Teammately
Teammately provides AI Alignment Infrastructure, a platform where AI agents elicit expert judgment and translate it into rubrics, policies, and benchmark coverage for enterprise AI development. Its agent, Lemon, conducts adaptive expert sessions and synthesizes benchmark cases, while Trialground provides managed harness execution and rubric evaluation. The platform is designed for teams that need to bring domain expertise into model training, evaluation, and alignment workflows.
- Artificial Intelligence
- AI Agents
- Developer Tools
- Software Only
- Enterprise Software
Funding
Raised to date
$400KRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Enterprises often hold deep domain expertise but struggle to express that knowledge in a form AI development can use. Expert judgment is distributed across people and teams, preferences depend on context, and exceptions only surface when someone encounters a decision that feels wrong. Manually preparing, interpreting, and following through on expert contributions makes it difficult to scale expert participation in AI development.
Solution
Teammately provides AI Alignment Infrastructure, a platform where AI agents elicit expert judgment and translate it into rubrics, policies, and benchmark coverage. The company's AI agent, Lemon, prepares and adapts expert sessions to uncover the criteria, exceptions, and preferences behind a judgment. Lemon Elicit conducts adaptive case reviews, forms, chats, and voice interviews, developing findings into proposed standards that experts can inspect and refine. Lemon Weave synthesizes benchmark cases, worlds, and targeted training data from ontology tuples, following coverage designs informed by expert experience. Trialground provides managed harness execution and rubric evaluation so teams can assess candidate behavior against established standards. The platform also includes Lemon Code and Lemon Goal, which help engineers develop and optimize harness prototypes in a sandbox environment.
Target Audience
Primary customers are enterprise AI development teams that need to bring domain expertise into model training, evaluation, and alignment workflows. This includes organizations building AI systems for regulated or specialized domains where expert judgment is critical to defining correct behavior.
Features
- Lemon Elicit: adaptive expert elicitation through case reviews, pairwise and listwise comparisons, trajectory assessments, forms, chat, and voice interviews, with AI-driven session preparation and interpretation
- Rubrics and policies: structured benchmark criteria with explicit scope, precedence, and conflict detection so teams can govern shared standards across the enterprise
- Coverage engineering: ontology-driven benchmark design that makes intended situations and proportions explicit, guiding case construction and world synthesis
- Lemon Weave: synthesis of cases, worlds, and targeted training data from ontology tuples, including executable environments with tools and state for agent tasks
- Trialground: managed harness execution and rubric evaluation for offline experiments, with evidence that separates harness problems, training data gaps, and unresolved expert preferences
- Lemon Code and Lemon Goal: AI agents that develop and optimize harness prototypes in a sandbox, giving engineers tested ideas to carry forward
- Kestel and Bower: fine-tuned open-weight models for binary rubric evaluation and coverage-directed case synthesis respectively