Business Model
Last updated: February 2026
Two products, one company
IT asset lifecycle management platform for NIS2 compliance. Cloud SaaS from €49/month. Open source, self-hostable for free.
A public case study: can 1 human + AI agents run a SaaS company? All numbers, decisions, and results public on GitHub. The story generates distribution.
Open Source Core (AGPL)
The full platform is open source under AGPL-3.0. Anyone can self-host it for free. The AGPL license ensures that forks cannot be monetized as a service without releasing modifications — this protects against a competitor taking the code and building a closed commercial product on top of it.
Open source is distribution. A sysadmin finds the project on GitHub, tests it, and buys the cloud version when they need managed infrastructure. No sales call, no demo request, no friction.
Cloud SaaS Revenue
One flat monthly fee based on company size. No per-user fees, no per-asset fees, no overage charges.
| Plan | Company Size | Price/month |
|---|---|---|
| Free | Self-hosted, unlimited | €0 |
| Starter | ≤25 employees | €49 |
| Growth | ≤100 employees | €99 |
| Scale | 100+ employees | €199 |
Team Model: AI Agents + Human Advisors
There are no employees. The company is run by one human (Orchestrator) directing AI agents. When human expertise is needed, we bring in advisors — not employees.
This model improves gross margin significantly vs. traditional SaaS: no sales salaries, no engineer salaries, no CS headcount. Fixed costs: ~€210/month (infrastructure + AI tools).
Unit Economics
| Metric | Target |
|---|---|
| Fixed monthly costs | ~€260 |
| Break-even customers | ~6 (Starter plan) |
| Average Revenue Per Account | ~€87/month (blended) |
| Gross margin | >90% (no human labor cost) |
| CAC target | €0 (organic only) |
Bootstrapped — No Investors
No venture capital. No angel investors. No accelerator. 100% founder-owned.
IT managers want tools that are still around in 5 years. A bootstrapped company optimizes for survival and customer value, not growth metrics for a deck. The AI-managed model makes this economically viable at a scale that would be impossible with a traditional team.