AUTONOMOUS WORKFORCE
AI back office automation for the work that has to be right: matching invoices to purchase orders, chasing approvals, reconciling accounts, watching compliance obligations and filing what comes back. Every decision leaves an audit trail, and money never moves without a person.
What a finance agent does, and what it never does
An AI finance agent is a scoped worker on a back-office queue: it reads documents, matches them against your records, applies your rules and tolerances, and either completes the item or stops it with a reason attached.
Finance is the department where the guardrails matter most, so the design starts there. Agents in this pillar are built to stop. A mismatch outside tolerance, a changed bank detail, a duplicate, an unfamiliar supplier - each has a defined halt condition rather than a best guess. Nothing that moves money happens without a named approver, and that is architecture, not policy.
The return comes from volume and timing. These queues are large, rule-bound and currently worked in office hours by people who are expensive and bored. Agents work them overnight, so your team arrives to exceptions rather than a backlog.
You probably need this if you recognize these
- Month-end is a scramble, and everyone knows exactly which three days.
- Invoices arrive in six formats and get keyed by hand.
- Approvals sit in someone’s inbox until a supplier chases.
- Reconciliation is done by a person comparing two screens.
- You cannot answer “why was this paid” without asking someone who remembers.
What you get
A document intake agent
Reads invoices, receipts and statements in whatever format they arrive and extracts the fields that matter.
A matching agent
Reconciles documents against purchase orders, receipts and ledger entries line by line, within your tolerances.
A chasing agent
Follows up approvals and missing documents on schedule, and escalates by age.
A compliance watch agent
Monitors obligations and flags what needs review before a deadline, not after.
An onboarding agent
Runs supplier and customer onboarding checklists and files what comes back.
The audit trail
Every extraction, match, decision and approval recorded together, exportable for your auditors.
How an invoice moves through the hive
AI finance and back-office automation
Arrive
The invoice lands by email or supplier portal. The orchestrator opens a run and logs the source.
Self-healed - retried with fallback tool. Human not required.
Extract
Line items, totals, dates, tax and supplier details are read from whatever format arrived.
Match
The purchase order and goods receipt are found and compared line by line.
Check
Tolerances, duplicates, tax treatment and changed bank details are tested against your rules.
Post or stop
Clean invoices post to the ledger and queue for payment. Anything else stops.
Escalate
Stopped items wait for a named approver with the discrepancy already highlighted.
The back office, staffed
Invoice Matching Agent
Matches invoices to purchase orders and receipts, and stops the ones that do not reconcile.
Compliance Watch Agent
Tracks obligations and deadlines and flags what needs a human review.
Onboarding Agent
Runs the checklist, chases the missing documents and files the results.
Where finance agents work
Agents read and write through your existing finance systems. We do not ask you to move your ledger.
- ERP and accounting
- Purchasing and procurement
- Banking and payment platforms
- Document and email intake
- Expense systems
- CRM
- Data warehouse
- Document storage and archives
Platform names are shown as examples of the categories agents connect to. They are not partnerships or endorsements.
Where the agent always stops
Autonomy boundary
Agents may extract, match, post within tolerance, chase and file. Paying, changing bank details and creating suppliers are always outside it.
Approval gates
Every payment, every tolerance exception and every new supplier reaches a named approver with the evidence attached.
What stays human
Judgment on disputes, anything unusual about a supplier, and every decision with a legal or tax consequence.
Logging
Source document, extracted values, match result, rule applied, decision and approver, kept together for the retention period you set.
How the work runs
Typical ranges from our engagement model (doc 04 §5), not a quote.
| Stage | Typical | What happens |
|---|---|---|
| Pilot | 3-10 days audit, then 2-4 weeks | Extraction and matching on real historical documents, scored against what your team decided at the time. |
| Build | 3-8 weeks | ERP integration, tolerance rules, approval routing, exception categories and the audit export. |
| Release | 1-2 weeks | Shadow matching alongside your current process, compared item by item before anything posts. |
| Managed | ongoing, optional | New supplier formats absorbed, tolerances tuned, exception categories extended. |
What we measure
- Touchless rate
- Share of items completing without a person, measured against your baseline (Yours)
- Overnight
- The queue is worked before your team arrives (Target)
- 0
- Payments made without a named approver (Target)
- 100%
- Of decisions reconstructable from the audit trail (Target)
“ Until then these are design targets and measurement commitments, not results.
What this looks like in practice
Reconciliation hive
Reference scenario · FinTech. Invoice and payment matching with a full audit trail and a human approval gate.
Reference scenario - a composite build illustrating our method. Figures are modeled and the model is shown.
Frequently asked questions
Will an agent ever pay an invoice on its own?
No. Posting to the ledger within tolerance is inside the boundary; releasing payment never is. Every payment has a named approver, and that gate is enforced in the integration rather than assumed in a policy document. We would decline to build it the other way.
What about fraud, especially changed bank details?
Changed bank details are a hard halt condition, not a tolerance. The agent flags the change, shows the previous value and the source of the new one, and waits. Agents are consistent in a way people under time pressure are not, which is exactly where this class of fraud succeeds today.
Will our auditors accept this?
The audit trail is designed for that conversation: source document, extracted values, rule applied, decision, approver and timestamp, exportable. We build to your retention policy and your controls. We cannot promise what a specific auditor will accept, and anyone who does is guessing.
Our invoices arrive in a dozen formats. Does that break it?
That is the normal starting condition and the main reason keying is still manual. Extraction is built against your real historical documents, including the awkward suppliers, and new formats are absorbed as they appear rather than requiring a rebuild.
Do we need to change our ERP?
No. Agents work through your existing finance systems with scoped credentials. Where an API is missing or poor, that integration work is scoped in the audit rather than discovered mid-build - see AI integration.
What happens at month-end when volume spikes?
That is where the return concentrates. Agents scale with volume rather than with staffing, so the spike is absorbed instead of planned around. Your team spends month-end on exceptions and judgment rather than on the backlog.
Related services
Managed AI Workforce
We run the hive and keep it healthy.
Business Process Automation
End-to-end processes that run without a queue.
AI Integration & Implementation
Connecting agents to your ERP and finance stack.