Work securely with case data
Run AI on hardware you control and encrypt new case notes and chats end to end.
Insurance
Move claims forward with private AI
Let AI prepare claim files and underwriting submissions on your own machines. Your team checks the evidence and makes the call.
Automate routine case prep
Have AI pull facts from documents and flag missing evidence before a handler picks up the case.
Keep decisions with your team
Share the same case context with approved colleagues and see who reviewed and approved the work.
Keep control from intake to decision
Start with one process where an agent can prepare the file and a person can check the evidence.
Keep sensitive case data under your control
Run the model on your own machines with Edge AI. With Encrypted data enabled, new supported case notes and documents are encrypted before upload and can be opened by enrolled teammates.
Reuse your intake process on every case
Set up a workflow to extract the details your team needs, flag gaps, and hand the file to the right reviewer. Run the same steps on the next claim or submission.
Give handlers an assistant that knows your policies
Give your assistant approved policy material so handlers can find answers and draft replies. Bring a fine-tuned model, or talk with us about one we can provide or tune together for the documents you handle.
See how each decision was made
Choose the tools and skills agents can use, then require a named handler or underwriter to approve the work. Keep a record of what the AI did and what the reviewer decided.
Start with a case your team knows
Bring a sample document and the checks your team already makes.
Claims intake
Pull key facts from a claim pack and flag missing evidence for a handler to check.
Underwriting review
Prepare a summary of a submission so an underwriter can check the source and make the decision.
Policy service
Draft a response from approved policy material for a team member to review before it goes out.
See how it could work on a claim
Bring a sample claim or submission. We’ll discuss the model, where it runs, and who reviews the output.