HexaClaw
Corporate travel operations · policy-scoped execution

The Agentic Organization
for corporate travel.

HexaClaw orchestrates corporate travel agents across country compliance, account growth, implementation vetting, data reconciliation, and policy approvals—with cited evidence and human checkpoints on every material action.

Launch the demoSee a day in the lifeNo install · six mocked travel scenarios · scripted execution flows
6
travel agent scenarios
4
country rollouts tracked
96.7%
records auto-matched
21
vetting answers assessed
Section 02 · day in the life

A day in the life of a global corporate travel program.

Six workflows, one continuous fabric of agents. Click any hour to see how compliance, account, implementation, and operations teams stay coordinated.

All scenarios →

June close: reconcile booking, card, and expense data

The fleet matches 96.7% of 1,284 records, normalizes low-risk differences, stages nine duplicate corrections, and routes one material hotel exception with the full evidence pack.

Record MatcherCorrection AgentException AnalystCase Router
Artifact produced
REC-3918 · supplier dispute staged
Every agent action is policy-scoped via MCP and posted with a citation trail—humans approve, agents act.
Section 03 · agentic frameworks

The agentic framework behind modern travel operations.

Corporate travel teams need more than a general-purpose model. They need coordinated agents, controlled system access, country-aware policies, traceable evidence, and human approval for material decisions.

NemoClaw
NVIDIA Nemotron-native agents
Strengths
  • Strong analysis across long policy and operational documents
  • Native streaming and tool use
  • High-throughput classification and extraction
Enterprise gaps
  • ·Limited multi-agent coordination primitives
  • ·Enterprise operations tooling still maturing
Best at: deep analysis of policies, questionnaires, and country rules.
OpenClaw
Open framework, swap-any-model
Strengths
  • Model-agnostic across hosted and local models
  • Large plugin and MCP ecosystem
  • Flexible integration with travel operations systems
Enterprise gaps
  • ·Governance and approval controls must be assembled
  • ·Domain policies are not built in
Best at: rapid travel-operations prototypes and integration-heavy workflows.
Claude Magnetic Services
Anthropic managed multi-agent
Strengths
  • Managed multi-agent orchestration
  • High-quality reasoning and tool-use accuracy
  • Careful handling of complex exception decisions
Enterprise gaps
  • ·Hosted only—no on-prem option
  • ·Premium pricing for high-volume operations
Best at: high-trust vetting, policy explanations, and approval summaries.
Section 04 · our approach

HexaClaw is thecontrol plane for agentsin corporate travel.

HexaClaw coordinates specialized agents across corporate travel workflows. It provides the policy, confidence, approval, and evidentiary layer teams need to automate repetitive work without losing control of client, financial, or compliance decisions.

The HexaClaw stack
UsersImplementation · Account · Operations · Travel Manager
Control planeHexaClaw—policies, confidence, audit, evidence
AgentsCompliance · Growth · Vetting · Reconciliation · Policy
MCPOIP · Salesforce · Tools Catalog · Travel Policy · Approvals
DataCountry Rules · Bookings · Expenses · Cards · Documents
Declared agent roles

Each travel agent has a defined purpose, source scope, confidence contract, and stop rules for missing or conflicting evidence.

Policy-scoped MCP

OIP, Salesforce, catalog, booking, expense, payment, and approval access is declared per agent. External writes remain staged.

Country-aware controls

Recommendations pass through country compliance, data-residency, licensing, client-policy, and deliverability checks before publication.

Evidence on everything

Every answer points to the synthetic rule, tool record, project, policy, transaction, or historical questionnaire that supports it.

Humans on the loop

Low-confidence vetting, policy exceptions, financial adjustments, catalog changes, outreach, and bookings require named approval.

Operationally observable

Confidence, match quality, false corrections, pending owners, approval state, and every mocked tool decision remain visible and auditable.