Autonomous Enterprise Document Reasoning Platform
End-to-end multimodal document reasoning, policy validation, and automated ERP dispatch
An enterprise agentic system that extracts information from complex commercial contracts and invoices, reasons across regulatory compliance policies, and executes workflow actions with deterministic human approval gates.
The Problem
Global logistics and trade organizations handle hundreds of thousands of multi-page commercial invoices, bills of lading, and customs declarations. Discrepancies between contracts and invoices were caught only after payment was processed, leading to millions in annual reconciliation loss.
Traditional OCR and regex heuristics fail when documents vary in layout, language, and table structure. Meanwhile, naive LLM prompt chains frequently hallucinated line-item totals and lacked deterministic safeguards required for financial ledgers.
Our Technical Approach
We built a multi-agent verification graph. An extractor agent performs spatial VLM document parsing; a compliance evaluator agent tests extracted values against legal rulebooks; a discrepancy arbitrator flags conflicts; and an executor agent submits verified transactions with cryptographic audit proofs.
Pipeline Architecture & Dataflow
Implementation Details
The entire agent graph is stateful and idempotent. Every tool invocation requires signed JSON payloads, and any transaction exceeding pre-configured risk thresholds automatically triggers an asynchronous escalation ticket with side-by-side visual grounding.
- •Large models should never perform arithmetic directly; they must format operands into deterministic python execution environments to avoid subtle math hallucinations.
- •Human reviewers require exact spatial bounding box overlays on the original document rather than raw extracted text to build trust.
- •Agent loops must enforce hard recursion limits (maximum 3 self-correction iterations) to prevent runaway token costs on genuinely malformed inputs.
Deploy a Similar Architecture in Your Organization
Our engineering team can evaluate your data modalities, throughput constraints, and security requirements to build a custom implementation plan.