Chalk gives you the infrastructure to build, run, and improve production AI in your own cloud
Context
Serve fresh, real-time data to your agents and models at inference time, in milliseconds.
Runtime
Deploy and run those agents and models securely and at scale.
Learning
Train and evaluate on point-in-time correct history, so your agents and models improve from exactly what production saw.
Who uses Chalk
AI engineers
Shipping agents into production
ML engineers
Serving real-time models at scale
Data scientists
Who want to ship features directly
Risk & recsys
Risk, safety, and recsys teams that can’t afford stale data
Security & platform
Security and platform leads who need AI running in their own VPC
In production, across industries
Teams in marketplaces, payments, and consumer apps run production AI on Chalk.
- Recommendations
99.9% of users
receive a real-time personalized feed.Live marketplace recommendations based on fresh data at inference. Not yesterday’s batch.
- Payment authorization
1-2 weeks eng time saved per shipment of new data definitions to production.
Peer-to-peer marketplace scaling internal ML teams through 80% shared data patterns and self-serve.
- Social media / dating
100% air-gapped.
Data never leaves the environment.Consumer app iterating on AI matchmaking and embedding models in prod without compliance bottlenecks.
Under the hood
Python compiled to native
Write resolvers in Python. Chalk compiles them to run on a Velox high-speed engine. Notebook ergonomics, C++ performance.
Agent infrastructure in your VPC
GPUs, sandboxes, scaling groups, and a governed MCP Gateway for every agent tool call. All in your cloud.
Train/serve parity by construction
The same code runs at training and at inference. Skew doesn't accumulate and LLM evals are perfectly time-consistent.
Any data source in milliseconds
Pull from Snowflake, MySQL, Postgres, Redis Kafka, or external APIs. Your warehouse, your governance.
Named one of the World's Most Innovative Companies of 2026 by Fast Company.
