01
Mapped 12 business domains, 52 screens, and 9 production workspaces.
Case study · Delivery evidence
An AI-native production line for accounting operations
A multi-agent workspace that treats each client portfolio as a persistent operating context and moves work through controlled production stages.
By Onyx Devs Lab · Published · Updated
The operating challenge
Accounting work was split across client files, collection, bookkeeping, review, tax preparation, and exception handling. AI needed to assist the full workflow without obscuring evidence or professional accountability.
Designed intervention
02
Separated deterministic accounting rules from AI judgement.
03
Designed queues, retries, status tracking, evidence chains, and explicit human takeover.
04
Kept final official submissions in a controlled path where direct APIs were unavailable.
Validation snapshot
These figures separate delivered scope from pilot validation. Each metric retains its measurement definition so product coverage is not mistaken for business impact.
business domains modelled
Customer, invoice, bookkeeping, filing, and compliance operations
screens and flows mapped
Interface operations translated into orchestrated production steps
production workspaces
Batch work, exception takeover, and permission governance
low-risk task automation
Tasks completed without rewriting and passed deterministic checks
evidence-chain completeness
Critical judgements retain source, rule, version, and action record
average month-end cycle
From complete documents to a result ready for human review
Cross-scenario architecture guide
Compare the retail decision layer, accounting multi-agent controls, and legal-AI provenance in one public guide while retaining each case’s evidence boundary.
Evidence boundary
The published figures separate mapped product scope from pilot workflow validation. They do not claim financial outcomes, and regulated decisions and official submissions remain subject to qualified human review.