Who we are

FAHALWAYS builds expert-authored evaluations around real professional work. We help teams examine how AI models and agents retrieve evidence, reconcile conflicting information, use tools, and produce usable deliverables.

Selected demonstrations

The following examples are synthetic demonstrations of our approach, not client results or customer endorsements.

Business-document review: an assistant must reconcile invoices and project records, distinguish requests from approvals, and identify decisions that require human review. Explore the workflow and video.

Data-pipeline repair: a coding agent makes a failed job run again, but valid records disappear. The evaluation examines the resulting data and required behavior beyond the success message. Explore the technical example and video.

How we approach quality

We agree the workflow and acceptance criteria, develop the source materials and assignment, prepare reference outcomes, and review the scoring rubric. Checks examine whether the task is answerable from the supplied evidence and whether the criteria match the requested work. Reviewer materials remain separate from model-facing files.

Inspect the approach before commissioning work

A selected public preview shows a synthetic assignment, abbreviated source evidence, an example deliverable excerpt, and scoring categories. Complete cases, reference solutions, and detailed scoring materials are shared privately under agreed terms.

Review the three-case pilot · Request a relevant preview

Research and implementation

Explore commissioned evaluation research on agent judgment and evidence use, or consulting and implementation to turn findings into practical improvements.