Counterparty Intel Docs // Product System
A real diligence system, not a report prompt.
Argus converts messy counterparty submissions into structured intelligence through an 8-stage review pipeline, evidence artifacts, traceability controls, deterministic checks, and human-review posture.
These docs explain the standards, outputs, and review posture behind Argus without exposing the internal implementation recipe.
Public docs should make it obvious that Argus is operationally real without revealing prompts, providers, orchestration internals, smoke commands, or system recipes.
Argus is designed as a multi-stage diligence engine. It ingests counterparty material, separates claims from evidence, maps source support, identifies contradictions, preserves artifacts, and produces a reviewable intelligence output.
The public docs describe intake, claim extraction, entity mapping, source review, evidence classification, contradiction detection, report assembly, and human-review posture without exposing the internal recipe.
Read moreArgus is meant to preserve the review trail: what was claimed, what was supported, what contradicted the claim, what remained unresolved, and where a human reviewer should focus.
Read moreArgus is built with deterministic checks, smoke-test discipline, structured artifacts, predictable report assembly, and validation boundaries that make investigations reviewable and comparable over time.
Read moreSee the high-level operating shape of the system without exposing the private orchestration recipe.
Understand why Argus produces reviewable artifacts instead of only narrative outputs.
See how findings, posture, contradictions, unresolved items, and escalation points fit together in a public-facing output model.
Read how repeatability, validation, and report discipline are treated without revealing internal commands or implementation mechanics.