How do we make AI automation dependable enough for finance or compliance?
Agentic workflow design
A model that is nearly always right sounds excellent until it runs against your ledger all day. Nearly right is wrong, repeatedly, and delivered with exactly the same confidence as the correct answers. So the model is never the last thing to touch a decision. The agent proposes; deterministic rules, schemas, tests and a human where the risk warrants it decide what proceeds. Finance, data migration and compliance work is built this way because an auditor, not a user, finds the errors.
Why accuracy is the wrong measure
A model that is right 95% of the time produces fifty wrong entries a day at a thousand runs, delivered with the same confidence as the correct ones. The useful question is not how often the system is right, but whether anything notices when it is not.
The pattern that answers it is set out in full on the concept page, with worked detail on what a verifier actually checks.
The agent proposes
The judgment across messy inputs.
The verifier gates
Deterministic checks, none of them a model.
Pass proceeds, fail holds
A failure routes to a person with the reason attached.
Where it earns its keep
Finance-critical automation, data migration validation, knowledge extraction, semantic-layer query validation, report generation, operational triage, and internal tooling that writes to systems of record.
It is unnecessary where the output is read by the person who asked for it before anything happens: a drafting assistant does not need a gate, because the reader is one.
What you get
- Workflow design with explicit gate criteria
- Deterministic validator suite
- Human review routing and exception handling
- Audit trail generated as a by-product of the gates
- Test coverage for the verification layer
Start here if
- Automation touches money, identity, or a regulated process
- A previous automation shipped errors nobody caught
- Reviewers are rubber-stamping a queue that is mostly correct
- The process must be explainable to audit or risk
Frequently asked questions
What do you need from us before gate design can start?
The workflow, and the cost of a silent error in it. Those two facts decide how much of the check can be deterministic and where a person has to stand. Everything else follows from them.
Does this work on a process we have already automated?
Usually, and it is the more common starting point. An automation that already runs has a history of the errors it produced, which is the best specification anyone could write for what the verifier has to catch.
Related
Automating something that must not be wrong?
Tell us the workflow and the cost of a silent error. The gate design follows from those two facts.
Last reviewed · 1AYM