A virtual employee costs a fraction of a human one. But not €100 — and here is why.
AI agents built on your company's own policies, documents and processes — and wired into the tools your people already use. Managed, or self-hosted so nothing leaves your perimeter.
Learning policy · your profile
Leave policy · your profile
Questions about policies, procedures and personal data — "will my training be reimbursed?", "what does my health insurance cover?" — answered by the HR Assistant, the first agent in the list below. Tested on real HR conversations — vacation days, salary reviews, insurance, training budgets — and ready to deploy.
Why the €100 "AI employee" doesn't work
An off-the-shelf bot is trained on generic data. It has never seen your policies, your procedures or your people — so it guesses.
Company knowledge has to be systematised, cleaned and structured before an agent can use it. That preparation is 80% of the work.
Email, Telegram, CRM, your employee database — an agent that isn't wired into your systems is just a chat window.
A properly built agent works 24/7, doesn't resign and scales by config. Over a year it costs several times less than a human hire.
Ready-to-deploy agents
Don’t see your process here?
Many don’t. The six above are the processes I meet most often, not a full list. So we start with consulting: two or three weeks where I go through how your company actually works, find the steps where automation pays off and design a solution that fits them exactly — usually a custom agent or an integration, built the same way as the six above.
- Which steps in your work a machine can take over today and which still need a person
- What each one is worth now and once your volume doubles
- A solution shaped around those steps, with a plan for building it
From call to production: 6–10 weeks
the full cycle →What to automate, what it yields, what it costs. If it won't pay off — I say so.
Systematising your policies and documents. 80% of the result lives here.
A working agent on your data, for you to break.
Local and cloud models on your own test cases: quality, price, privacy.
A limited user group, real metrics, hardening against misuse.
Deployment, team training, SLA support, monthly metrics report.
Managed or self-hosted
Pavlo Zhdanov
Architect and product lead behind every agent on this site. 25+ years in digital products — CTO at Bigmir, director of digital at SkyUp Airlines and partnership programs with Google, Skyscanner, Allegro.pl and ICQ that I negotiated and turned into revenue lines. Today I design, build and support AI agents personally, so the person you talk to is the one who builds it.