The next generation of AI needs a new generation of evaluators.
AI systems are starting to do real work: writing code, using computers, operating tools, navigating workflows, answering domain-specific questions, and making decisions across complex tasks.
For these systems to improve, they need better evaluation. And better evaluation depends on people who can judge the work carefully, consistently, and with the right context.
Qualdrin finds, screens, and trains that talent.
We work with AI teams to build the human review layer behind frontier model evaluation: people who can inspect what a model was asked to do, follow the steps it took, test whether the workflow behaved correctly, and apply expert judgment where correctness matters.
We believe the future of evaluation is human-led and AI-assisted. Our team builds rubrics, structures review policies, and uses LLM evaluators to make review faster and more consistent, while keeping humans in the loop for judgment and final verification.
Our network includes 5,000+ subject matter experts, along with data quality operators, LLM analysts, prompt engineers, and traditional QA specialists who can be matched to the needs of each project.
Our work is grounded in real RL environment projects for frontier labs, where reviewers need to be accurate, consistent, and ready to contribute quickly.
Contact: faiz@qualdrin.com