Automating Letter of Credit Compliance with Multi-Agent AI on AWS

A fintech client is building AI-driven Letter of Credit (L/C) compliance tooling for trade finance banks. Under the manual process, L/C documents arrived by courier, were scanned, and were checked by hand against UCP 600 and ISBP 821, the international rulebooks for trade finance. A single mismatched date, amount, or party name could block a payment. The review took about five days end-to-end, and peak weeks ran at ten times normal volume.

The client asked Kloia to build the AI engine that could take on this work: read the documents, apply the rules, and produce a decision an operator could trust and act on.

Kloia needed to build the AI engine behind this process: read the documents, apply the rules, and return a decision an operator could act on. The requirements set a high bar.

• Handle Messy Real-World Documents
  Scanned bills of lading, faxes, born-digital PDFs, and stamped originals, arriving in one combined packet.
  
  
• Check Every Field Against The Rulebook
  Cross-reference each detail with UCP 600 and ISBP 821 clauses, not a hard-coded rule list.
  
  Show Its Work
  Cite the specific regulation and document evidence behind every decision, so operators can trust and audit the result.
  
  
• Speak The Operator's Language
  Produce a multilingual compliance report automatically.
  
  
• Never leave a decision undefined
  A non-answer is worse than a wrong one, because the operator is left with nothing to act on. The output had to be safe to put behind a real payment release decision.

• Multi-Agent Pipeline, Not One Big Prompt
  Specialized agents (classifier, extractors, judge, rapporteur) each own one job, so the reasoning chain stays traceable end to end instead of hiding inside a single opaque call.
  
  
• Retrieval-Grounded, Not a Black Box
  Every verdict is backed by a live regulatory index, so answers cite the source clause and can be checked, not just trusted.
  
  
• Always-On Containers, Not Serverless
  The multi-agent workload keeps models and a live cache in memory, so a persistent compute tier beats cold-start functions on both cost and speed.
  
  
• Tiered Document Reading
  Fast native PDF parsing handles most pages, with OCR reserved for scans and faxes that actually need it, keeping the pipeline accurate and cost-efficient at once.

Security & Integration

• API-Based Integration
  JWT-authenticated upload and job submission, with results delivered back via webhook, so the platform drops into an existing operations workflow instead of replacing it.
  
  
• Isolated Per Client
  Each client's worker fleet and regulatory index run independently, keeping data and processing separated between tenants.
  
  
• Full Audit Trail
  Every decision, document, and citation is logged, supporting internal compliance review and regulator scrutiny of AI-assisted decisioning.
  
  
• No Infrastructure Burden
  Kloia operates the AWS environment under the client's direction, so the client's team doesn't need to staff or maintain the AI infrastructure itself.

Built To Be Trusted With a Payment Decision

The hardest part wasn't teaching the AI to read documents. It was making sure it never left a decision undefined. Early on, the system occasionally finished its review without producing a clear answer, which is worse than a wrong one: the operator is left with nothing to act on.

Kloia built a layered safety net so the platform always produces a traceable verdict, with every fallback path logged for audit. That reliability engineering is what makes it safe to put behind a real payment release decision, not just a demo.

The platform replaced manual examination end to end:

• Target examination cycle down from five days to under one.
  
  
• 26 document types automated: bills of lading, commercial invoices, certificates of origin, insurance policies, air waybills, and more.
  
  
• 330 regulatory clauses from UCP 600 and ISBP 821 indexed and cited.
  
  
• 7 specialized agents handle classification, extraction, verification, cross-checking, and reporting, work that was previously done entirely by hand.
  
  
• Accuracy is protected on every change by a golden-snapshot regression suite seeded with real client transactions. Measured outcomes against the client's target cycle time and accuracy goals are tracked by their operations team during pilot.

What This Unlocks

• Ready for multi-tenant rollout: onboarding a second bank means deploying another worker fleet against the same regulatory index, not rebuilding the platform.
  
  
• Extends to adjacent trade finance instruments (standby L/Cs, documentary collections, guarantees) by adding extractors and regulatory chunks, not rewriting the pipeline.
  
  
• Built for regulatory scrutiny: every decision carries a citation and document evidence, giving the client a defensible audit trail that a black-box model can't.