An Aivell watches a mailbox and your network folders for new documents, reads each one onboard — office files, PDFs, scans, photos — gives it a clean title, files it, and indexes it into the knowledge base so search finds it minutes after it arrives. No uploads, no manual tagging, no stale handbook.
starts when: A new document lands in the docs mailbox or a watched folder
Every knowledge base is a snapshot of the week someone had time to maintain it. The launch is glorious: everything tagged, everything findable. Six months later the handbook is three versions behind, the newest spec sheet lives in someone’s inbox, and the search returns the 2022 price list with total confidence.
The rot isn’t laziness — it’s that keeping documentation current is a job nobody was hired for. Someone has to notice the new file, convert it, name it sensibly, put it in the right place and update the index. That’s classic invisible admin, the kind that quietly costs businesses around $17,000 per employee per year. So it doesn’t happen, and the knowledge base becomes a museum.
The result is a knowledge base with the one property none of them have: it is current on a random Tuesday, not just the week after the cleanup.
No flowcharts, no code — a chore is just a message to your Aivell, in your own words. It shapes it into a solid, guarded procedure and follows it to the letter. This one:
watch docs@ and the handbook folder on the share for new files
read each file onboard — office files, PDFs, scans, whiteboard photos
give it a clean title and file it under the right section
newer version of an existing document? replace it, archive the old one
anything mentioning salaries or personnel waits for Paolo before indexing
index it into the knowledge base — searchable within minutes
reply to the sender saying what was indexed and where it lives
first monday of the month, list documents older than two years for review
Connected with single-click passkeys — no copied tokens, no OAuth hell.
Every tool can be limited to exactly what this chore needs. For this one, you might set:
If a person can read it, so can the box — office documents, PDFs, scanned contracts, a phone photo of a whiteboard from this morning's meeting. The vision model runs onboard, so a photographed page gets the same privacy as a typed one.
No. Conversion, reading and indexing all run on the box inside your network. A draft contract dropped in the folder is searchable ten minutes later and has never crossed your firewall.
Two layers. The chore routes sensitive material — the example above holds anything about personnel for Paolo's approval — and the guardrails limit which folders the Aivell can index at all. What you never point it at, it never sees.
The new version replaces the old one in the index, and the old file moves to the archive rather than being deleted. Answers cite the current version; the paper trail keeps every previous one.
Every manual, contract and memo indexed on a box in your office. Your team asks in plain language and gets cited answers — nothing leaves the building.
Incoming paperwork classified, renamed and filed to the correct folder by an AI colleague that reads each page inside your office — no document uploaded anywhere.
Leave, benefits, expenses — employees ask in chat and get answers quoting your own HR handbook. Questions never leave the box in your office.
An Aivell is an on-premise AI colleague: a small box that plugs into your network, runs its own AI onboard and takes the repetitive work off your desk. Prompts, documents, data — nothing ever leaves your office. Unplug the internet: it keeps working.
You describe each task as a chore, in plain language. Your Aivell turns it into a solid, guarded procedure and runs it in the background — with guardrails on every tool, a complete audit trail, and approvals in your hand when you want them. One-time setup, fixed monthly fee. No tokens, no overages.
onboard inference · air-gapped · fixed monthly fee