A EUR 50,000 AI project: what do you get for it in 2026?

Key points: EUR 50,000 is not a small amount for an SME AI project - but it is not an unlimited budget either. Realistically you get: a working prototype or MVP of one clearly scoped AI application, built in 8-14 weeks, deployed to production. With subsidies (WBSO + MIT + SLIM) you can get back EUR 17,500-EUR 25,000, bringing net costs down to EUR 25-32k. What you do not get: a platform migration, three different AI functions at once, or an enterprise architecture.

The realistic scope of EUR 50,000

A well-structured EUR 50,000 AI project delivers one of the following:

Option A: Predictive analytics model in production

• An ML model that predicts one concrete thing (customer churn, demand volumes, fraud, conversion)
• Built on your existing data (max 2 data sources)
• Integrated into an existing dashboard or CRM
• 6-9 months of maintenance advice/monitoring included

Option B: AI chatbot or agent on your knowledge

• LLM-based chatbot trained on your documents, FAQ, product data
• Integrated into website or internal system
• Vector database set up (Pinecone, Weaviate or self-hosted)
• Safety filters and monitoring

Option C: Automation workflow with an AI step

• Document classification, invoice recognition, email routing or similar
• Integration with your existing software (ERP, CRM, mail)
• Error handling and human-in-the-loop where relevant
• ROI typically recouped in 6-12 months on time savings

Option D: AI-augmented dashboard

• Enrich an existing Power BI/Tableau dashboard with predictions, anomaly detection, natural-language queries
• Combination of classic BI + ML features
• Suitable as a follow-up to an existing data dashboard project

What EUR 50,000 does NOT cover

Be realistic about what falls outside the scope:

• Setting up a full data warehouse (separate project, EUR 40-100k)
• Multiple AI functions at once (chatbot AND forecasting AND dashboard = EUR 100k+)
• AI in production without an existing data infrastructure (first go from Excel to a data foundation)
• Compliance + governance + AI as an integrated track (separate EUR 15-25k for AI Act compliance)
• Continuous retraining for 12+ months (separate operational cost)

Budget breakdown: where does the money go?

In a typical EUR 50,000 project the costs break down as follows:

Important nuance: if you choose a track with Stratalytic, the subsidy application is included - no separate costs. We only charge for the project itself.

Subsidy impact: from EUR 50,000 to EUR 25-32k net

Subsidies can cover 35-50% of the project budget. For a EUR 50,000 project the stack looks like this:

WBSO (36% reduction on development hours):

• Stratalytic developer hours on the project: ~EUR 30,000
• WBSO reduction: 36% x EUR 30,000 = EUR 10,800 back

MIT feasibility (35% of project costs in the research phase):

• Discovery + architecture + R&D research: EUR 13,000
• MIT feasibility: 35% x EUR 13,000 (well under the EUR 20k cap) = EUR 4,550 back

SLIM (60% of training costs):

• Team training cost: EUR 5,000 (can be separate or included in the EUR 4,000 budget above)
• SLIM reimbursement: 60% x EUR 5,000 = EUR 3,000 back

Total subsidy proceeds: EUR 18,350 (37%).

Net costs: EUR 31,650 for a working AI system in production.

Timeline: 12 weeks from briefing to production

A realistic EUR 50,000 project timeline:

Work running in parallel:

• Subsidy applications in weeks 1-2 (WBSO runs in parallel throughout the project)
• MIT feasibility is typically submitted at the start of the project
• SLIM application in preparation for the next round

Common mistakes in EUR 50k projects

1. Scope creep. "Can we also add X?" - avoid this if it weakens your main theme. One thing done well > three things done mediocrely.

2. Forgetting data quality. No ML without clean data. Reserve at least 20% of the budget for data engineering. This is where many projects get stuck.

3. No change management for the team. The model works, but no one uses it. Reserving SLIM training is not a luxury; it determines whether the investment pays off.

4. Underestimated deployment costs. Training a model takes a week. Keeping it in production takes ongoing attention over time. Reserve budget here.

5. No subsidy strategy. Without WBSO/MIT/SLIM you pay 50% more than necessary. Plan this before the start of the project, not afterwards.

Case in point: Masparts

For Masparts we built three AI models in the existing Laravel/Filament backend for a comparable budget tier: a cross-sell engine on 1.2M product relations, quote scoring with 84% conversion accuracy and early-warning customer signals. Live in four weeks, directly in the system where sales was already working. The ROI: measurable quote prioritisation from day one.

Not every EUR 50k project has this impact, but the approach is transferable: one clearly scoped problem, built into an existing system, with the subsidy stack arranged up front.

Want to explore whether your idea fits within EUR 50k?

Schedule a 30-min intro call. We discuss your use case, estimate the scope, and within 48 hours give you an indication of budget, lead time and which subsidies fit.

Frequently asked questions

Is EUR 50,000 enough for a serious AI project? For an MVP or focused AI application: yes. Think of a predictive model, a chatbot on your own data, or an automation flow. For enterprise-scale platforms this is too limited - that's more like EUR 150-300k.

How much of that is eligible for subsidy? With a good subsidy strategy: 35-50%. Concretely: EUR 17,500 via WBSO + EUR 4,550 via MIT feasibility + EUR 3,000 via SLIM = EUR 25,050 coverage on a EUR 50,000 project.

How long does a EUR 50k AI project take? Typically 8-14 weeks end-to-end. Three weeks for data research and design, four to eight weeks for build, two weeks for deployment and training.