Put AI to work for you, the open source way
Artificial intelligence (AI) is powering new discoveries and experiences across fields and industries. Use Red Hat platforms to build, deploy, monitor, and use AI models and applications, accelerated by the speed, trust, and transparency of the open source community.
Featured solutions for building and using AI
Red Hat® Enterprise Linux® AI
Get started with an open source-licensed LLM.
Red Hat Enterprise Linux AI can help you encourage creativity and bring generative AI (gen AI) applications to life.
Red Hat Enterprise Linux AI brings together the Granite family of open source-licensed large language models (LLMs) and InstructLab, a community-driven solution for enhancing LLM capabilities.
Red Hat OpenShift® AI
Create and run AI apps across our hybrid cloud.
Red Hat OpenShift AI is an open source platform for building, training, testing, and serving models for your own AI-enabled applications.
Data scientists and developers can rapidly deploy and monitor ML workloads and models on-premise and in the public cloud through a fully supported environment.
Overview
Red Hat Lightspeed
Use AI to increase efficiency.
Following Red Hat Ansible® Lightspeed with IBM watsonx Code Assistant, Red Hat is rolling out additional gen AI services that make platforms easier to use.
The Red Hat Lightspeed portfolio will include OpenShift Lightspeed, a gen AI-based virtual assistant to troubleshoot problems and get help. Additionally, the upcoming Red Hat Enterprise Linux Lightspeed aims to demystify building, deploying and managing Linux.
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Why choose Red Hat for AI?
With the technological foundation of Linux, containers, and automation, Red Hat’s open hybrid cloud strategy gives you the flexibility to run your AI applications anywhere you need them.
Red Hat Enterprise Linux AI is a foundation model platform used to seamlessly develop, test, and run Granite family large language models (LLMs) for enterprise applications.
Red Hat OpenShift AI provides the common platform for your teams to build and deploy AI applications and machine learning (ML) models with transparency and control.
For large AI deployments, Red Hat OpenShift offers a scalable application platform suitable for AI workloads, complete with access to popular hardware accelerators.
Through Red Hat Lightspeed, AI-enabled tools are improving productivity and lowering the skills barrier, beginning with Red Hat Ansible Automation Platform, and continuing across the Red Hat portfolio.
Community projects
Red Hat believes an open source approach to AI removes barriers to experimentation and innovation.
InstructLab offers a new approach to contributing to and training LLMs that uses the power of the open source contributor model.
Podman AI Lab gives developers the ability to build, test, and run gen AI applications using an intuitive, graphical interface on their local workstation.
Play in the OpenShift AI sandbox
With components curated from Open Data Hub and other open source projects, Red Hat OpenShift AI gives data scientists and developers a powerful open hybrid AI/ML platform for gathering insights from data and building AI-enabled applications. Take it for a spin in our developer sandbox.
Connect with an AI ecosystem
Complete your AI pipeline with Red Hat’s AI partners. Access solutions ranging from data integration and preparation, to AI model development and training, to model serving and inferencing based on new data.
Solution Pattern
AI applications with Red Hat and NVIDIA AI Enterprise
Create a RAG application
Red Hat OpenShift AI is a platform for building data science projects and serving AI-enabled applications. You can integrate all the tools you need to support retrieval-augmented generation (RAG), a method for getting AI answers from your own reference documents. When you connect OpenShift AI with NVIDIA AI Enterprise, you can experiment with large language models (LLMs) to find the optimal model for your application.
Build a pipeline for documents
To make use of RAG, you first need to ingest your documents into a vector database. In our example app, we embed a set of product documents in a Redis database. Since these documents change frequently, we can create a pipeline for this process that we’ll run periodically, so we always have the latest versions of the documents.
Browse the LLM catalog
NVIDIA AI Enterprise gives you access to a catalog of different LLMs, so you can try different choices and select the model that delivers the best results. The models are hosted in the NVIDIA API catalog. Once you’ve set up an API token, you can deploy a model using the NVIDIA NIM model serving platform directly from OpenShift AI.
Choose the right model
As you test different LLMs, your users can rate each generated response. You can set up a Grafana monitoring dashboard to compare the ratings, as well as latency and response time for each model. Then you can use that data to choose the best LLM to use in production.
Real-world AI success stories
Red Hat Helps Ortec Finance Accelerate Growth and Time to Market
Ortec Finance, a global technology and solutions provider for risk and return management, is serving machine learning models on Microsoft Azure Red Hat OpenShift and is adopting Red Hat OpenShift AI.
Banco Galicia speeds new customer onboarding
Using an AI-based natural language processing (NLP) solution Red Hat OpenShift, the bank cut verification times from days to minutes with 90% accuracy.
Boston University builds an educational platform
Using Red Hat OpenShift AI, Boston University scaled a learning environment to accommodate hundreds of computer science and computer engineering users.