AgentsBooks
Onboarding is a queue, not a craft. One client file can touch 4 documents, 3 systems and 2 reviewers before anyone decides anything. Agents work the queue; people decide.
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Sound familiar? These challenges cost teams hours every week.
Every new client arrives as a folder of half-complete documents. The work is not hard, it is relentless, and it lands faster than a small team can clear it.
A registered address gets typed into the intake form, the case tracker and the review memo. Three copies, three chances to diverge, and no single record of which one was checked.
Six months later somebody asks why a file was cleared. The answer lives in an inbox, if it survived at all.
Deploy AI agents that handle the heavy lifting — so you can focus on what matters.
An intake agent watches the channel clients already use, reads what arrives, names each document, and lists what is still missing before a person opens the file.
The case lives in the memory primitive rather than in an inbox. Every document, check and decision attaches to one record that the agents and the reviewer both read from.
Identity documents, ownership structure and screening candidates are gathered and attached to the case before it reaches a person, so review starts from evidence instead of a blank form.
Complete files move. Anything ambiguous, expired or contradictory is routed to a named reviewer together with the specific question that needs a human answer.
Each finished file produces a dated onboarding record: what was collected, what was checked, who decided, and on what basis.
This is how an AI-native service company is put together: agents hold the process, people hold the judgement, and the org chart shows both.
Five simple steps to launch your AI agent and start seeing results.
Stand up the agents a compliance firm actually needs: an intake agent, a document agent, a screening agent, and the reviewer they escalate to.
Point the control primitive at the mailbox, form or portal where client documents already arrive. Nobody is asked to learn a new tool.
State what a complete file looks like for each client type. The agents chase the gaps instead of a person maintaining a checklist by hand.
Name who reviews what. Expired documents, opaque ownership and screening candidates go to a person; the rest clears on evidence the agents attach.
Every file leaves a dated trail. That trail is the operating record of an AI-native service company, and it is what you show when someone asks.
Here's an example of what teams are building with AgentsBooks.
A four-agent desk for a compliance firm: an intake agent that reads incoming documents, a document agent that checks completeness and expiry, a screening agent that gathers candidates for review, and an escalation path to a named human reviewer who makes the decision.
Create This Agent →
Halt reads every incoming alert, classifies severity, opens the right Slack thread, and pages the on-call only when it actually matters.
Praxis turns a discovery-call transcript into a proposal: scope, timeline, fee, and a tasteful close.
Sage scans 20 feeds before standup, picks the 5 papers worth your attention, and posts a tagged Slack thread by 8 AM.
The desk above is a starting shape, not a fixed product. Take it, rename the agents, and put your own review rules on the exception path.
Create your first AI agent in under 2 minutes. No credit card, no setup complexity.