Project 02 In development
AI Evaluation Framework
An open framework for evaluating LLM outputs against domain-specific quality criteria. Designed to address the threshold problem: what does 'good enough' mean for high-stakes professional work?
PythonLLM eval
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.