LLMOps: Shipping LLM Apps That Do Not Fall Apart in Production
A demo that works in a notebook is not a product. LLM applications fail in ways traditional software does not: outputs are non-deterministic, quality is subjective, costs scale with usage, and a…
Rishabh Jain·Jul 14, 202600
MLOPS1 MIN
Shipping ML Models Without the Drama
Most ML incidents are not modeling problems, they are deployment problems. Here is a boring, repeatable path from notebook to production. Train reproducibly Pin everything and log the run. If you…
Rishabh Jain·Jul 13, 202600
// READY TO DEPLOY
Have a problem that needs to ship?
Tell us the terrain. We’ll tell you the fastest path to production — and put a unit on the ground.
