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Volume 1

Production AI Radar

Production AI stack signals for DACH/EU B2B teams

ADOPTTRIALASSESSCAUTIONMLOPSLLMOPSOBSERVABILITYFINOPSPLATFORM & DEVEXGOVERNANCE

Four rings score adoption confidence

Adopt sits at the center: run it in production today. Trial and Assess widen the circle as evidence thins. Caution marks tools we would not bet a regulated workload on.

Six quadrants map your production stack

Every blip lands in the slice of the stack it serves, from model operations to governance. Read your weakest quadrant first; that is usually what blocks release.

Movement shows what changed this volume

New blips appear, proven tools pull inward toward Adopt, and disproven ones drift out. The delta between volumes is the actual signal.

Six production quadrants, 38 mapped tools, and 26 adoption guides. Filter by ring, quadrant, buyer context, or search your stack. Score it against your gaps in a fixed-scope audit.

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62 of 62 signals · Volume 1

MLOpsLLMOpsObservabilityFinOpsPlatform & DevExGovernance
Your stack

Themes for Volume 1

Patterns we see across DACH/EU production AI stack assessments, not generic industry hype.

Audit-first beats pilot-first

Teams that score production readiness before scaling pilots close enterprise deals faster. Fixed-scope diagnostics surface the 5-8 gaps that block sign-off - not another PoC.

LLM cost bleed is the new shadow IT

Ungoverned API keys, missing token attribution, and no routing policy routinely push LLM spend 2-3× forecast. FinOps for inference is no longer optional for mid-market B2B.

Landing zones beat click-ops AI accounts

Shared accounts without network, identity, or tagging baselines force every model and agent into a security exception. Terraform landing zones are becoming the default enterprise ask before the first production inference path.

Agentic coding needs harnesses, not hope

Coding agents without feedforward specs and feedback gates create cognitive debt faster than they ship features. Golden paths and quality sensors belong in the loop before human review.

Infra uptime ≠ model health

Standard APM green while answers degrade is the most common surprise in LLM production incidents. AI observability is a distinct layer - not a dashboard add-on.

Guardrails belong in Git, not slide decks

Input/output rails, injection tests, and PII scrubbing only work when versioned, reviewed, and red-teamed like any other production control - not as a one-time security workshop.

Vector ops is the hidden RAG bottleneck

Model choice rarely explains bad RAG. Collection versioning, filtered search, backup, and reindex gates separate demos from systems that survive enterprise traffic.

Next step

Get your 90-day production roadmap in 10 business days

Fixed scope from €4,500. Maturity heatmap, FinOps register, EU AI Act inventory, and an honest verdict. Sprint within 90 days and your assessment fee is credited.

Full assessment fee credited toward your build. Book a Production Implementation Sprint or Private LLM Platform Package within 90 days of your assessment and we credit 100% of the assessment fee toward that quote, so diagnosis rolls straight into the build.

Audit deliverables

  • 6-dimension maturity heatmap
  • FinOps register
  • EU AI Act system inventory
  • 90-day backlog (IaC & automation prioritized)
  • Executive readout
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