AI Transformation & Modernization · est. 2019

AI transformation
& modernization.

We take AI from pilot to production — and modernize the platforms, data, and delivery practices it depends on. Senior engineers who set the strategy and write the code, from AI agents to rebuilt legacy systems.

Book a 30-min call → See case studies ↘

Part 3 9 min read

AI Governance Framework: From Proof to Procurement

The third part of the series: how we package the posture assessment and measurement layer into a complete AI governance framework — and the Stand-Prove-Procure Method we use to build one with every client.

Seven-Artifact Pack for procurement review

Stand-Prove-Procure three-stage method

Procurement Q→Artifact mapping

Read Part 3 → Start with Part 1 → Read Part 2 →

AI Governance Framework — Stand, Prove, Procure stages connecting posture assessment, measurement layer, and seven-artifact procurement pack

From Pilot to Production

AI Transformation

Find the workflows where AI pays for itself, then build it into production — agents, automation, and the evaluations and guardrails that keep them honest.

AI Strategy & Use-Case Roadmap
AI Agents & Workflow Automation
AI Cost & Reliability Engineering

Modernize the Foundation

Platform Modernization

Re-architect the legacy systems, data, and infrastructure AI depends on — monoliths into scalable services, manual releases into automated pipelines.

Legacy & Monolith Modernization
Cloud, Data & Platform Engineering
DevOps, MLOps & Business Continuity

Enterprise Readiness

AI Governance

Structured governance assessments and frameworks that prepare your AI systems for enterprise procurement and regulated markets.

AI Posture Assessment
Compliance & Risk Management
Monitoring & Accountability

Success Stories

AI in Production, Measured in Results

Agent pipelines shipping at scale, legacy platforms rebuilt, and AI bills brought back under control — with the numbers to show for it.

AI Cost Engineering · AI Infrastructure Latest

How We Reduced a YC Startup's AI Costs by 47.7%

Inside a YC startup's AI cost optimization: model routing, context trimming, and self-hosted inference, with a $230K-to-$120K monthly spend breakdown.

Provider-bill reduction: -47.7% (~$230K → ~$120.3K/mo)
Annualized provider savings: ~$1.3M/yr before on-prem costs

Anthropic Claude · OpenAI · Open-weight models (self-hosted) · +4

Read Full Case Study

AI Agents · Cost Engineering

W6W's Autonomous API Integration Harness

An agent harness that selects, builds, tests and ships API connectors at scale — with the weekly budget acting as admission control rather than a dashboard.

Weekly throughput, and climbing: 10 → 152+ apps
Throughput gain so far: 15.2×

DeepSeek (self-hosted) · Claude Haiku · Claude Sonnet · +3