From AI prototype to production — the journey EU teams skip

The journey, named

The AI prototype-to-production journey is the work that turns a notebook, a Copilot trial or a hackathon agent into a service with an SLO, an owner, a cost envelope and an evidence pack. LMXAI exists for that interval. The homepage claim is literal: one partner across software, architecture, data and commercialisation, acting as fractional AI CTO.

Where teams stall

1. Unowned demo. It lives on one laptop. Nobody can redeploy it.
2. No gold questions. Quality is “it felt good in the steering committee.”
3. Prompt-only security. API keys in a .env, documents in a shared drive, no audit trail.
4. Surprise invoice. Context and agent loops were never modelled.
5. Compliance as a slide. “We will be EU AI Act ready” with no inventory or logs.
6. Handoff vacuum. The vendor leaves; the repo is a zip file.

The production checklist LMXAI uses

Stage	Exit criterion
Frame	Intended purpose, users, data classes, success metric written down
Thin slice	One workflow in a real environment, not a slide prototype
Retrieve / tool	Index or tools you own; eval set of ≥30 gold items
Serve	vLLM or contracted API behind a gateway; traces on
Harden	Auth, egress policy, PII handling, human override
Prove	SLO + cost sheet + AI Act gap list signed by an owner
Transfer	Your org, your runbooks, your on-call — we stay or we leave cleanly

How long it takes

A honest thin slice is weeks, not quarters. A workspace or clinical agent that a 500-person org can use is months, because retrieval quality, IAM and works-council constraints dominate the calendar — not model choice. Anyone who quotes a production date from a model card is selling the skipped journey.

Related reading: production RAG and agents, sovereign vLLM, workspace vs Copilot.