# SERVICE / 01
AI that ships to production,
not just to a demo
Your AI pilot worked in the demo. Six months later, it's still in staging — no MLOps, no monitoring, no owner. We get agents, RAG pipelines, and MCP integrations into live operation, typically in under 90 days. EU AI Act classification built into delivery, not bolted on after.
# THE-PROBLEM
why this matters.
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.
- 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
// symptoms
# IS-IT-FOR-YOU
best fit · not ideal.
- You have a specific AI use case, not "we need an AI strategy"
- Your team can point us at the data the AI needs to reason over
- EU AI Act compliance is part of the ask, not an afterthought
- You want the people building it on every call — not a delivery manager
// best fit for
- Greenfield "AI transformation" programs without a concrete first use case
- Research-grade projects with no production target
- Fortune 500 multi-year rollouts — we're a two-person team, not a consultancy of scale
// not ideal for
# OUR-APPROACH
how we deliver.
-
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
what good looks like.
- Typical time to production
- <90 days
- Measured productivity lift
- 15–20%
- To working internal release
- 6 weeks
- EU AI Act compliance
- Built in
# TECH-STACK
technologies we use for applied ai & custom solutions.
production-tested tools and frameworks — not a wish list.
# DEFINITION
what is applied ai & custom solutions consulting?
Applied AI consulting is the practice of building production-ready AI systems — agents, RAG pipelines, and MCP integrations — for enterprise use cases, with a focus on measurable business outcomes and regulatory compliance. We deliver this for mid-market companies in DACH with EU AI Act risk classification and documentation built into every project.
# FAQ
common questions.
-
How long does it take to get an AI agent into production?
Most projects reach production in under 90 days — architecture, dev, testing, MLOps, and EU AI Act classification. Timeline depends on data readiness and integration complexity. A working internal release is typically ready within 6 weeks. -
Do you handle EU AI Act compliance?
Yes. Every project includes risk classification under Article 6. We build the documentation, audit trails, and human oversight before the August 2026 deadline. Juri handles compliance, Oleks builds the technical controls. -
What is MCP and why does it matter?
MCP (Model Context Protocol) lets AI agents connect to your business tools — CRMs, databases, internal apps — without custom code per integration. We build MCP servers so your AI reads and acts on real business data.
ready to put applied AI into production?
30-min discovery call. we'll bring an architecture sketch and a rough price band.
book-call// or write: hello@saloid.com · gräfelfing · de