2 Employee Onboarding AI Agents, Live in Production.
2 live agents automate employee onboarding within human resources. They all run on demand. Each one publishes the inputs it needs, the steps it works through and what it hands back.
-
Onboarding Handbook Generation
Build a new starter's handbook from your actual policies — role-specific, with every statement traced to a source and the gaps marked rather than filled in.
-
Training Documentation
Turn how a task is actually done into a document a new starter can follow — with the steps that only exist in someone's head written down and the ones nobody could verify marked.
Writing down the steps that only exist in someone's head
Onboarding documentation has a predictable decay. A handbook is written once, policies change underneath it, and the version a new starter receives contains statements that are no longer true — stated with the same confidence as the ones that are. Because nothing records where each statement came from, nobody can audit it, so the drift is invisible until a new joiner acts on something outdated. Task documentation fails differently: the person who knows how a process actually works has done it a thousand times, so the write-up omits the steps that have become automatic. What reaches the new starter is a procedure with three invisible gaps, and they fill them by interrupting a colleague, which is the cost the document was meant to remove.
These agents make provenance explicit. Onboarding Handbook Generation builds a role-specific handbook from your actual policies, with every statement traced to a source and the gaps marked rather than filled in. Marking a gap is more useful than covering it: an acknowledged gap gets closed, and a plausible invention gets believed. Training Documentation turns how a task is actually done into something a new starter can follow, with the steps that only exist in someone’s head written down and the ones nobody could verify marked as such. That marking matters for the same reason — an unverifiable step in a procedure is a place where the documentation and reality may already have parted, and flagging it is the honest output.
What this moves
- Onboarding statements traced to a source
- Every statement in a new starter's handbook is traced to an actual policy, with gaps marked rather than filled in with something plausible.
- Tasks documented well enough to follow
- The steps that live only in an experienced colleague's head are captured, and the ones nobody could verify are marked instead of guessed.
Human Resources
How AI agents handle employee onboarding
Drawn from the 2 agents above — what they require, how they run, and what comes back.
What they need
- The new starter
- Source material
- Document settings
What comes back
- Covered by policy
- Handbook
- Not covered by any policy
- Sections included
- Policies used
- Could a new starter follow this
- Training document
- Steps nobody wrote down
How they run
- Run on demand
- 2
- Steps per run
- 3
- Credits per run
- 7–8
- Use a knowledge base
- 1
Where employee onboarding fits in human resources
Leave, expenses, notice periods and benefits questions arrive daily and the answers are already in the handbook. Employees ask a person because searching a PDF is worse than asking — an agent fixes that side of it.
Next Step
Deploying employee onboarding agents
These run as-is against the inputs listed above. Most deployments adapt one — a different source system, a different tolerance, a different approval path. The first call establishes which.