Register new products on retailers' systems
AI reads your product data and spec sheets and fills each retailer's registration screen or Excel template. Staff check unclear fields and approve.
- 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
Before a launch, makers and wholesalers give each retailer the JAN code, dimensions, case pack, ingredients, images, and more for buyer meetings and product setup. Even with the data in an industry database, the final hand-off to each retailer is still done one by one, re-entering the same details into registration screens and Excel templates whose fields and formats differ by retailer. Wholesalers sometimes do the registration on makers' behalf.
The workflow in Kitewell
- AI reads values from internal product data (Excel) and spec sheets (PDF) to match each retailer's fieldsAI judgment
- Staff check fields that are hard to map, such as units, case packs, and categoriesHuman task
- Fill each retailer's product registration screen or Excel template without submittingWeb
- Staff review the filled screens and templates and approve registrationApproval
- Submit the registration and write the date and result back to each row of the product listWeb
What AI does
Maps your product data to each retailer's fields, whose names and units differ. Fields that are hard to map are shown to staff with the part of the source document it relied on.
Where people decide
Staff check unclear mappings and the content before registration. Staff decide trading terms such as the launch date and price.
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 product data maps correctly to each retailer's fields
- Whether each retailer's terms allow automated operation of its registration screens
- Which items retailers can take from an industry database or product information platform instead
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
- If our products are in an industry database, is automation still needed?
- If a retailer takes product data from the database, use that first. A study commissioned by METI found that even with product data gathered in industry databases, the final hand-off to each retailer is still done individually. Automation covers that individual entry.
- 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.
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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.