S6CLASSIFY · REVIEW · SHIP
AI Workflow Layer
AI embedded in specific workflow steps — classification, extraction or bounded assistants with mandatory review, not floating chat.
// PROBLEM · FIELD SIGNALS
Teams experiment with AI in isolation; outputs leak into customers without review; data boundaries are unclear.
// WHAT GETS BUILT
- AI steps inside states with permissions and corpus boundaries
- Review UI before customer-facing or ledger writes
- Audit trail alongside workflow history
// TYPICAL MODULES
- Document classification / extraction
- Controlled RAG or internal search
- Review + correction UI
- Risk boundaries + audit log
- Integration with workflow states
// WHEN THIS FITS
- Document-heavy flows with repetitive triage
- Knowledge is scattered across PDFs and legacy files
- Workflow basics exist — AI layers on structure, not chaos
// WHAT THE CLIENT GETS
Measured leverage from AI — outputs gated by review states your team actually uses.
// STARTING SCOPE · NON-BINDING
Data hygiene and review design dominate cost — scoped pilots before broad rollout.
// RECOMMENDED NEXT STEP
Use the scope diagnostic to sequence layers and surface hidden coupling — then contact with the messy version of tools, volumes and failure modes. No fictional case studies: typical use cases are mapped after intake.