AI & Data

VETO — Verification Engine

Multi-model epistemic verification engine that validates scientific claims through adaptive jury deliberation, achieving 90% cost reduction over brute-force approaches.

1,053 tests, all passing Test Coverage
~90% reduction via Cost Pyramid Cost Optimization
Adaptive Jury with 5 circuit breakers Architecture
48 Python modules, 8 rubrics, 6 connectors Modules
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Overview

Why Verification Matters

In the era of AI-generated content, the ability to verify scientific claims at scale is no longer optional — it is infrastructure. VETO addresses this by providing a transparent, cost-efficient, and model-agnostic verification pipeline that treats every assertion as a hypothesis to be tested.

Unlike generic fact-checking tools, VETO is purpose-built for scientific and technical domains, where nuance, citation integrity, and multi-source triangulation are essential.

Core Capabilities

  • Cost Pyramid: intelligent claim triage (SKIP → CITATION_ONLY → STANDARD → CRITICAL) routes 90% of claims through lightweight verification, reserving expensive multi-model deliberation for high-stakes assertions only.
  • Adaptive Jury: starts with 3 judges and escalates on disagreement — not 9 models by default. This keeps costs predictable while maintaining rigorous consensus on contested claims.
  • Source Fabric: hierarchical retrieval engine capable of searching across 10,000+ sources with deduplication and semantic ranking.
  • Convergence Loop: iterative deliberation with 5 circuit breakers prevents runaway costs and infinite loops.

Status

In Development
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