Research a list of prospects

For an Excel list of hundreds of companies, each one's business, locations, and size are collected from its website into its row, with a priority for sales.

  • All industries
  • Sales
  • 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 trade shows and meetings, staff research each company's website one at a time and compile the results in a spreadsheet. Everyone researches differently, so results vary.

The workflow in Kitewell

  1. Open the Excel list of company names and URLs and run each rowAutomatic
  2. Collect business, locations, and headcount from each websiteWeb
  3. AI judges whether each company fits your target customerAI judgment
  4. Sales reviews low-confidence and high-priority companiesHuman task
  5. Write the results into each row of the list, and export a CSV for your sales systemAutomatic

What AI does

Judges industry, size, and fit with your target customer from the collected information, and keeps the text each judgment is based on.

Where people decide

Sales reviews companies with low confidence or high priority and decides the order of approach.

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 target customer can be defined in terms AI can judge
  • Whether the evidence behind each judgment convinces your sales team
  • Whether the output imports into your sales system

How the onboarding runs

  1. Week 1Requirements and success criteria
  2. Weeks 2 to 3Build
  3. Week 4Verify on production screens
  4. 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.

See how the onboarding runs and its terms

Frequently asked questions

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.

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.