What is Teammately?
Teammately is correctness infrastructure for teams building specialist AI. It turns in-house experts' judgment into an operating system for designing benchmark coverage, making correctness explicit, constructing challenging cases, evaluating candidate behavior, and deciding what to improve next. AI agents prepare and connect the work so scarce expert attention is spent on consequential judgment rather than manual organization.
Definition
The system has five connected capabilities. Coverage Engineering defines the behavior space a benchmark must represent. Correctness Elicitation turns tacit preferences, exceptions, and disagreements into policies, applicability conditions, and binary rubrics. Weave constructs cases, response variants, case materials, and—where supported—worlds from that structure. Trialground evaluates Harnesses and weights against benchmark Cases and preserves responses and Rubric results. Coevolve explores candidate improvements and keeps every retained direction tied to current benchmark evidence.
These capability names explain how the system works. Procedures use the labels visible in the product, such as Correctness Governance, Agent Setup, Benchmark Datasets, Coverage Management, Expert Contributions, Benchmark Evaluations, and Improve.
Decision checkpoint
| If the team needs... | Capability | Product surfaces to open |
|---|---|---|
| A deliberate map of important behavior | Coverage Engineering | Coverage Facets and Coverage Management |
| Reusable standards grounded in specialist judgment | Correctness Elicitation | Correctness Governance and Expert Contributions |
| Challenging cases and supporting materials | Weave | Assets, Benchmark Datasets, Case Construction Patterns, and Case Foundry |
| Repeatable evidence about candidate behavior | Trialground | Harnesses and Benchmark Evaluations |
| Evidence-backed candidate improvement | Coevolve | Improve and Improvement Sessions |
Why teams use it
A benchmark score cannot define correctness on its own. Specialist systems depend on domain rules, exceptions, source authority, interaction patterns, and consequences that generic criteria do not capture. Teammately gives experts and AI engineers a shared artifact graph: an expert contribution can inform a policy, a policy can produce a rubric, a coverage gap can motivate a case, a case can expose a harness weakness, and an evaluation can become the starting evidence for an Improvement Session.
This reuse is the practical meaning of scaling expert judgment. Teammately prepares coverage structure, candidate cases, possible standards, and unresolved questions before asking an expert. The expert's response remains attributable and can be materialized into governed artifacts instead of disappearing into meeting notes.
Product scope
Project-level foundations hold reusable knowledge and assets: Correctness Governance, Coverage Facets, Assets, Agent Setup, and Project Settings. Benchmark workspaces bind those foundations to a concrete evaluation program through Benchmark Datasets, Coverage Management, Expert Contributions, Benchmark Evaluations, and Improve.
Teammately preserves correctness evidence and makes the next engineering question inspectable. Customer teams remain responsible for downstream product, governance, deployment, and operational choices.
Worked example
Grounded enterprise search
Coverage Engineering identifies conflicting-current-source questions as an important behavior slice. Correctness Elicitation records the expert rule that material claims must cite the controlling source or state uncertainty. Weave creates cases with current and superseded documents. Trialground evaluates a retrieval harness and exposes unsupported blends of the two sources. Coevolve starts from those failures, tests a source-selection change, and retains only candidates supported by evaluation evidence.
Related workflows
Related reference pages
Source confidence
Doctrine-backed: this page follows the current public top-page story and the approved product-to-UI mapping. Linked code-backed pages define exact routes, states, and controls.