Logiciel Solutions · AI Engineering
Getting a model to work in a notebook is 10% of the work. Getting it to production reliably is the other 90%. 60 items covering everything from model validation to incident response to governance.
1. Model Quality & Validation
A model that passes offline eval doesn’t always survive real-world inputs. Verify before you ship.
2. Infrastructure & Scalability
Latency SLAs and scaling assumptions feel theoretical until the first traffic spike.
3. Monitoring & Observability
Models degrade silently. Without observability, you learn from user complaints, not dashboards.
4. Security & Compliance
AI inference endpoints are attack surfaces. Treat them that way before launch.
5. Operations & Incident Response
The first time you roll back a model under pressure isn’t the time to write the runbook.
6. Business & Governance
A production model without governance is a liability waiting to be discovered.
Your production readiness score
We’ll email the full checklist breakdown and have an AI engineer review the gaps most likely to cause production incidents at your scale.
No spam. We’ll follow up only if it’s relevant.
