Cost transparency: What you can realistically expect
The most common question from our initial consultation partners: "What does it cost?" Our answer is always honest: it depends on the scope. But we can give very transparent reference values based on 50+ completed projects.
Pricing overview by project size
| Project type | Investment | Timeline | Example |
|---|---|---|---|
| Single workflow | €2,000–5,000 | 1–2 weeks | Email triage or invoice OCR |
| Process suite (3–5 workflows) | €5,000–15,000 | 4–8 weeks | Lead qualification + reporting + support |
| Department transformation | €15,000–30,000 | 2–3 months | Full sales automation |
| Company-wide AI strategy | €30,000–50,000+ | 3–6 months | Multi-department integration with custom AI |
Ongoing costs
| Item | Monthly cost |
|---|---|
| n8n Cloud (workflows) | €20–50 |
| OpenAI API (GPT-4 usage) | €30–200 |
| Server/hosting | €5–30 |
| Monitoring & maintenance | €0–200 |
| Total (typical) | €100–500 |
For comparison: a full-time employee doing the same tasks costs €3,000–5,000/month including employer contributions. Automation saves 80–90% of these costs.
ROI calculation: A concrete example
Scenario: Automating lead qualification
| Item | Amount |
|---|---|
| Initial setup | €8,000 |
| Ongoing costs (monthly) | €150 |
| Saved staff costs (monthly) | €2,500 |
| Net saving per month | €2,350 |
| Break-even | 3.4 months |
| Saving after 12 months | €20,200 |
| Saving after 24 months | €48,400 |
Hidden costs: What to watch out for
- ▸API costs at high volume: GPT-4 costs ~$0.03 per 1,000 tokens. At 10,000 processings per day, that amounts to ~€50–100/month.
- ▸Data quality: poor input data requires cleansing — plan for 10–20% of the budget.
- ▸Change management: employees need to adopt the new tools. Training costs: €500–1,000.
- ▸Scaling costs: as you grow, API costs increase linearly — plan for reserves.
How to plan your budget correctly
- ▸Step 1: Identify your most expensive manual process (staff hours × hourly rate).
- ▸Step 2: Calculate the monthly saving at 80% automation.
- ▸Step 3: Budget = 3–4 × monthly saving (for a break-even under 4 months).
- ▸Step 4: Start with a pilot project and scale on success.
Why cheap often costs more
We regularly see businesses start with cheap solutions (Fiverr, no-code cobbling) and come to us 3–6 months later. The reason: initial costs were low, but the solution did not scale, broke on edge cases, or processed data insecurely. Re-implementation then costs twice as much.
A professionally implemented workflow has an uptime of 99.5%+. A cobbled-together solution often runs below 90% — meaning you have to manually handle every 10th case.