AI Evaluation Framework

An open framework for evaluating LLM outputs against domain-specific quality criteria.

The problem it solves

Every enterprise AI project eventually hits the same wall: how good is good enough? The absence of rigorous evaluation frameworks isn’t a research problem — it’s a leadership problem. This framework provides structure for making that determination explicit.

Design principles

• Domain-specific criteria over generic benchmarks
• Human-in-the-loop calibration
• Longitudinal tracking as models and tasks evolve
• Exportable to common observability tooling

Status

In active development. Framework architecture is defined; implementation in progress.