Why we are building this
Expertise should become a development capability your team can keep using.
A model update should not erase the work of understanding what good behavior means. Teammately connects AI-driven elicitation, rubrics, coverage, synthesis, and experiments so each iteration can build on the judgment already established.
Expertise is present. The specification is incomplete.
Enterprises already hold the knowledge their AI needs, distributed across people, policies, and experience. The difficult work is uncovering the relevant judgment, preserving its conditions, and making it usable in development.
Read our approachAgents undertake the work around expert judgment.
Preparation, adaptive elicitation, interpretation, and further investigation belong together. Automating those tasks lets expert participation contribute to rubrics, coverage, and experiments without requiring every connection to be organized manually.
Explore elicitationA benchmark must explain what it stands for.
The situations and proportions in a dataset shape its conclusions. We treat coverage across ontologies as an engineering responsibility, informed by product objectives, expert experience, and changing usage.
Explore coverageBetter behavior through harnesses and weights.
Some improvements change how a harness reasons and acts with a model. Others depend on what the weights learn. Shared expert standards and coverage should inform both, with evidence that makes each development decision assessable.
Understand the platformExperts establish judgment. Teams choose what to adopt.
Agents can prepare a question or propose a criterion, but your organization decides which standards represent its intent. Engineers retain responsibility for the changes they carry into production.
Explore Rubrics and PoliciesThe value has to show up in development.
We want expert effort to resolve useful distinctions and support improvements that hold under examination. That means looking at preparation and review effort, coverage, candidate behavior, and regressions together.
Read the research questions