Write job postings for each job board
From a client's job request, AI drafts postings in each job board's format. Staff check them, then publish through each board's official route.
- 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
For every job request, staff write postings for each job board, with different lengths and fields, and publish or update them in each board's admin screens. The same content is rewritten again and again, and inconsistent pay or location wording causes inquiries.
The workflow in Kitewell
- Add the client's job request to a batch sheetAutomatic
- AI drafts postings in each board's format and lengthAI judgment
- Check that pay, location, and hours match the request, and that items job postings must state since April 2024, such as the scope of changes to duties and workplace, are presentAutomatic
- Staff check and edit the postings and approve publishingApproval
- Publish through each board's official route, such as an API or CSV uploadAutomatic
What AI does
Drafts postings in each board's format and length from the request, and points out wording that disagrees with it, such as pay or location.
Where people decide
Staff check every posting before it is published. Admin screens are operated automatically only where a board's terms allow it.
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
- Which publishing routes your boards offer: API, CSV upload, or applicant tracking system integration
- Whether each board's terms allow automated admin operation (some require asking first)
- Draft quality, and how often staff need to edit
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
- Can it fill in job boards' admin screens too?
- Postings go out through each board's official route, such as its API or CSV upload. Admin screens are operated automatically only where a board's terms allow it. Some boards ask to be contacted first, so the PoC checks each board you use.
- 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
Check and track dispatch period limits
Site limits come from the client's notice; per-person limits run from the worker's start in the unit. As either nears, AI drafts a check that staff review.
Import hours reported by clients
AI reads hours clients email as Excel files, PDFs, or scans and checks them against contracts. Approved hours go to the dispatch system for payroll and billing.
Track placement retention and fee refunds
Confirm with employers at set points up to six months after hire that placed people stayed. For early leavers, draft the refund and log the six-month count.
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.