Saloid's Applied AI practice delivers production-ready AI systems — agents, RAG pipelines, and MCP integrations — for mid-market enterprises in DACH, with EU AI Act compliance from the start.
AI that ships to production,
not just to a demo.
Talk to us about your AI project The problem
AI pilots die in staging. Nobody built the MLOps pipeline, nobody set up monitoring, and nobody planned how this thing actually creates value once the demo is over.
Symptoms
- POC worked in the demo — still stuck in staging six months later
- No CI/CD for models. Retraining is manual, if it happens at all
- EU AI Act deadline approaching with zero classification or documentation
- AI tools can't access real business data — locked behind APIs nobody built
- Team excited about AI, but no one owns the path from prototype to production
Our approach
Use-case validation
Separate the hype from the viable. We assess feasibility, data readiness, and EU AI Act risk class before writing a line of code.
Rapid prototype
Working agent or pipeline in weeks, connected to your real data via MCP — not a sanitized demo dataset.
Production engineering
MLOps scaffold, monitoring, drift detection, human oversight loops. The boring stuff that makes AI actually work.
Launch & iterate
Deploy to your EU infrastructure, document everything, train your team. Then iterate based on real usage data.
Outcomes
<90 days
Notebook to production
15–20%
Measured productivity lift
6 weeks
To working internal release
100%
EU AI Act compliant
Tech stack
LangChainOpenAIAnthropicAI AgentsRAGMCPMLOpsPythonNode.jsReactVector stores Frequently asked
How long does it take to get an AI agent into production? +
Do you handle EU AI Act compliance? +
What is MCP and why does it matter? +
Other disciplines
Ready to fix your data stack?
20 minutes. No slides. We'll tell you what we'd do, what it costs, and whether you actually need us.