Context
The operating situation
Accounting firms carry client books from bank-file import through categorization, review, workpapers, year-end close, and tax-ready handoff. Most automation in this space asks professionals to trust a decision they cannot inspect.
Challenge
The operating problem
Move client books from bank-file import toward review, workpapers, year-end close, and tax-ready handoff while keeping professional judgment in control.
Approach
Decisions that shaped it
- Built the web application, backend services, and firm/client workflow end to end.
- Made confidence, reasoning, corrections, and review states visible instead of hiding them behind automation.
- Established a sandbox and production-oriented security foundations for iterative validation.
Solution
What was delivered
A web application, backend services, and firm/client workflow covering AI-assisted categorization, audit trail, correction history, and human review, running on a sandbox and production-oriented security foundation.
Outcome
Documented outcome
A working product foundation where AI-assisted categorization is proposed with visible reasoning, corrected where wrong, and confirmed by an accountant before it counts.
Beta maturity. No claim is made of autonomous bookkeeping, guaranteed accounting accuracy, or regulatory approval. Product metrics, screenshots, and user counts are held back pending owner approval.
Controls
What kept it safe to operate
- Confidence and reasoning exposed on every transaction decision rather than hidden behind automation.
- Correction history retained so a reviewer can see what changed and why.
- Human review states gate the workflow; the product proposes, an accountant decides.
- Sandbox environment separated from production-oriented security foundations.