Documented architecture
Complete architecture diagram + validation workshop with technical teams and management.
§ LEVEL 02 · MID-ENTERPRISE
AI
Infrastructure · Mid-Enterprise
AI at mid-enterprise scale is not 12 individual ChatGPTs. It's a centralized foundation, clear governance and industrialized pilots — not POCs that die in committee.
§ You have AI pilots everywhere — HR, finance, ops — but none make it to production. Every team reinvents the wheel. Data doesn't flow. Governance is unclear.
7→1
data sources unified in one foundation
5
pilots industrialized in 12 weeks
+€4,2M
AI value documented on the mid-enterprise cohort
Méthode
Waimia
01 Architecture
Define target architecture
Mapping of existing data flows, ongoing AI pilots, security and governance constraints. Choice of technical foundation.
02 Centralized foundation
Deploy the centralized foundation
Unified API gateway, complete audit log, AI model observability. A shared infrastructure for all teams.
03 Pilot industrialization
Industrialize priority pilots
The 5 highest-impact pilots go to production: load testing, defined SLAs, operational monitoring.
04 Multi-team adoption
Deploy multi-team adoption
Internal AI competence center. Function-specific training program. SLA governance and operational steering committee.
Ce qu'on
dépose chez vous
Six technical and organizational deliverables. Infrastructure operated by your teams at delivery.
Gateway + audit log
Unified API gateway, complete audit logs, Helicone observability. Source code delivered.
Industrialized pilots
5 use cases in production: load testing, SLA, automatic monitoring, documentation.
Governance & SLA
AI governance policy, SLA per use case, escalation process and steering committee.
Observability
Cost/latency/health dashboards per AI model. Configured alerts, 12-month history.
Competence center
Internal training program by function + complete technical documentation for autonomy.
Signal
terrain
We had 7 AI pilots running in 4 different divisions. None in production. In 12 weeks, Waimia laid the foundation, industrialized the 5 priority ones and trained our technical teams. We now operate the infrastructure internally.
7→1 data sources unified in one foundation
5 pilots industrialized in production
+€4,2M AI value documented in 12 months
100% technical teams trained and autonomous
−72% LLM costs after model optimization
3,1× ROI measured on mid-enterprise cohort at 12 months
AI infrastructure at scale.
60 minutes to scope your pilot status and define the industrialization sequence. Precise quote following scoping.