Correctness changes with context
The right behavior depends on journey and traveler context, live operational state, entitlements and constraints, recovery and escalation options. Generic scoring misses those interactions.
Solutions · Airlines
Airline AI that stays useful when operations stop being routine
Carry fare, service, and disruption judgment into every customer and operational agent.
The hardest airline moments combine live operational state, policy, customer needs, and constrained options. Teammately creates benchmarks for those interactions before they happen in production.
The domain reality
Generic quality is not enough for consequential airlines behavior.
The standard lives across specialist teams
Fare and ticketing rules, Guest service and recovery, Airport operations, Disruption management each hold part of the judgment the system needs to behave well.
Real work is full of exceptions
A benchmark must represent edge cases, uncertainty, conflicting goals, and escalation—not only the most common airlines path.
Priority workflows
Start where expert judgment materially changes the answer.
Travel assistants
Evaluate rebooking, alternatives, entitlements, and explanations against live constraints.
Disruption agents
Test behavior across cascading delays, cancellations, missed connections, and scarce capacity.
Airport copilots
Benchmark operational recommendations and handoffs in time-sensitive situations.
Customer recovery
Ensure offers and communication reflect policy, customer context, and service intent.
Correctness blueprint
Connect specialist judgment to the benchmark and the build.
Your experts define
- Fare and ticketing rules
- Guest service and recovery
- Airport operations
- Disruption management
The benchmark covers
- Journey and traveler context
- Live operational state
- Entitlements and constraints
- Recovery and escalation options
Your AI team receives
- A deliberate coverage map
- Explicit policies and binary rubrics
- Targeted cases, variants, and exceptions
- Inspectable evaluation and improvement evidence
One connected workflow
Five product capabilities, applied to one domain standard.
Coverage Engineering
Design the combinations of journey and traveler context, live operational state, entitlements and constraints, recovery and escalation options the benchmark must represent.
Correctness Elicitation
Turn judgment from fare and ticketing rules, guest service and recovery, airport operations, disruption management into policies, applicability conditions, and binary rubrics.
Weave
Create targeted airlines cases, variants, artifacts, and worlds from the coverage plan.
Trialground
Run candidate models and agents in controlled environments and preserve the behavior-level evidence.
Coevolve
Explore parallel improvement directions and return newly discovered gaps to the right specialists.
What good looks like
A development team that can improve behavior without losing domain intent.
Coverage you can defend
Know which airlines conditions, exceptions, and risks the benchmark represents—and which it does not.
Judgment that scales
Reuse every specialist decision across policies, rubrics, evaluation, and future cases.
Evidence for every iteration
Compare model, prompt, harness, and agent changes against the same domain-grounded standard.
A controlled learning loop
Route unresolved questions and newly discovered gaps back to accountable experts.
Teammately evaluates agent behavior against airline standards; safety-critical and operational control remains with authorized systems and personnel.
Build a benchmark around how your airlines experts actually judge quality.
Start with a consequential workflow and the specialists already accountable for it. Teammately turns their judgment into reusable development infrastructure.