Context and uncertainty change the standard
Population, setting, evidence, missing information, intended use, and user role can all change what useful and appropriate behavior looks like.
Solutions · Healthcare
Healthcare AI shaped by specialist intent
Let clinicians, scientists, quality leaders, and operators define what useful, appropriate, and safe behavior means in context.
Generic judges cannot represent every intended use, evidence condition, uncertainty boundary, and escalation rule. Teammately helps teams create deliberate behavioral benchmarks with the specialists who understand the work.
The domain reality
Generic quality is not enough for consequential healthcare behavior.
Safety includes what the system refuses or escalates
A benchmark must cover unsupported certainty, risky omissions, inappropriate scope, and the boundary between assistance and accountable review.
Evidence and workflows evolve
Scientific knowledge, organizational policy, clinical pathways, and operational constraints require a standard that can be updated without losing provenance.
Priority workflows
Start where expert judgment materially changes the answer.
Clinical and medical information assistants
Evaluate evidence use, uncertainty, contextual relevance, scope boundaries, and escalation for information-support workflows.
Scientific research copilots
Test synthesis, source fidelity, competing evidence, limitations, and specialist usefulness across research questions and documents.
Patient and member support
Benchmark clarity, empathy, policy application, safe boundaries, and routing across realistic questions and user circumstances.
Documentation and operations agents
Evaluate extraction, summarization, tool use, workflow actions, and exception handling with operational specialists in the loop.
Correctness blueprint
Connect specialist judgment to the benchmark and the build.
Your experts define
- Appropriate scope and evidence standards
- Risk, uncertainty, and omission boundaries
- Contextual exceptions and limitations
- When clarification or accountable escalation is required
The benchmark covers
- Population, setting, role, task, and intended use
- Evidence conditions and missing information
- Representative, ambiguous, and adverse cases
- Outputs, actions, trajectories, and escalation behavior
The team receives
- Expert-grounded applicability and rubrics
- Traceable cases and contextual artifacts
- Candidate evidence across model and harness changes
- A focused queue of unresolved specialist questions
One connected workflow
Five product capabilities, applied to one domain standard.
Coverage Engineering
Design representation across population, setting, role, intended use, evidence, uncertainty, consequence, and escalation.
Correctness Elicitation
Use high-information cases to turn specialist judgment, exceptions, and limitations into applicable policies and rubrics.
Weave
Create missing cases, response variants, documents, multimodal artifacts, and worlds from deliberate coverage needs.
Trialground
Run candidates against controlled cases and workflows while retaining complete response, action, trace, and rubric evidence.
Coevolve
Explore improvement directions and route uncovered safety, evidence, or applicability questions back to accountable specialists.
What good looks like
A development team that can improve behavior without losing domain intent.
Specialist intent survives implementation
The standard is explicit enough to follow models, prompts, agents, tools, and harness changes.
Risk is represented deliberately
Ambiguous, adverse, missing-information, and escalation cases are designed into coverage.
Uncertainty changes behavior
Teams can test whether systems clarify, qualify, abstain, and escalate under the right conditions.
Iteration remains inspectable
Cases, sources, expert decisions, runs, and rubric outcomes remain connected as the system evolves.
Teammately supports expert-grounded AI development and evaluation. It does not replace clinical validation, regulatory review, organizational governance, or accountable healthcare decision-making.
Build a benchmark around how your healthcare experts actually judge quality.
Start with a consequential workflow and the specialists already accountable for it. Teammately turns their judgment into reusable development infrastructure.