optimized deep learning models for computer vision, generative AI, and large language models (LLMs). With built-in tools for model optimization, the platform ensures high throughput and lower latency, reducing model footprint without compromising accuracy. OpenVINO™ is perfect for developers looking to deploy AI across a range of environments, from edge devices to cloud servers, ensuring scalability and performance across Intel architectures.

SuperAGI SuperCoder is an open-source autonomous system that combines AI-native dev platform & AI agents to enable fully autonomous software development starting with python language & frameworks SuperCoder 2.0 leverages LLMs & Large Action Model (LAM) fine-tuned for python code generation leading to one shot or few shot python functional coding with significantly higher accuracy across SWE-bench & Codebench As an autonomous system, SuperCoder 2.0 combines software guardrails specific to development framework starting with Flask & Django with SuperAGI’s Generally Intelligent Developer Agents to deliver complex real world software systems SuperCoder 2.0 deeply integrates with existing developer stack such as Jira, Github or Gitlab, Jenkins, CSPs and QA solutions such as BrowserStack /Selenium Clouds to ensure a seamless software development experience

Build, deploy, and scale end-to-end AI applications in the cloud. Griptape gives developers everything they need to build, deploy, and scale retrieval-driven AI-powered applications, from the development framework to the execution runtime. 🎢 Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. ☁️ Griptape Cloud is a one-stop shop to hosting your AI structures, whether they are built with Griptape, another framework, or call directly to the LLMs themselves. Simply point to your GitHub repository to get started. 🔥 Run your hosted code by hitting a basic API layer from wherever you need, offloading the expensive tasks of AI development to the cloud. 📈 Automatically scale workloads to fit your needs.

Faros AI connects the dots between your engineering data sources – ticketing, source control, CI/CD, and more – giving unprecedented visibility and insight into your engineering processes. Be amazed at what you can achieve with Faros AI. With Faros AI, engineering leaders can scale their operations in a more data-informed way — using data to identify bottlenecks, measure progress towards organizational goals, better support teams with the right resources, and accurately assess the impact of interventions over time. DORA Metrics come standard in Faros AI, and the platform is extensible to allow organizations to build their own custom dashboards and metrics so they can get deep insights into their engineering operations and take intelligent action in a data-driven manner. Leading organizations including Box, Coursera, GoFundMe, Astronomer, Salesforce, etc. trust Faros AI as their engops platform of choice.

DeepSpeed is an open source deep learning optimization library for PyTorch. It's designed to reduce computing power and memory use, and to train large distributed models with better parallelism on existing computer hardware. DeepSpeed is optimized for low latency, high throughput training. DeepSpeed can train DL models with over a hundred billion parameters on the current generation of GPU clusters. It can also train up to 13 billion parameters in a single GPU. DeepSpeed is developed by Microsoft and aims to offer distributed training for large-scale models. It's built on top of PyTorch, which specializes in data parallelism.

Ollama is an innovative platform that focuses on providing AI-powered tools and services, designed to make it easier for users to interact with and build AI-driven applications. Run AI models locally. By offering a range of solutions, including natural language processing models and customizable AI features, Ollama empowers developers, businesses, and organizations to integrate advanced machine learning technologies into their workflows. With an emphasis on usability and accessibility, Ollama strives to simplify the process of working with AI, making it an appealing option for those looking to harness the potential of artificial intelligence in their projects.

Lilac is an open source tool that enables data and AI practitioners to improve their products by improving their data. Understand your data with powerful search and filtering. Collaborate with your team on a single, centralized dataset. Apply best practices for data curation, like removing duplicates and PII to reduce dataset size and lower training cost and time. See how your pipeline impacts your data using our diff viewer. Clustering is a technique that automatically assigns categories to each document by analyzing the text content and putting similar documents in the same category. This reveals the overarching structure of your dataset. Lilac uses state-of-the-art algorithms and LLMs to cluster the dataset and assign informative, descriptive titles. Before we do advanced searching, like concept or semantic search, we can immediately use keyword search by typing a keyword in the search box.

