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Chalk

Chalk is the real-time data platform for AI and machine learning. It provides feature pipelines, low-latency serving, training data, and compute infrastructure in your cloud.

Their llms.txt

The beginning of the file, from our validated copy saved 2026-10-21T10:09:43.250Z. Cached copy · Source on chalk.ai

# Chalk

> Chalk is the real-time data platform for AI and machine learning. It provides feature pipelines, low-latency serving, training data, and compute infrastructure in your cloud.

## Company

- [Homepage](https://chalk.ai/): Chalk is the data platform for AI and machine learning.
- [About Chalk](https://chalk.ai/about): Learn about Chalk, its mission, and its team.
- [Careers at Chalk](https://chalk.ai/careers): Open roles and life at Chalk.

## Get started

- [Book a demo](https://chalk.ai/book-demo): Talk with the Chalk team about your use case.

## Resources

- [Blog](https://chalk.ai/blog): Technical articles, product news, and company updates.
- [Customer stories](https://chalk.ai/customers): How teams build production AI and ML systems with Chalk.
- [Events](https://chalk.ai/events): Upcoming and recorded Chalk events.
- [Code examples](https://chalk.ai/code-examples): Examples of feature pipelines built with Chalk.
- [An ML agent's investigation, in a Chalk Notebook](https://chalk.ai/try/agentic-ml-notebook): A recorded, read-only Chalk Notebook in which a coding agent investigates a default-rate rise, retrains a model on Chalk Model Training and tests it on a Chalk branch against production.
- [Ship Better Models: A New ML Workflow with a Context Layer and Agents](https://chalk.ai/watch/use-chalk-notebooks-for-agents): Join us for a session on rebuilding the ML workflow around a real-time context layer and an AI agent that helps data teams investigate, iterate, and ship better models.
- [Give Agents Context for Evals & Production](https://chalk.ai/watch/agent-context-evals): Join us for a session on building production-ready agents equipped with a context layer. Real-time context helps teams avoid the pitfalls of stale data: agents that misfire and unreliable evals.
- [Life After Tecton Migrating to Chalk](https://chalk.ai/watch/databricks-tecton): Check out this on-demand webinar learn about your options following Tecton's acquisition by Databricks.
- [How Chalk fuels Whatnot’s live shopping platform](https://chalk.ai/watch/whatnot-case-study): Chalk powers Whatnot’s real-time recommendation engine, enabling low-latency personalization and scalable ML infrastructure for the largest live shopping marketplace.

## Blog posts

- [How Chalk Uses Chalk | How We Evaluate LLM Outputs Before We Trust Them](https://chalk.ai/blog/how-chalk-uses-chalk-evaluate-llm-outputs): How Chalk uses Chalk to evaluate LLM outputs before trusting them in production.
- [Give agents exactly the access they need with Chalk MCP Gateway](https://chalk.ai/blog/chalk-mcp-gateway): Give agents exactly the access they need with Chalk MCP Gateway
- [Chalk Model Gateway: Route AI in Your Own Cloud | Chalk](https://chalk.ai/blog/announcing-chalk-model-gateway): Chalk Model Gateway is an OpenAI-compatible model gateway that runs inside your existing Chalk deployment, in your own cloud. Fallbacks, budgets, rate limits, judge-based routing and tracing, with your provid
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