# Introducing Forge

DevFeed: [Introducing Forge](<https://devfeed.tech/articles/introducing-forge-7005.md>)

Original publisher: [Read original article](<https://mistral.ai/news/forge/>)

Published: 2026-03-17T16:00:00Z

Content type: article

Language: en

Sources: [Mistral AI Blog](<https://devfeed.tech/sources/mistral-ai-blog.md>)

Topics: [data](<https://devfeed.tech/topics/data.md>), [Orchestration](<https://devfeed.tech/topics/orchestration.md>)

Tags: [agents](<https://devfeed.tech/tags/agents.md>), [ai-models](<https://devfeed.tech/tags/ai-models.md>), [data](<https://devfeed.tech/tags/data.md>), [enterprise](<https://devfeed.tech/tags/enterprise.md>), [post-training](<https://devfeed.tech/tags/post-training.md>), [reinforcement-learning](<https://devfeed.tech/tags/reinforcement-learning.md>), [training](<https://devfeed.tech/tags/training.md>)

## AI overview

Forge is presented as a system for enterprises to train AI models on proprietary knowledge, including internal documentation, codebases, structured data, and operational records. It supports pre-training, post-training, and reinforcement learning to align models and agents with enterprise workflows and policies.

## Source excerpt

Today, we're introducing Forge, a system for enterprises to build frontier-grade AI models grounded in their proprietary knowledge.