Insurance template
Claims intake
Agents read each claim and its attachments, then check the facts against the policy. Your adjusters review the cited evidence and make the decision in one claims queue.
From inbox to review
One claim, with the evidence kept together.
Read the attachments
The agents read the first notice, estimate and supporting documents. Each fact stays linked to the page it came from.
Check against the policy
The policy period, deductible and relevant clauses sit beside the reported facts. Missing information is flagged for follow-up.
Put it before an adjuster
The adjuster checks the evidence, asks for anything still missing and makes the decision. The queue keeps the review moving.
The app
The claim file beside the queue.
An adjuster can move from the reported loss to its source documents and the relevant policy clause. Missing evidence has a next step, and approval stays with a person.
Illustrative app. All companies, people and figures are sample data.
What it reads
- First notices from your claims inbox
- Claim forms and incident reports
- Photographs and repair estimates
- Policies, schedules and endorsements
What your team sees
- A queue of claims to review
- Facts cited to the claim documents
- Relevant policy clauses and deductibles
- Missing information to request
What you set
- The intake inbox and document sources
- Which facts to extract
- Who reviews each claim
- Which gaps require follow-up
Questions
What people ask about claims intake.
Can a person review the facts before they move on?
Yes. Review queues come with every agreement. A reviewer can see each extracted value beside its source passage and approve or edit it before it reaches another system.
Can we choose which facts it extracts?
Yes. You define the fields it pulls out, and each value comes back cited to its page.
Can you set up the intake process for us?
Yes. We can map your process, build the workflows and the app, and hand your team something ready to use.
Is our data used to train models?
No. Your documents and results are never used to train a model, and a data processing addendum backs that.
Can it run in our own environment?
Yes. Strive runs in our cloud, or in your own VPC on AWS, Google Cloud or Oracle Cloud, or on your own Kubernetes cluster.
Which document-heavy job would you hand over first?
Bring one process you want to improve and the information behind it. We build the first version with you in the session, so the first thing you see is your own work, running.
Contact SalesAn hour of your time and a process you know well. That's all it takes.