Hi. We're Restrct.
We're a small team of engineers who got tired of watching AI agents fall apart the moment they touched real company data. So we're building the context layer that makes them trustworthy instead.
Restrct compiles your team's knowledge and official documents into one deterministic, source-labeled context package - so every action an agent takes can be traced back to a source, a rule, and a reason.
Our Story
Restrct started the way most infrastructure companies do - with a problem we kept running into ourselves. We'd watch AI agents perform well in a demo, then get deployed against real policy documents, team memory, and edge cases, and quietly start making things up.
The issue was never the model. It was that nobody could tell the agent - or a compliance team, after the fact - where an answer actually came from, or whether it was even allowed to act on it. So we set out to build the layer that should have existed already: context that's versioned, source-labeled, and auditable by design.
Restrct is operated by Krecera Private Limited, based in New Delhi, India.
Why we're building Restrct
We at Restrct believe AI agents can only be trusted with real work once every decision they make can be traced back to a source, a rule, and a reason. Too many teams are duct-taping documents, memory, and prompts together and hoping the agent gets it right. We think context deserves the same rigor as code - versioned, tested, and auditable - so we built Restrct to be the deterministic, source-labeled context layer between your data and your agents.
Transparency
Every answer carries its source end-to-end - policy document or team memory - so nothing your agents say is a black box.
Determinism
No LLM sits in the retrieval path. The same query against the same data returns the same result, every time.
Accountability
Actions that need human approval are flagged before the agent acts, not left for the agent to decide.
Meet the founders
Nandika Gupta
Co-Founder
Nidhi Singh
Co-Founder
Madhur Prakash Mangal
Co-Founder