Pricing and billing integrity
Compare applicable signed terms, billing configuration and actual charges. Identify rule mismatch and unbilled or overbilled exposure.
FINANCIAL INTELLIGENCE / AI ASSURANCE
Reliable automation needs controls at every stage. Explore how source validation, duplicate prevention, approval boundaries and independent review shape financial workflows from intake to release.
Compare applicable signed terms, billing configuration and actual charges. Identify rule mismatch and unbilled or overbilled exposure.
Distinguish investigators, financial approvers and executors; enforce authoritative in-ticket decisions.
Challenge the first diagnosis, reconcile conflicting sources and check final claims against evidence.
ENGINEERED CONTROL FRAMEWORK
My architecture treats AI as an investigator and orchestrator, not an unchecked financial operator. These controls are drawn from ATHOS, PORTHOS, ARAMIS and the batch-billing architecture; some are implemented workflow behaviors, while later policy-aligned refinements remain design specifications.
Validate organization, invoice, commercial terms, payment state and source provenance. Separate verified facts from inference; halt when authoritative evidence is absent or contradictory.
Check live records before processing; correlate original invoices, corrections and replacements. Recheck before execution to reduce duplicate charges, repeated requests and race conditions.
Separate investigation, routing, approval preparation and financial execution. Restrict tool permissions and require the appropriate authorized human for credits, refunds, reissues and approval decisions.
Classify the permitted remedy before requesting approvals. Verify current policy, applicable approval tier, segregation of duties and the approval record; never infer approval from silence or chat acknowledgement.
Stop on expired authentication, invalid inputs, uncertain payment status or failed reconciliation. Quarantine exceptions, record missing information and use controlled retry rather than silent continuation.
Normalize source rows, split combined charges, process bounded batches, inspect interim output and stop remaining batches when checks fail.
Use a separate audit pass to reconcile generated output against live source records, check charge occurrences and surface discrepancies for human remediation.
Preserve case identity, source references, timestamps, decision status, approver evidence and original-to-correction lineage. A workflow completion signal is not proof of a financial action.
Challenge the initial diagnosis, reconcile cross-system evidence and apply a final evidence-and-policy gate before presenting a recommendation.
Use explicit worker contracts, bounded data access, prompt-injection resistance, human escalation and distinct ownership between investigator, router and approval envoy.
Reject unapproved access, invalid portal requests and absent actor identity.
Validate identity, amount, payment state and original-to-correction lineage.
Boundary tests, no self-approval, in-ticket authority and special overlays.
Regression results, live version verification, human sign-off and rollback readiness.
ENGINEERING EVIDENCE / CONTROL ARCHITECTURE
The five-stage workflow demonstrates preventative duplicate checks, batch-level fail stops, structured write-back and a separate post-generation review. Explore the architecture and the failure-handling decisions behind it.
Explore the five-phase control architecture ↗Define the problem, assess the opportunities and plan a practical route to an applied AI or automation solution.