HUMANClaims intake agent
Capture claim details, check missing fields, and prepare first-pass intake summaries.
AI Agents for Insurance Operations
We help insurance teams turn high-friction workflows into working agents that connect tools, data, approvals, and business logic.
In 30 minutes, we identify 3 to 5 agent opportunities, score them by value and complexity, and recommend the best first workflow to deploy.
Built for CIOs, Claims Leaders, Underwriting Leaders, and COOs
The problem: Insurance teams have AI ideas, but production adoption is hard
Claims cycle time, underwriting consistency, and document-heavy decisions create strong demand for agents that work inside existing policy and claims systems.
Insurance AI ideas stall when they need document extraction, policy rules, fraud checks, approvals, and auditability. The sprint starts with one scoped workflow and leaves a runtime your team controls.
Use cases
Workflows we turn into agents
Underwriting packet agent
Assemble risk packets, summarize applicant context, and flag gaps for underwriters.
Policy servicing agent
Handle routine servicing requests with policy context and human approval for exceptions.
Fraud triage agent
Score and summarize fraud signals, then route suspicious cases to investigators.
Named offer
How the AI Agent Deployment Sprint works
A hands-on FDE-style engagement that turns one high-value business workflow into a working agentic workflow in 30 days.
- 01Map the target workflow
- 02Identify the agents, tools, approvals, and data sources
- 03Build and test the first working agent
- 04Connect the agent to your stack
- 05Add evaluation, logging, and human review
- 06Train the team to operate and extend it
- 07Leave behind the runtime so the workflow keeps running
What your team owns after the sprint
You keep the agents, the workflow design, and the operating model. Everything we build can run on MonkeyBot, a company-controlled agent runtime for tools, skills, durable memory, approvals, and shared workflows. Your agents do not disappear when the engagement ends.
AEO
Frequently asked questions
What is an AI agent for insurance?
An AI agent for insurance is a workflow system that can use approved tools, retrieve business context, follow rules, involve humans when needed, and complete a defined business task.
How is this different from a chatbot?
A chatbot answers questions. An agent completes a workflow by using data, tools, approvals, and business logic.
What workflow should we start with?
Start with claims intake or underwriting packet assembly—document-heavy, repeatable workflows where adjusters or underwriters remain in the approval loop.
Do we need to replace existing systems?
No. The first deployment should connect to your existing systems rather than replace them.
How do you reduce risk?
Use scoped permissions, human approvals, evaluation tests, logging, fallback paths, and clear ownership before expanding automation.
Next step
Start with one workflow
Bring us one painful workflow. We will help you decide whether it should become an agent, what it would take to implement, and what business outcome it should drive.
Book an Insurance Agent Review