Most enterprise AI fails because of broken data foundations.

We diagnose what's broken, then replace the bottleneck.

Start with a Diagnostic See the Platform →
AI Readiness Diagnostic
  • ✕ Semantic layer Not present
  • ✕ Schema governance Critical gaps
  • ! Pipeline health Fragmented
  • ✕ Agent query readiness Not ready
Latency Index 78 / 100 4 critical findings
→
Remediation path identified Foundation design · Semantic layer build · ADO deployment

Evidence

The pattern is in the data.

88%

of AI proofs-of-concept never reach production.

IDC Research

70%

of senior data scientists' time goes on manual pipelines, not analysis.

Anaconda State of Data Science

6 in 10

enterprises running AI at scale report no impact on profit.

McKinsey State of AI, 2025

How we engage

Diagnostics first.
Platform second.

01 AI Enablement Consulting

Find the gaps. Build the foundation.

See the consulting offer →
02 The Autonomous Data Office

Replace the bottleneck. Scale without headcount.

See the platform →

Two-to-four-week diagnostic. Fixed fee.

Book a Discovery Call