With our advanced planning engine, even the most complex user requests can be executed. Out-of-the-box automation, inside your product. So your users can ask your system to do awesome things using normal texts, things like "Please show me last month's sales and give me some recommendations". You can plug OpenCopilot into your product using our chat bubble, and no coding skills are required. Or you can use our SDKs to make your copilot truly blend in. You can also feed your copilot all sorts of data and it will be able to understand it and offer help to your users. You can self-host OpenCopilot on your website using a single make install command. All paid plans include personal support from the team. Your users can ask complex questions that require executing multiple actions in one go. The single platform to build, manage, and deploy your next AI-powered feature. You will get new features first, it's going to be super nice since we ship a lot.

Model Context Protocol (MCP) is an open protocol designed to standardize how applications provide context to large language models (LLMs). It acts as a universal connector, similar to a USB-C port, allowing LLMs to seamlessly integrate with various data sources and tools. MCP supports a client-server architecture, enabling programs (clients) to interact with lightweight servers that expose specific capabilities. With growing pre-built integrations and flexibility to switch between LLM vendors, MCP helps users build complex workflows and AI agents while ensuring secure data management within their infrastructure.

Serve your ML model in any cloud in minutes. Unified model packaging format enabling both online and offline serving on any platform. 100x the throughput of your regular flask-based model server, thanks to our advanced micro-batching mechanism. Deliver high-quality prediction services that speak the DevOps language and integrate perfectly with common infrastructure tools. Unified format for deployment. High-performance model serving. DevOps best practices baked in. The service uses the BERT model trained with the TensorFlow framework to predict movie reviews' sentiment. DevOps-free BentoML workflow, from prediction service registry, deployment automation, to endpoint monitoring, all configured automatically for your team. A solid foundation for running serious ML workloads in production. Keep all your team's models, deployments, and changes highly visible and control access via SSO, RBAC, client authentication, and auditing logs.

Composio is an integration platform designed to enhance AI agents and Large Language Models (LLMs) by providing seamless connections to over 150 tools with minimal code. It supports a wide array of agentic frameworks and LLM providers, facilitating function calling for efficient task execution. Composio offers a comprehensive repository of tools, including GitHub, Salesforce, file management systems, and code execution environments, enabling AI agents to perform diverse actions and subscribe to various triggers. The platform features managed authentication, allowing users to oversee authentication processes for all users and agents from a centralized dashboard. Composio's core capabilities include a developer-first integration approach, built-in authentication management, an expanding catalog of over 90 ready-to-connect tools, a 30% increase in reliability through simplified JSON structures and improved error handling, SOC Type II compliance ensuring maximum data security.

Steev is an AI training assistant that manages your training runs, eliminating the need for constant supervision and enhancing model performance. It reviews and analyzes your code before training begins, identifying potential errors, providing fixes, and suggesting better approaches to improve your workflow and outcomes. Steev takes proactive steps, adjusts training parameters, and resolves issues before they escalate, going beyond mere observation. Tracking all key variables during training, Steev sends instant notifications when your attention is needed, eliminating constant progress checks. Everything you need for smarter training is built into Steev, ready to go with zero setup required. You can try Steev for free during their beta program.

A hybrid front-end seamlessly transitions between Gluon eager imperative mode and symbolic mode to provide both flexibility and speed. Scalable distributed training and performance optimization in research and production is enabled by the dual parameter server and Horovod support. Deep integration into Python and support for Scala, Julia, Clojure, Java, C++, R and Perl. A thriving ecosystem of tools and libraries extends MXNet and enables use-cases in computer vision, NLP, time series and more. Apache MXNet is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision-making process have stabilized in a manner consistent with other successful ASF projects. Join the MXNet scientific community to contribute, learn, and get answers to your questions.

RapidCanvas is a no-code AI platform that helps businesses go from idea to live AI solution within hours. Our AutoAI technology automates the AI build and deploy process, reducing time to value by 90%. We work with you to understand your needs and create an out-of-the-box AI solution that is tailored to your specific requirements. Our data science experts will work with you to optimize the results to your satisfaction. RapidCanvas is a trusted partner for leaders in Financial Services, Retail, Renewable Energy, and Manufacturing. We have a proven track record of success in helping businesses achieve their goals with AI. If you are looking for a way to accelerate your AI journey, RapidCanvas can help. Contact us today to learn more.