Agents that understand the work.
Blackrock AI agents are designed around specific travel jobs, with access to the context and controls required to be useful inside real operations.
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CRM Agent
Know the account before the call starts.
The CRM Agent can bring together recent commercial activity and available customer context to help teams prepare and follow up faster.
Potential actions:
- summarise account history
- summarise an opportunity
- identify next actions
- draft follow-up messages
- highlight inactive opportunities
- create or suggest tasks
- prepare meeting context
Operations Agent
Find exceptions before they become incidents.
The Operations Agent can review workflow states and operational signals to surface items that need human attention.
Potential actions:
- flag incomplete processes
- summarise supplier errors
- identify stale tasks
- surface unusual booking states
- group similar incidents
- prepare an operational summary
Customer Agent
Faster answers with the booking context attached.
Assist support teams and, where appropriate, travellers or agents with questions related to the platform and booking journey.
Potential actions:
- retrieve booking context
- explain status
- retrieve relevant policy or knowledge
- draft responses
- support English and Arabic workflows
- escalate when confidence or permissions are insufficient
Intelligence Agent
Ask the operation a question.
Allow authorised teams to explore operational and commercial data through natural-language queries and generated summaries.
Examples:
- Which clients grew most this month?
- Which suppliers are timing out most often?
- Which open opportunities have had no activity?
- What are today's highest-priority operational issues?
Human control is a feature.
Agent permissions should reflect user permissions. High-impact actions can require explicit confirmation. Sensitive data access should be scoped. Agent activity should be logged where appropriate.
Start with the workflow, not the model.
We begin by identifying the repetitive decision or information problem, then design the agent around the data, tools and controls required to solve it.
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