Trust Harness
Accuracy That Holds at Enterprise Scale
The Trust Harness ensures that every insight — whether delivered to an analyst, an executive, or an AI agent — is validated, explainable, and governed before it reaches anyone. No black boxes. No unverifiable outputs. Every answer earns trust.
WHY IT MATTERS
AI Accuracy Breaks at Enterprise Scale. The Trust Harness Fixed It.
Most AI tools work in controlled demos. But in production — with messy data, conflicting definitions, and thousands of users across domains — accuracy collapses. The Trust Harness is built to prevent this. It validates every answer against the Insights Context Graph, enforces governance policies automatically, and gives users full visibility into how each result was generated.
Accuracy & Validated of Results
Every answer is validated against the Insights Context Graph before delivery — verifying the right tables, joins, definitions, and rules were applied. Your team only acts on results the system can stand behind.
Full Explainability for Every Answer
No black boxes. Every result arrives with the SQL, lineage, and reasoning path that produced it — so users can verify, auditors can trace, and stakeholders can trust.
Reinforcement Learning to Improve Over Time
Accuracy compounds with use. Endorsements lock in validated patterns, corrections update the graph — so the system gets more accurate the longer you use it.
Enterprise-Grade Governance
Every answer is governed by default. Access controls are enforced automatically at query time across every source and every user — no separate governance layer to maintain.
KEY CAPABILITIES
How Every Answer Earns Trust
Reinforcement, Accuracy, and Validation
Every answer generated by Promethium passes through a multi-step validation pipeline before delivery. The Trust Harness checks results against the Insights Context Graph — verifying that the right tables, joins, definitions, and rules were applied. Anti-hallucination safeguards catch inconsistencies, and human reinforcement (endorsements, corrections, and flags from domain experts) continuously strengthens the system. The result: accuracy that doesn’t just hold in a demo — it holds in production, across domains, at scale.
Explainability and Lineage
Every answer includes its full reasoning chain: the SQL that was generated, the data sources that were queried, the joins and filters that were applied, and the business definitions and rules that shaped the result. Data lineage traces the path from source to answer — across every system the query touched. No black boxes. Users can verify, auditors can trace, and stakeholders can trust — because every result is fully transparent.
Fine-Grained Access Control
The Trust Harness enforces governance at query time — automatically. A modified Open Policy Agent (OPA) applies row-level, column-level, and policy-level security across every query, every source, and every user. Domain policies, role-based rules, and organizational constraints are enforced consistently — whether the query comes from an executive in a BI tool, an AI agent via MCP, or an analyst in Mantra. No separate governance layer to maintain. No gaps between policy and execution.
HOW IT WORKS
Validation and Accuracy for Enterprise AI at Scale
Every answer passes through a structured validation pipeline before it reaches any user or agent.
Here’s what happens between generation and delivery.
Validate Against the Context Graph
The Trust Harness checks every candidate answer against the Insights Context Graph — verifying that the right tables, joins, metric definitions, and business rules were applied. Structural errors are caught before the result goes further.
LLM-as-a-Judge
An independent LLM evaluates the answer for logical consistency, hallucination risk, and alignment with the original question — catching semantic errors that rule-based validation alone would miss.
Confidence Scores
Graph validation and LLM evaluation produce a confidence score for each result. High-confidence answers are delivered directly. Lower-confidence answers are flagged for manual review by a domain expert before reaching the business.
Full Explainability
Every answer is packaged with its full reasoning chain: the SQL generated, the sources queried, the definitions applied, and the rules enforced. Every result arrives with the evidence to verify it.
Reinforce and Compound
Subject matter experts endorse, correct, and flag answers. Endorsements lock in validated patterns. Corrections update the graph. Over time, confidence scores rise, fewer answers need manual review, and accuracy compounds across domains.
THE PROMETHIUM DIFFERENCE
Every Answer. Verified. Before It Reaches Anyone.
Validation, Not Just Generation
Most AI tools focus on generating answers. Promethium validates them. Every result is checked against the Insights Context Graph, tested for consistency, and verified before delivery. The gap between “generated” and “trusted” is where most platforms fail — the Trust Harness closes it.
Governance Built In, Not Bolted On
Access controls, domain policies, and compliance rules are enforced at query time — automatically. There’s no separate governance tool to configure, no manual review step that slows things down. Security is part of the answer pipeline, not an afterthought.
Accuracy That Compounds
Human reinforcement feeds back into the system with every interaction. Endorsements lock in validated patterns. Corrections update the graph. Promethium doesn’t just maintain accuracy — it improves it with every query across every domain.
