INDUSTRY ARCHITECTURE / Travel & logistics

Travel & logistics architecture

A connected reference design spanning domain information, data engineering, AI services, agent execution, and governance.

DOMAIN DESIGN DECISION

The business context
shapes the architecture.

Events arrive from multiple carriers with inconsistent timestamps, status codes, and identifiers, making exception ownership difficult.

Normalize carrier status vocabularies, keep both event and ingestion time, and retain the source of every status transition.

Start with shipment monitoring rather than attempting to automate the whole industry at once. Define a bounded request, the evidence required to answer it, and the person accountable for accepting the result.

DATA → AI → AGENTIC AIDOMAIN CONTEXT: Shipment / Movement event / Booking / Service exception

Data architecture

01
Domain sources
Shipment events, booking records, carrier messages, service rules. Identify the system of record, owner, refresh rate, and approved purpose for each source.
02
Ingestion & contracts
Batch, change-data capture, events, and document intake as appropriate. Validate schema, identity keys, event time, and rejected records.
03
Storage & transformation
Separate raw evidence, validated records, and curated domain products. Preserve version history and reconciliation results.
04
Semantic serving
Shipment · Movement event · Booking · Service exception. Publish agreed definitions, access rules, and reusable interfaces for analytics and AI.

AI architecture

01
Approved information
Use curated domain products and approved documents. Preserve metadata, effective dates, and access scope.
02
Retrieval & features
Build permission-aware retrieval indexes or model features for the specific task. Test relevance and freshness independently.
03
Model & evaluation
Evaluate candidate methods on representative domain examples. Check groundedness, completeness, uncertainty, cost, and failure behavior.
04
Experience & feedback
Serve sourced drafts or scored signals through a review experience. Capture feedback without silently retraining or widening data access.

Agentic AI architecture

01
Task & identity
Record the initiating user, allowed purpose, task boundary, and completion criteria.
02
Reasoning & state
Shipment exception agent and Travel service agent. Keep task state, retrieved evidence, and unresolved questions traceable.
03
Scoped enterprise tools
Expose typed, permission-checked search, lookup, and draft tools. Validate arguments and handle retry or timeout safely.
04
Approval & audit
Carrier commitments, route changes, rebooking, and refunds require approval. Record tool calls, reviewer decisions, and the accepted result under an agreed retention policy.

Shared governance & operationsOwnership · classification · lineage · access · quality · retention · evaluation · observability · incident response · cost management

Implementation decisions
to resolve before build.

Data lifecycle

Identify authoritative records, history requirements, update frequency, retention, and the consequences of stale information. Preserve source event time and ingestion time where ordering matters.

Serving & integration

Choose batch, event, API, or document access based on workload needs. Separate read-only retrieval from tools that alter enterprise records. Define timeouts, retries, and recovery ownership.

Operational evidence

Measure event ordering quality, exception identification, evidence traceability, and recovery-option review time. Keep versioned evaluation cases, end-to-end traces, and reviewer feedback so changes can be assessed against an agreed baseline.

CASE

A shipment exception investigation workspace

See the proposed architecture applied to a focused workflow.

Journey & shipment control workspace

Bring movement events and operational exceptions into one review flow.