The data room
that shows its
work.
Upload your deal room documents. Ask anything. Every answer is retrieved from your workspace, cited, and scored for how well it's actually grounded.
According to the report, what's the AI maturity score?
Most AI answers ask you to just trust them.
A chatbot that summarizes a data room is easy. One where you can trust the summary enough to act on it is the actual problem — and that means showing exactly which document backed which sentence, not a generic disclaimer at the bottom of the reply.
From raw documents
to grounded answers.
Four steps, every one of them visible — not a black box between your question and its answer.
Hybrid retrieval, not just vector search.
pgvector cosine search and Postgres full-text search run together, merged and reranked — with a fuzzy fallback for typo-heavy queries neither one catches alone.
Built to be checked, not just trusted.
Grounded, cited answers
Responses stream token-by-token, then get scored sentence-by-sentence against retrieved chunks — a real grounding percentage, not a canned disclaimer.
Isolated workspaces
Every retrieval query is scoped with a workspaceId clause inside the SQL itself. Another workspace's documents can't enter the result set — not filtered out, never fetched.
Real agent tools
The assistant can create tasks, search documents, run sandboxed calculations, and summarize a workspace — each call logged with its arguments and result.
Built-in RAG evaluation
A benchmark suite computes Precision@K and Mean Reciprocal Rank against your live retrieval — not a synthetic demo dataset.
Frontend and backend, deployed independently.
A Next.js UI with zero database access, talking to a Python backend that owns every retrieval, every tool call, and every metric.
Isolation you can
point to in the query.
Deal room data doesn't mix — not because of a filter applied afterward, but because the isolation boundary lives in the retrieval query itself.
Workspace-scoped by design
Isolation is enforced inside the SQL query itself — a WHERE workspaceId clause on every retrieval, not a filter applied after the fact.
Session-based auth
JWT-backed sessions stored in an httpOnly cookie — never exposed to client-side JavaScript.
Tool execution audit trail
Every AI tool call — task creation, document search, code execution — is logged with its arguments and result.
Grounding verification
Responses are scored against retrieved source chunks, so you can see how much of an answer is actually backed by your documents.
Request-level observability
Every request carries a correlation ID through metrics, logs, and traces, so a slow or failed answer can be traced end to end.
Independently deployable
Frontend and backend ship separately — a backend fix or scale-up never requires redeploying the UI.
Stop trusting.
Start verifying.
Set up a workspace, upload a document, and ask it a question — the grounding score is right there under the answer.