Understand what experts value and why
Lemon uncovers the reasoning, tastes, and trade-offs behind expert decisions, including when a different choice is appropriate. Experts review and correct how Lemon captures their thinking.
AI Alignment Infrastructure
Make AI alignmentan in-house capability
An agent-powered platform that puts your enterprise'sexpert judgment to work shaping how AI behaves and improves.
Aligning AI with your enterprise's context and taste can build a moat against frontier models, but sustaining it requires continuous effort, and relying on external teams for every improvement puts that advantage at risk.
Teammately equips your experts and AI engineers to align and improve AI themselves, at scale. For example, an expert explains a return exception. Lemon proposes criteria for review and prepares contrasting Cases. Trialground compares candidate behavior, and your team decides what to adopt.
More impact per human judgment
Build rubrics and enterprise alignment
Lemon develops rubrics grounded in expert reasoning, preferences, and the conditions that shape a judgment. Working with experts on their own schedules, it mediates differing views, deepens discussions across teams, and surfaces overlooked decisions about AI behavior.
Generate cases for the situations that matter
Lemon synthesizes inputs and tasks around situations worth exploring with experts. Coverage guides the combinations and controlled variations, helping clarify distinctions that even extensive production logs may leave unresolved.
Improve harnesses and model weights
Investigate where your agent falls short on your own benchmarks through managed sandbox trials and rubric evaluation. Lemon helps develop harness changes to guide your coding agents and expand scarce expert input into datasets for targeted weights post-training.
“We have the technical expertise to improve AI, but how we improve it depends on business context and domain knowledge. Bringing that knowledge into the development process is a major challenge.”
Whitepaper: AI Alignment Infrastructure
A practical guide to connecting expert judgment, coverage, and AI improvement, with worked examples, team responsibilities, and guidance for a first assignment.
Read the whitepaper
Meet Lemon,
your AI agent for alignment.
Lemon undertakes the preparation, inquiry, construction, and investigation behind AI alignment. Your team reviews its proposals, examines the results, and decides what moves forward.
Get to know LemonLemon at work
Preparing coverage
Proposed dimensions and ontologies, with the reasoning behind them.
Learning from experts
Focused follow-ups and proposed rubrics for expert review.
Pursuing benchmark goals
Candidate harnesses and the evaluation results behind them.
Powerful AI is within everyone’s reach. Build your advantage beyond the model. Teammately makes your expertise the difference.
Specialty Retailers
When relevance alone does not make a good recommendation.
A relevant product may still be the wrong recommendation. Customer intent, assortment priorities, availability, and acceptable alternatives change what an experienced merchant would choose.
“What I see in Teammately is a way to turn our experts’ knowledge into a lasting capability for AI development. It goes beyond collecting a dataset once—it gives teams the tools to keep building and improving their own.”
Business Software Companies
Acceptance standards for customer-specific AI work
Maintain acceptance standards across customer workflows as software changes. Assess product AI and internal customer-insight analysis, then develop better candidates.
“Teams need a way to see how far their evaluation dataset diverges from actual real-world usage—and when they need to update their test cases.”
Travel Booking Platforms
Service judgment when standard booking flows stop resolving cases
Develop post-booking AI around specialist service judgment, supplier responsibilities, and useful handoffs. Construct exception coverage and assess existing responses.
“A real product needs its own definition of success. Human reviewers have to explain what’s good or bad—and why. Then you have to check whether the AI judge agrees.”
Airlines
Resolving complex passenger cases when disruption changes the options.
Passenger support combines fare rules, connection dependencies, limited rebooking options, and service recovery. Capture how experienced teams weigh those constraints, then test whether agents can reach feasible resolutions, explain trade-offs, and recognize when an exception needs expert attention.
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Vehicle & Equipment Manufacturers
Owner-support quality across product variants
Develop owner-facing AI around useful interpretation, clarification, and next-step guidance. Construct multimodal assessment cases across vehicle and product variants.
Read solution“Teammately is addressing many of the problems we’re trying to solve. I can see how our organization could benefit.”
Why we build
Machine intelligence is scaling fast. Humanity must stay in control.
We’re maximizing alignment per human effort by augmenting human judgment.
Explore our research directions
Where Teammately fits.
What starting involves.
How does Teammately compare with Scale, Surge, and Mercor?
Scale, Surge, and Mercor help teams build expert-informed datasets, evaluations, and model improvement programs. Their offerings combine expert workforces, technology, and support for designing and executing these programs.
Teammately is an agent-driven software platform for making your organization’s expertise part of how your AI learns and improves. Lemon prepares materials and questions, adapts as experts respond, and develops their reasoning into proposed criteria and benchmark coverage. Your team reviews those proposals with the linked expert contributions and Cases, revises them, and decides which standards to adopt.
An expert's clarification can guide related benchmark Cases, training examples, and Harness experiments. Shared Policies retain where the standard applies, while further Contributions address changes and unresolved questions. Your team develops an ongoing capability to maintain and apply its expertise throughout AI development.
How does Teammately fit alongside LangSmith, Braintrust, or Langfuse?
Teammately can work alongside your tracing, evaluation, and development tools. It gives your AI team a system for organizing expert elicitation, designing benchmark representation, and connecting that work to offline training and optimization.
AI observability and evaluation platforms such as LangSmith, Braintrust, and Langfuse already help teams connect production observation with evaluation and dataset development. Teammately helps identify where changing user behavior diverges from what your benchmark represents. Actual usage informs the case mix; expert standards and coverage objectives guide which conditions, combinations, and proportions to test. Include rare, consequential situations even when recent traffic contains none.
Use expert review and related Cases to clarify the criteria and the importance of each case class. Stable benchmark versions give teams a shared basis for comparing improvements as they refine coverage and develop candidates. Data exchange remains scoped to your existing setup.
How does Teammately handle ambiguous or conflicting expert judgments?
Different judgments can reflect missing context, competing priorities, or different expectations about where a rule applies. Teammately’s agents investigate those distinctions and prepare focused questions, comparisons, or reviews to clarify them.
Experts and accountable owners decide what should become a shared standard, where an exception applies, and what remains unresolved.
Do we retain ownership of what we build with Teammately?
Your expertise, standards, benchmarks, and development assets remain yours.
We don’t use your workspace data to train shared models or optimize harnesses for other workspaces without your permission. See our Privacy Policy and Trust Center for more on data handling.
Who operates Teammately, and where do we start?
Teammately provides a development workspace for your AI team and a dedicated participation interface for domain experts. Your AI team works with agents to direct elicitation, review standards and coverage, and evaluate candidate improvements. Engineers decide which development changes to adopt.
Experts contribute through prepared reviews, comparisons, forms, chat, and voice interviews. Agents handle the preparation, adaptive elicitation, and interpretation, so experts can focus on the judgments and distinctions that need their expertise.
Bring a development objective and the materials you already have. You can begin with a new initiative, a training requirement, or an existing system; a finished benchmark is not required.
Your expertise stays yours.
We do not use your workspace data to train shared models without your express written agreement. Control access by workspace and project. Private connectivity is available for data ingestion and model inference.
Our security program follows the SOC 2 Security criteria, with controls assessed internally. Independent SOC 2 Type II audit in progress.
Explore our Trust Center
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Build AI that meets your standards.
Tell us about the challenges you’re facing with your AI. We’ll show you how Teammately can help.