Enter applications and book policies
From the agreed quote, enter the application in the insurer's agency system, book the policy, and update the ledger after the customer and staff confirm.
- Runs on your own PCs and servers
- Use Azure OpenAI, Amazon Bedrock, Google Vertex AI, or an in-house model
- Its engine is Descarty's open-source Dagu (GPL-3.0)
The problem today
After a quote is agreed, each insurer's steps continue: entering the application, confirming it with the customer, booking the policy, and recording it in the customer ledger. With insurers scaling back the clerical help their staff gave agencies, agencies now have to do work they used to leave to the insurer.
The workflow in Kitewell
- AI lists the items the application needs from the agreed quote and the customer ledger, and points out what is missingAI judgment
- Staff confirm the missing information and the application with the customerHuman task
- Enter the application in the insurer's agency system and save the confirmation screenWeb
- Staff review the confirmation screen and approve the applicationApproval
- Submit and book the policy, and record it in the customer ledgerWeb
What AI does
Compares the agreed quote with the customer ledger and shows which required items are missing and which have changed since the quote.
Where people decide
The customer confirms the application, and staff approve after reviewing the confirmation screen. AI never fills in items the customer must answer, such as declarations.
Prove Kitewell on your own systems
Try it free for 14 days on your own PC. To see it working first, ask for a 30-minute demo. There is also a one-month onboarding (¥500,000 before tax), where we build your first job together.
What to check when you try this work
- Whether your agency agreements and each insurer's system rules allow automated screen operation
- Where in each insurer's process the customer confirms or signs electronically
- Which steps carry the confirmation-screen check and the approval
How the onboarding runs
- Week 1Requirements and success criteria
- Weeks 2 to 3Build
- Week 4Verify on production screens
- Final dayReport
One-month onboarding
- Length
- One month
- Cost
- ¥500,000 (tax excluded). Your staff build, with the developer beside them
- If you go on to a license
- The onboarding fee is credited to the first year's contract
- Without the onboarding
- At Team scale, start on Team monthly (¥14,800 per computer a month, tax excluded), and cancel in any month
You can try it first on your own PC, in the free 14-day trial.
Frequently asked questions
- Does AI ever enter the customer's declarations?
- No. Items the customer must answer, such as declarations, are answered by the customer through the insurer's process. Kitewell enters only items from the agreed quote and the customer ledger.
- Do our documents and screens leave the company?
- Kitewell runs on your own PCs and servers, and Descarty never receives your business data. You choose the AI model: a cloud API, or an in-house or local model with an OpenAI-compatible API. With an in-house model, no data leaves the company. With a cloud model, what the AI reads is sent to the model's provider.
- What if the AI misreads something?
- A person checks what the AI produced before the work goes on. In a sheet, every value the AI reads shows the quote it came from, and rows below your confidence threshold go to a person. Reviewers can send work back with notes on what to fix, and who approved what is kept in the run history.
- What happens when a screen changes or a run stops?
- When a screen changes, the AI reads it again, relearns the step, and carries on. The relearned step is saved, and later runs repeat it. If a run still stops, ask the assistant right there, and it finds the cause and proposes a fix. A proposal is not saved until a person applies it.
- What happens to the RPA and systems we use today?
- Keep them. Kitewell operates screens the way a person does, so it works with systems that have no API. Move the robots that keep stopping and the work you gave up automating because it needs judgment, and leave fast, fixed processing in your current RPA.
- What does it cost?
- ¥14,800 per computer per month, or ¥148,000 per computer when paid yearly, before tax. A computer costs the same whether it builds or runs. You can try it free for 14 days. The one-month onboarding, where we build your first job together, is ¥500,000 before tax, credited to the first year if you go on.
Related use cases
Find expiring policies and send renewal notices
Collect expiring policies through the insurers' shared gateway or agency systems, and draft renewal notices showing what changed. Coverage changes are flagged.
Consolidate policy data from each insurer
Collect new, changed, and cancelled policies from each insurer into the CRM's customer register. AI suggests which records are the same customer; staff confirm.
Draft comparison explanations and records
When a multi-insurer agency recommends a product, AI drafts the quote comparison and the reason. Staff edit it before explaining it and keeping the record.
See this work in a demo
A 30-minute demo shows this workflow running. The 14-day free trial lets you check it on your own systems.