Reconciliation
Compare records across systems that disagree - ledger against bank, ERP against spreadsheet - and surface only the exceptions worth a person's time.
Endeavor for financial services and accounting
Endeavor automates finance work that has to survive an audit. Reconciliation, extraction, and first-pass review — with source attribution, versioned instructions, and human approval where the risk sits.
Accuracy is not enough on its own
In regulated work, being right is only half of it. You also have to show why the answer is right, which records produced it, and who signed off. A model that cannot answer those questions cannot be used, however good it is.
That is the gap Endeavor is built to close: not a cleverer model, but an evidence trail around it.
Where it fits
Document extraction
Pull structured fields and obligations out of invoices, contracts, and statements against schemas you define.
Close support
Run recurring checks and first-pass review consistently, so the same standard is applied every period.
The audit trail
| Question an auditor asks | What Endeavor produces |
|---|---|
| Which records were used? | Source attribution on every output |
| What was the agent told to do? | Immutable version history of instructions |
| Who approved this? | Named human sign-off recorded against the agent |
| Could it have seen data it shouldn't? | Access scoped to the initiating user's clearance |
| What did it cost? | Token spend attributed per task |
Frequently asked questions
Is AI output defensible in an audit?
It is if you can show what produced it. Endeavor records which source records were read, the instructions in force at the time, and who approved the agent - which is what an auditor actually asks for.
What finance work is a realistic starting point?
Reconciliation between systems that disagree, extraction from invoices and contracts, close-support checks, and first-pass review of documents a person currently reads in full.
How is sensitive financial data protected?
Sensitive values are redacted before any external model call, models can be hosted locally so nothing leaves your environment, and each agent is scoped to the clearance of the person who invoked it.
Does a human still approve the outcome?
Yes, wherever you decide. Approval gates are identified during decomposition and built into the workflow rather than added afterwards.