Start with real work
We begin with the workflows, tools, constraints, and decisions an AI system needs to handle. The task defines the expertise we bring in.
About Alpheva
We bring expert judgment into AI development. We find where models and agents fall short, then build the data, environments, and evaluations that help them improve.
Why we exist
Real work demands more than a correct response. It takes judgment: knowing which constraints matter, which tool to use, when to question an assumption, and how to recover when something goes wrong.
Alpheva makes that expertise useful to AI. We work with specialists to evaluate model behavior, capture how complex work gets done, and turn what we learn into the next round of improvement.
People behind the work
Our work brings together AI research, data operations, engineering, and professional judgment. Domain experts define what good work looks like; researchers and engineers turn that knowledge into systems models can learn from.
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How we work
We begin with the workflows, tools, constraints, and decisions an AI system needs to handle. The task defines the expertise we bring in.
We capture assumptions, tradeoffs, revisions, and corrections alongside the final result. The path to a good answer matters.
We evaluate against professional standards and observable outcomes, so improvement means better performance on the work itself.
We turn failures into targeted training data, environments, and evaluations, then measure what changed.
Applied research
Evaluation and training belong in the same loop. The failures we find inform the data we build, and the models we improve face the standards that revealed those failures.
Explore how we put expert judgment, agent environments, and outcome-based training into practice.
Build with Alpheva
Tell us what your model or agent needs to do better. We’ll help identify the expertise, data, and evaluations it needs.
Talk to our team