Services
Your RAG prototype works. Is it ready for production?
Building RAG and extraction MVPs is fast. Knowing if they'll work in production is hard. Without systematic evaluation we are guessing.
I design and implement evaluation infrastructure for RAG and extraction systems — creating measurable confidence about where your system can be trusted, so you can scale with evidence, not guesswork.
For extraction: I build or improve production-ready pipelines with evaluation infrastructure — whether you're starting from scratch or optimizing an existing system.
For RAG: I diagnose, evaluate, and improve existing systems. I'm telling you if it works, where it breaks, and how to fix it.
Discovery Call (Free)
What it is: 0.5-1 hour conversation to understand your evaluation needs.
Best for:
- Leaders wanting expert assessment before committing
- Teams unsure which service tier fits their situation
What happens:
- Discuss your AI system and quality concerns
- Identify evaluation gaps and priorities
- Recommend the engagement that creates reliable signal
- Clear next steps: diagnosis, reality check, or full build
Timeline: 1-1.5 hours | Investment: Free
RAG Reality Check
What it is: Evaluate whether your RAG approach will work on real documents before you commit to building.
Best for:
- Teams planning RAG systems who need to know if the approach is viable
- Leaders deciding between RAG approaches (chunking strategies, hybrid search, etc.)
- Organizations wanting to de-risk AI investment
What you get:
- Document landscape analysis (types, structure, variability, edge cases)
- Evaluation set design with representative test documents
- Custom metrics for your domain and use case
- LLM-as-judge calibration
- Failure mode taxonomy (where it breaks, how often, severity)
- Clear "build / don't build / build differently" recommendation
Timeline: 2-4 weeks | Investment: Starting from EUR 5k
Evaluation Infrastructure Build
What it is: Full evaluation framework design and implementation for production confidence.
Best for:
- Teams committed to production deployment
- Organizations needing ongoing quality monitoring
- Engineering leaders wanting safe iteration with regression testing
What you get:
- Everything in the RAG Reality Check, plus:
- Production-ready evaluation harness (code + config)
- Gold standard dataset with documented success criteria
- Baseline metrics report and failure taxonomy
- Automated regression testing suite (CI/CD ready)
- Team training and documentation
Timeline: 6-8 weeks | Investment: Starting from EUR 10k
Continuous Quality Guardian
What it is: Monthly support for evolving AI systems that need sustained quality oversight.
Best for:
- Teams with complex systems that change frequently
- Organizations adding new document types or use cases
- Companies needing expert oversight during scaling
What you get:
- Monthly evaluation runs on production data
- Quarterly gold standard refresh as system evolves
- New evaluator development for emerging needs
- Quality trend analysis and advisory
- Priority support for quality incidents
- Guidance on model upgrades (new GPT/Claude versions, OSS models)
Timeline: 3-12 month retainer | Investment: Starting from EUR 1k/month
Two Tracks, Different Standards
| Information Extraction | RAG & AI Automations | |
|---|---|---|
| Success criteria | 95%+ precision/recall | No critical failures + good UX |
| Why different? | Fully automated, no human review | Human validates answers |
| Ground truth | Clear, measurable | Fuzzy, subjective |
| My role | Build or improve to production accuracy | Diagnose and improve existing systems |
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Not sure which service fits?
Start with a free discovery call. We'll figure out the right approach for your situation together.