Where it lives
Private & protected
Your searchable index is built and stored for your account alone — never used to train models.
Security & trust
Your data stays yours.
Your searchable index lives in a private workspace. AI gets the relevant passage and its source — not your whole archive. Full end-to-end privacy and zero data retention.
What comes back
Source included
Agents receive the relevant passage with its source by default. They can request more when needed without automatically loading the whole file.
Who can see what
Team boundaries
Separate permission groups for departments, matters, or clients. Search respects those walls before anything reaches an agent.
Less leaves the building
Same answer, less exposure.
Because it stops re-reading whole files, your agent gets the passage and its source instead of the document — so less of your material ever leaves for the model provider to reach the same answer. Zero data retention policies ensure your raw material is never stored long-term.
Agent access
Your AI connects inside your network.
Find and Seek lets approved AI tools connect on your machine or private network. The searchable library is not sent through a Find and Seek cloud service.
Execution
No open-ended agent loop.
What an agent can reach through Find and Seek is a fixed, whitelisted surface: search the memory, read the evidence, follow it back to the source. It cannot run shell commands, make arbitrary web requests, or read outside what you connected. The tier above that — approvals, saved analyses, a run trail — is built and sits behind an experimental flag until it survives the same adversarial testing the shipped surface went through. We would rather say that than imply you can buy it today.
Shipped
Whitelisted actions only
Shell commands, arbitrary HTTP, and unconstrained file reads are rejected by design.
Behind a flag
Human sign-off
Sensitive departments, clients, or matters requiring explicit approval before analysis proceeds.
Behind a flag
Run trail
What ran, which information it used, and which sources supported the result, recorded for review.
Still being finished
Honest boundaries.
AI responses show sources and confidence without exposing how the search works under the hood. The local searchable library is sensitive, so encryption, consent controls, and sensitivity levels are part of the enterprise release path. Individual user identity for AI connections is on the roadmap for multi-user setups.
One more thing
This is a trust summary for buyers and evaluators — not a penetration-test report. For a security review on an enterprise deployment, contact enterprise@findandseek.app.