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Travel & shoppingInvestigate and reportPersonal

Multi-stop trip planner

Build and compare complete route options instead of optimizing each booking in isolation.

What this workflow does

Build and compare complete route options instead of optimizing each booking in isolation. It separates observed facts from inference, surfaces conflicting evidence, and delivers a review-ready finding set instead of an opaque answer.

What you gain

Fewer impossible connections and hidden total costs.

What the AI agent changes

How this worked before

Traditional automation could collect records, but a person still had to compare sources, resolve conflicts, and write the conclusion.

What the AI agent changes

The agent can plan a search, inspect multiple sources, distinguish facts from inference, and return a cited report.

Agent trigger

The user provides destinations, dates, constraints, and budget.

Inputs

  • Process context: transport, stays, transfer time, entry rules, preferences, and total cost
  • Approved policies, ownership, and exception rules

Agent flow

  1. 1

    Collect source material from the approved systems and record its timestamp.

  2. 2

    Cross-check conflicting signals and separate facts from inference.

  3. 3

    Prepare ranked complete itineraries with trade-offs and source links with citations, unknowns, and confidence.

  4. 4

    Deliver the approved report and preserve its evidence set.

Human decisions

After step 3

The accountable process owner approves ranked complete itineraries with trade-offs and source links.

Outcome

  • User-approved itinerary ready for booking
  • Evidence, exceptions, and audit trail

Guardrails

  • Label inference separately from observed facts.
  • Do not close the investigation while required sources are unavailable.

Risks and mitigations

Missing or stale evidence can produce a confident but incomplete finding.

Show source coverage, conflicts, timestamps, and unanswered questions.

Sources and evidence