docenta is a local-first content retrieval engine built for LLM agents. It turns your files, mail, and chat history into one askable collection. Answers come with receipts: exact file, exact span. Nothing leaves your machine.
Real behavior, not a mockup: document search, mail, and past agent sessions are one corpus. The docent answers from all of it.
docenta answers "which of my files says this" and proves it. A docent is the museum guide you ask about a collection. Documentum is Latin for "a thing that teaches". Your corpus gets a docent.
Ingest, index, embeddings, answers: all on your hardware. Zero uploads, zero telemetry, zero cloud dependency. Originals are never copied; only searchable derivatives are stored.
The primary user is your AI agent. Token-disciplined content_search, entity_card, timeline, and evidence_pack tools over MCP; your agent already speaks the protocol.
Answers cite exact spans in exact files. Token budgets are enforced and disclosed. When the corpus cannot answer, docenta says so instead of improvising.
In a 48-task agent harness, the evidence pack answered 44 of 48 questions against 39 for iterative search, in 1 to 2.5 tool calls per task. Deterministic layers, zero learned models in the loop, bit-stable re-runs.
The same docent, pointed at what your work actually holds. Each page shows the shape of an answer for one kind of desk.
Pleadings, scanned exhibits and the mail thread with opposing counsel, cited by page and line. Privilege stays on the machine.
Adjuster notes, policies, forms and photos with their time and place, as one timeline with receipts.
Twenty years of mail, photos and documents, asked in plain words, honest when the answer is not there.
An export in an evening, the live mailbox from then on; threads, attachments and fields that answer.
Code, git history and every agent session as one corpus over MCP, measured against grep.
Thousands of PDFs, notes and drafts with a citation for every claim and the conflicts shown.
docenta is a commercial product of SKY, LLC, now in private preview. Tell us what your agent needs to remember and we will tell you when the door opens.
request early access or check back here: the public beta will be announced on docenta.ai