Input signals
- claims requests or alerts
- claims operating data
- help desk
- SLA
Back to AI agents
Customer service
Claims Agent
It can understand requests, search knowledge, answer with context, summarize cases and escalate sensitive exceptions, focused on claims. It works with authorized system context, connected tools and verifiable evidence before closing or escalating a case.
Supports the team in claims: understands requests, checks sources, prepares recommendations and executes only actions allowed by permissions and policies.
Signals, actions and outputs
This model keeps the agent from being just a conversation: it defines what it reads, what it can execute and what it leaves ready for the team.
Connected tools
- SLA monitor
- human transfer
- knowledge search
- intent classifier
Agent actions
- Classifies the request within claims and determines urgency, owner and confidence level.
- Checks SLA monitor and human transfer before recommending or preparing an action.
- Prepares drafts, tasks, alerts or updates so the team can act faster.
- Hands off when confidence is low, there is financial impact, an external commitment, a policy exception or a decision requiring human approval.
Operating outputs
- actionable claims summary with cited sources
- recommendation with confidence, owner and next step
- evidence ready for review, audit or operational follow-up
How the agent operates
The cycle starts with context, applies rules, executes actions and ends with reviewable evidence.
01
Reads context
Checks authorized sources, messages, documents or process data.
02
Reasons with limits
Uses guardrails, thresholds and policies to prioritize and decide next steps.
03
Acts or escalates
Runs an automation, prepares an answer or assigns the case to an owner.
04
Leaves evidence
Stores summaries, decisions, errors, files and session traceability.
Operating governance
Guardrails
- Human approval for critical changes, sensitive external messages or financial impact.
- Role-limited access; every lookup and action is audited.
- Mandatory escalation when sources are missing, confidence is low or a policy exception is detected.
Channels
- web chat
- support portal
Human handoff
Hands off when confidence is low, there is financial impact, an external commitment, a policy exception or a decision requiring human approval.
Evidence
Each interaction can stay linked to session, execution, user, source consulted and proposed or executed action.
Applied real-world pattern
Based on real service-agent deployments that understand intent, search knowledge, execute self-service and transfer with context when needed.
help desk
knowledge base
CRM
chat and WhatsApp
Related agents
Customer service
Customer Service Agent
Supports the team in customer service: understands requests, checks sources, prepares recommendations and executes only actions allowed by permissions and policies.
View agentCustomer service
Support Agent
Supports the team in support: understands requests, checks sources, prepares recommendations and executes only actions allowed by permissions and policies.
View agentCustomer service
SLA Agent
Supports the team in SLA management: understands requests, checks sources, prepares recommendations and executes only actions allowed by permissions and policies.
View agentReview Claims Agent with a real process
We validate sources, permissions, available tools and escalation criteria before proposing the first deployment.