Correctness changes with context
The right behavior depends on traveler intent and party, availability and timing, budget and tradeoffs, rules, risks, and changes. Generic scoring misses those interactions.
Solutions · Travel
Travel AI that understands the difference between possible and right
Make traveler intent, product knowledge, and service judgment part of the benchmark.
A good travel recommendation depends on preferences, companions, timing, budget, availability, and risk tolerance. Teammately helps teams test the combinations that generic evaluation misses.
The domain reality
Generic quality is not enough for consequential travel behavior.
The standard lives across specialist teams
Destination knowledge, Product and booking rules, Traveler service, Partner and disruption operations 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 travel path.
Priority workflows
Start where expert judgment materially changes the answer.
Trip discovery
Test recommendations against nuanced preferences, tradeoffs, seasonality, and suitability.
Itinerary planning
Evaluate feasibility, pacing, dependencies, and transparent constraint handling.
Booking copilots
Benchmark product comparison, rules, disclosures, and option selection.
In-trip service
Test changes and recovery behavior against live context and traveler priorities.
Correctness blueprint
Connect specialist judgment to the benchmark and the build.
Your experts define
- Destination knowledge
- Product and booking rules
- Traveler service
- Partner and disruption operations
The benchmark covers
- Traveler intent and party
- Availability and timing
- Budget and tradeoffs
- Rules, risks, and changes
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 traveler intent and party, availability and timing, budget and tradeoffs, rules, risks, and changes the benchmark must represent.
Correctness Elicitation
Turn judgment from destination knowledge, product and booking rules, traveler service, partner and disruption operations into policies, applicability conditions, and binary rubrics.
Weave
Create targeted travel 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 travel 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 makes travel expertise testable; live availability, safety information, and final booking actions must remain connected to authoritative systems.
Build a benchmark around how your travel experts actually judge quality.
Start with a consequential workflow and the specialists already accountable for it. Teammately turns their judgment into reusable development infrastructure.