MergeOn Intelligence

MergeOn is document intelligence infrastructure that produces structured, auditable outputs called ReviewPacks. It is designed to replace manual document review workflows by combining multi-model intelligence, deterministic policy enforcement, and mandatory human acceptance to deliver results in hours or days rather than weeks.

ReviewPacks and Tiers

A ReviewPack is the atomic unit of MergeOn output: extracted fields, evidence anchors, tasks, confidence, geometry coordinates (when applicable), policy checks, and acceptance state.

Tier 1: Verified

Evidence-anchored extraction suitable for automation. Outputs are validated through enforced human review.

Tier 2: Findings

Flags inconsistencies, missing data, and anomalies for prioritized action.

Tier 3: Strategic Intelligence

Produces dependency-aware reasoning and scenario implications while remaining evidence-aligned.

Human-in-the-Loop Accuracy

MergeOn enforces human review on all tasks before final acceptance. Field geometry and coordinate placement are human-verified prior to being promoted to verified truth.

No ReviewPack is promoted to verified truth without explicit human acceptance; automated outputs alone are never treated as final.

MIL: MergeOn Intelligence Layer

MIL orchestrates multi-model co-generation and reconciliation. MergeOn is model-agnostic and designed to work across frontier model providers. Disagreement is treated as signal; convergence is enforced through gating, evidence checks, and escalation to human review.

Methods

• Monte Carlo uncertainty estimation
• Bayesian belief updating and confidence weighting
• Hungarian algorithm matching for optimal assignment and deduplication
• Regression and anomaly detection
• GraphRAG for entity-relationship grounded retrieval and reasoning
• KAN / MF-KAN style representations where non-linear feature learning improves stability

THEMIS: Policy and Compliance Enforcement

THEMIS is the enforcement layer that determines what can be accepted as truth. It applies policy rules, evidence requirements, and admissibility constraints so that outputs remain defensible and auditable.

Co-generation positioning

MergeOn outputs are co-generated and reconciled across multiple frontier models. MergeOn does not depend on any single model provider; it uses multi-model variance and agreement as part of the pipeline and finalizes truth through policy enforcement and human acceptance.