Proof AI

A hiring platform built around job-specific work simulations designed to evaluate what candidates can actually do.

Hiring tools can find and filter candidates without showing how someone will actually perform in the role. I built Proof AI around a different idea: an assessment should reflect the way a company actually works. Instead of a generic test, Proof creates a job-specific work simulation from the role and the competencies a company wants to evaluate.

Proof turns a job opening into a structured evaluation. Companies define the role and what they care about, and Proof generates a work simulation around those expectations. Candidate work is scored against competency rubrics and turned into a report of strengths, weaknesses, and evidence, with an employer view for managing evaluations and comparing performance.

I developed Proof from the initial concept through the working application. I worked across product strategy, user experience, interface design, development, AI workflows, and the evaluation system behind the reports. A big part of that was using AI without turning candidate work into a black box, so a hiring team could review the evidence.

I built and tested Proof as an early-stage product, then reached out to hiring teams to see whether the problem and approach resonated beyond my own assumptions. That became one of the most useful parts of the project. Building a working product and building something companies are ready to adopt are two different challenges, and those conversations need to shape the product earlier.