eval.qa

We're building a modular, human-plus-machine evaluation standard to define, score, and improve AI behavior, across outputs, agents, and workflows.

eval.qa is not an internal tool. It is a public benchmark and open specification designed to help the entire ecosystem measure trust.

eval.qa is stewarded by Alt.QA with public input through an open RFC process.

Unlike training-centric approaches, eval.qa starts from real-world tasks, human judgment, and system behavior, not synthetic prompts alone.

Derived from live evaluation pipelines used within Alt.QA.

Coming Soon
  • eval.qa schema (YAML-based)
  • Reference benchmark model
  • Canonical scoring framework
  • Open-source roadmap

The Eval Army

The Eval Army is a distributed corps of evaluators defining what "good" AI behavior actually looks like.

Output Evaluation

Assess AI-generated content across real tasks. Score accuracy, coherence, helpfulness, and safety using standardized eval.qa templates.

Failure Mode Discovery

Identify hallucinations, bias, inconsistencies, and edge cases that automated systems miss. Surface the problems that benchmarks don't catch.

Benchmark Piloting

Test and refine early benchmark datasets. Validate evaluation models. Provide the structured human judgment that grounds the standard.

No Prior QA Required

Clear thinking and attention to detail matter more than credentials or background.

All evaluators are calibrated using standardized rubrics and inter-rater reliability checks.

Evaluation Is the Next AI Frontier

Everyone is training models.
Few are verifying them.

As AI systems become agentic, autonomous, and embedded in decision-making, evaluation can no longer be an afterthought.

We believe evaluation is infrastructure, as foundational as training, deployment, or monitoring.

Alt.QA is the QA layer for intelligent systems.
eval.qa is the test bench and scoreboard for trust.

What's Coming

Phase 1
Initial schema release

YAML-based schema for defining evaluation criteria and scoring rubrics.

Phase 2
Reference benchmark

Canonical model for testing and validating eval.qa implementations.

Phase 3
First public validation cycle

Integration with task definition standards for workflow evaluation.

Phase 4
Open RFC process

Alpha, Beta, Public, structured refinement of the standard.

eval.qa is part of Alt.QA, the quality and truth infrastructure of TAO.ai and The Work Company.