Enterprise / established stage

AI pilots that reach production, not another deck

AI Automation at $3,000 a month. Senior engineer, OpenAI and Claude, vendor-neutral. NDA standard. Monthly retainer, cancel anytime.

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Starting at $3,000/mo · monthly retainer

Who this is for

Enterprise operations or IT leader piloting AI across departments.

The pain today

  • Every AI vendor pitch is a demo; none reach production.
  • Internal engineering lacks bandwidth for AI integration work.
  • The board is asking for AI strategy with no production track record.
  • Data governance and privacy concerns block every pilot past week 4.

The outcome you get

  • Pilots that reach production with measurable ROI.
  • Data governance explicit per automation.
  • Vendor-neutral engineering (I do not resell AI).
  • A quarterly AI ROI report for the executive sponsor.

Pilot-to-production pattern

Most enterprise AI pilots die between demo and production. The demo works in a sandbox with clean data. Production fails on messy data, edge cases, and integration gaps. I build pilots that reach production by starting from production constraints: real data, real volume, real access controls. Pilot one ships inside 6-8 weeks with a measurable metric (hours saved, tickets resolved, documents processed). Pilot two builds on the same integration layer. By month six, 3-5 automations are in production with quarterly ROI reporting. This is the pattern that separates AI engineering from AI demo-ware.

Data governance and privacy

Enterprise data governance is the make-or-break for AI automation. I write an explicit data-classification policy per automation: what data goes to the model, what stays on-premise, what gets redacted, what gets logged. For highly regulated data (PHI, PII, financial) I use self-hosted models (Llama, Mistral) or Azure OpenAI with signed data agreements. For commodity data, hosted Claude or OpenAI with careful prompting is fine. Every decision is documented and signed off by the enterprise data governance committee. This is senior engineering work plus documentation discipline.

Measuring AI ROI credibly

Enterprise ROI measurement for AI needs to be defensible. I use before/after time logs, ticket resolution times, document processing volume, and error rates. The monthly report goes to the executive sponsor with a CFO-readable ROI calculation. One AI Automation client (smaller but similar pattern) cut 40 hours a month of manual document work. Enterprise scale typically returns 500-2,000 hours a month across 3-5 automations. The retainer at $3,000 a month is a fraction of the recovered capacity.

Phased rollout across departments

Enterprise AI rollouts work best phased across departments, not simultaneous. Phase one: one department, one automation, 90 days. Phase two: expand within the department, start a pilot in a second. Phase three: cross-departmental automation sharing the integration layer. Over 12-18 months a typical enterprise ships 10-15 automations and retires 5-10 overlapping vendor tools. The savings over a year are typically $200,000-$800,000 in recovered capacity plus $50,000-$200,000 in retired vendor subscriptions.

Recent proof

A comparable engagement, delivered and documented.

Payment Integration Platform

Unified payment orchestration across Asia and Europe

Delivered the payment orchestration platform at bolttech, a $1B+ unicorn, with 40+ integrations across multiple regions.

Fintech$1B+ unicorn40+ payment providers15 new markets
Read the case study

Frequently asked questions

The questions prospects ask before they book.

Can you work with our Azure OpenAI or AWS Bedrock accounts?
Yes. I work on your infrastructure and accounts. No reselling, no vendor kickbacks.
What about HIPAA or FedRAMP workloads?
I work inside your compliance posture. HIPAA via BAA providers, FedRAMP via approved cloud regions and models. I do not substitute my compliance for yours.
Can you sign our enterprise MSA?
Yes. US LLC, standard insurance, NDA, DPA. Procurement turnaround typically 2-4 weeks.
Do you work across multiple departments?
In phases, yes. One or two departments concurrent is the practical limit for a single senior engineer. Beyond that I help recruit additional seniors from my network.
What's the typical enterprise engagement length?
12-18 months. Enterprise rollouts need calendar time for change management, phased rollout, and governance cycles.
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Available for new projects