Go back

Resources

Dec 13, 2025

Using Rubric Science to Solve the AI Trust Gap

The #1 barrier to enterprise AI adoption is "hallucination." How can a FinTech or Healthcare firm trust an autonomous system with high-stakes data?

long orb
long orb
long orb

The greatest barrier to AI adoption isn't power; it’s trust. Current LLMs are probabilistic—they predict the next likely word, not the next logical truth. This leads to "hallucinations" that are unacceptable in regulated industries. The solution is Rubric Science.

The Validation Layer Rubric Science is our methodology for "Reasoning Alignment." Instead of letting a model generate a response in a vacuum, we pass the query through a multi-stage validation engine:

  1. Contextual Anchoring: Forcing the model to retrieve only from "Auditable Ground Truth" (your internal data).

  2. Logic Extraction: Breaking down the answer into a "Chain of Thought" (CoT) that can be inspected.

  3. Rubric Audit: Testing the CoT against pre-defined industry constraints and compliance rules.

If the model cannot prove its answer through the rubric, the output is rejected. We are moving the industry from "Experimental AI" to Production-Ready Logic.