MomentumEngine – Secure Agentic AI Research Platform
Overview
MomentumEngine is a secure agentic AI research platform designed to eliminate hallucination risk in AI-generated research summaries. It combines a deterministic ranking engine with LLM agents — so every claim is grounded in traceable, evidence-backed data before the model generates prose.
The Challenge
AI-generated research summaries are fast but unreliable: they hallucinate facts, cite non-existent sources, and give no way to trace a claim back to its origin. Building a trustworthy research assistant means you can't just prompt a model and hope — you need a verifiable trust architecture that separates what the model knows from what the data proves.
The Solution
Designed a 4-layer trust architecture: raw inputs are normalized into claims, claims are validated against canonical facts, and LLM agents only synthesize outputs after deterministic pre-processing has already ranked, scored, and verified the underlying data. An 8-factor ranking engine handles freshness scoring, anomaly detection, and source credibility weighting before any LLM touch. Agents then handle candidate comparison, explanation generation, and periodic review — constrained to the already-verified fact layer.
Tech Stack
Outcomes
- ▸83.4% setup accuracy in historical evaluation against ground-truth data
- ▸Zero uncited claims in governed outputs — every response traces to a canonical fact
- ▸4-layer trust architecture eliminates direct LLM access to unverified inputs
- ▸Freshness scoring and anomaly checks reduce stale-data hallucinations