Fractional AI/Tech CTO · Technical Due Diligence · AI Architecture & Security Reviews

20+ years in systems where a failure is a regulated event, not a bug ticket. Now I bring that judgment to AI.

A named senior expert — not a faceless firm. I've run AI and money-movement at $2B+ regulated scale and shipped a production agentic-AI platform, so I can both judge an AI system and fix what's broken before the review that decides your deal.

Matching teams can request a free 30-minute scoping call before choosing a paid path.

See How I Work
  • Senior Principal on a $2B+ healthcare/PBM platform (CVS, Walmart, 11 Medicaid)
  • 20+ years high-consequence systems
  • National-government secure-systems leadership
  • Founder-built agentic AI platform
Fractional AI/Tech CTO
Ongoing senior AI and technology leadership: architecture direction, security posture, hiring review, and board-ready judgment — roughly 2–4 days per month.
Technical diligence
Per-deal architecture, security, AI-risk, scalability, and team assessment — written report and debrief call for investors and acquirers.
Review-event readiness
Technical risk review for high-consequence AI workflows: evidence needs, access boundaries, audit trails, enterprise review questions, and regulated-workflow exposure.

Why Hulbon exists now

AI made building cheap. Trust in AI is now the hard problem.

Hulbon is the named senior expert — Giorgi Koranashvili — who has run AI and money at $2B+ regulated scale and personally built a production agentic-AI platform. Fractional AI/Tech CTO, technical due diligence, and workflow risk review for AI in high-consequence and regulated-workflow settings.

The larger belief is simple: AI should reduce fear and scarcity, expand agency, and support systems that can live in better harmony with people and nature. The commercial work starts where that belief meets buyer reality: AI in workflows where access, evidence, and audit actually matter.

AI moves into regulated or high-consequence workflows, but nobody has mapped auth, data, payment, audit-evidence, or agent-boundary risk before the enterprise review.
Investors and acquirers need a clear-eyed technical read on an AI build — architecture, security, AI-risk, team — before committing capital, not a slide deck.
A team that needs ongoing AI/tech leadership can't justify a full-time CTO but can't afford the gaps in architecture direction, evidence posture, or hard build-vs-buy calls.

How I work

Start with a conversation about the system, not a proposal.

You get one senior engineer who has run regulated systems at scale — not a team of juniors and a template. We start with whatever is smallest and most useful, and go further only if that earns it.

The first call is thirty minutes and costs nothing. Bring the review, the questionnaire, or the deadline you are worried about.

Engage with confidence

Senior technical judgment, scoped in writing, with careful evidence boundaries.

  • Direct senior expertYou work with Giorgi, a named senior practitioner, not a junior handoff.
  • Written scope before paid workEvery paid step starts from agreed scope, deliverables, and access boundaries.
  • Least-privilege evidenceUse source, notes, test environments, redacted logs, and walkthroughs before any sensitive access.
  • No production credentials for first passA Snapshot or Decision Memo can start without live customer data or production secrets.
  • Independent technical judgmentRecommendations are technical and operational, not legal, investment, or compliance certification.
  • Nothing about your system is publishedHulbon has no public client work and will not create any without your written permission.

Fractional AI/Tech CTO Retainer

Ongoing fractional AI/Tech CTO for founders and CTOs who need senior AI and technical leadership: architecture direction, security posture, hiring review, and board-ready judgment — roughly 2–4 days per month.

Buyer: Founders, CEOs, and technical leads who need ongoing senior AI/tech leadership: AI architecture direction, security and compliance posture, hiring and code review, and board-ready judgment.
Fit signal: Best fit when you need a named senior expert for ongoing AI/tech leadership without the cost and commitment of a full-time CTO.
Timeline: Ongoing monthly retainer; 2–4 days/month
  • AI and architecture direction
  • Security and compliance posture
  • Hiring and code review guidance
  • Board-ready technical judgment
See Details

Day-Rate Advisory

Episodic senior AI/tech judgment by the day: architecture direction, security posture, diligence support, or hard build-vs-buy calls. No long-term commitment required.

Buyer: Founders, CTOs, and technical leads who need senior AI/tech judgment for a specific decision, review, or hard call — without a long-term commitment.
Fit signal: Best fit when you need one clear senior opinion on a specific technical decision, fast.
Timeline: 1 day per booking; typically 1–4 days/month
  • Senior-level review or working session
  • Written notes or decision artifact
  • Recommendation and next-step framing
  • Clear path to a retainer if ongoing fit
See Details

How Hulbon delivers

A short path from ambiguous AI risk to a clear verdict, trusted evidence, and ongoing senior leadership.

Step 1

Scope and inspect

Define the business workflow or system under review, then read the architecture, access model, dependencies, AI boundaries, and evidence around it.

Step 2

Map risk

Separate trusted behavior from review risk: auth, data, payments, audit evidence, agent/API boundaries, compliance posture, and team capability.

Step 3

Decide and advise

Return a clear verdict — proceed, proceed-after-hardening, or pause — with the smallest fix scope worth funding and a board-ready summary.

Step 4

Implement or anchor

When implementation is approved, ship focused boundary fixes and evidence. Or anchor into ongoing fractional CTO leadership for durable assurance.

Proof of build depth — Lantanios platform

I do not review AI products from the outside. I build and operate one.

Lantanios is a live multi-tenant platform I built, with Stripe Connect payouts, multi-tenant isolation, a site-scoped AI composer gated by role and approval, and multi-model agentic AI. The exact patterns this review looks for, solved in a system I built and run myself.

See systems I built myself
Stripe Connect
Custom domains and SSL
Agent-style tools
OpenAI, Anthropic, Groq
MongoDB, Redis, Socket.IO
GCP and AWS deployment

The credibility is regulated scale, secure-systems depth, and real implementation.

Almost nobody selling AI workflow risk judgment has run a $2B+ regulated-scale platform, held national-government secure-systems leadership, and personally built a live multi-tenant agentic-AI product. That combination is the entire Hulbon thesis — embodied in one named senior expert.

$2B+ Healthcare/PBM Platform Scale

Senior Principal — Magellan Health / Prime Therapeutics (2020–2025)

Architected a multi-tenant financial platform processing $2B+/yr for CVS, Walmart, and 11 state Medicaid programs in a high-consequence healthcare/PBM context. This is the verifiable anchor for regulated-scale architecture, access boundaries, audit evidence, and operational discipline.

$2B regulated platform

National-Government Secure-Systems Leadership

Senior technology leadership across national-government programs

Senior technical leadership building and operating complex secure systems where reliability, access boundaries, audit evidence, and operational continuity carried national-level stakes.

Access/evidence at national stakes

Founder-Built Agentic AI

Lantanios — live multi-tenant agentic-AI platform

Personally architected a live multi-tenant platform with Stripe Connect payouts, multi-tenant isolation, an AI composer gated by role and approval, and multi-model agentic AI (OpenAI, Anthropic, Groq). The exact patterns Hulbon hardens, solved in a real product.

I build, I don't just advise

Bring the codebase, product workflow, or portfolio risk.

Matching teams can request a free 30-minute workflow fit call. Hulbon will first check whether the review trigger, evidence, timing, and investment path are real.