About Me

Most AI initiatives die in the gap between the strategy deck and the production deploy. I was built for that gap.

The Architect Who Carries It All The Way

Enterprises don't have an AI-model problem — they have a translation problem. The business knows where it bleeds money. Engineering knows what's possible. Very few people can stand in the middle, speak both languages fluently, and carry a solution the whole distance. That's my job description.

🎯 What I Actually Do

I sit with operators and executives to find the problem worth solving, pressure-test it against the data and systems that actually exist, then architect, build, and ship the platform myself — with the evals, guardrails, and runbooks that keep it alive after the applause.

🏛️ Where I Sharpen It

At SKYTEK Solutions, LLC I lead the AI transformation practice for a security-first MSP that's served businesses since 2012 — which means everything I ship has to survive real users, real audits, and real 3 a.m. incidents. That discipline travels with me into every industry I work in: finance, healthcare, professional services, logistics, and beyond.

💡 The Operating Belief

"Transformation isn't a project you deliver — it's a capability you leave behind." Every engagement ends with a running system andthe team to run it. The measure of my work is what keeps shipping after I've moved to the next problem.

End-to-End
Idea → Deploy → Scale
12+
AI Systems in Production
6+
Industries Transformed
40%
Avg. Operating Cost Reduced

Operating Principles

💼

Business First, Model Second

The technology is chosen last. If the ROI case doesn't survive a skeptical CFO, it doesn't get built.

🔒

Production Is The Only Demo

Prototypes teach; they don't sell. Everything I show runs on real data with real guardrails, evals, and observability.

🤝

Teams Over Heroes

I hire, mentor, and hand over. What I leave behind is a capability, not a dependency.

Full-Stack, In The Widest Sense

From the boardroom framing of a problem to the observability stack that keeps the answer alive at 3 a.m.

🎯

🏆 Principal-Level Expertise

AI Strategy & Transformation
Expert
Enterprise Solution Architecture
Expert
Executive & Stakeholder Alignment
Expert
Generative & Agentic AI
Expert
AI Team Leadership & CoE Design
Expert
LLMOps, Evals & Guardrails
Expert
🧠

Generative AI & LLM Stack

OpenAI (GPT-4o, o-series)
Azure OpenAI Service
Anthropic Claude
LangChain & LlamaIndex
RAG & Vector Retrieval
Multi-Agent Orchestration
🤖

AI/ML Foundations

Prompt & Context Engineering
Whisper & Speech AI
Fine-tuning & LoRA
TensorFlow
PyTorch
Hugging Face
☁️

Cloud & Platform Engineering

Microsoft Azure (Primary)
AWS
Google Cloud
Docker & Containers
Kubernetes / AKS
Zero-Trust & Compliance
⚙️

Backend & APIs

FastAPI
Python
Node.js
Express.js
Flask
REST / WebSockets / GraphQL
🎨

Frontend & UI

React
Next.js
TypeScript
Tailwind CSS
JavaScript
HTML / CSS
🔀

Data & Automation

n8n Workflow Automation
Power Platform
PostgreSQL
MongoDB
Vector DBs (Pinecone, pgvector)
Redis Cache
🎓

Delivery & Leadership

Hiring & Team Building
Executive Advisory
Change Management
Upskilling & Enablement
Roadmap & OKR Design
Vendor & Build-vs-Buy Strategy

Where I Operate Deepest

98%

AI Strategy & Architecture

From problem framing to signed architecture — pricing, risk, and ROI baked in

95%

GenAI, Agents & LLMOps

Agentic systems, RAG, evals, and guardrails that survive real production

92%

Leadership & Enablement

Standing up AI teams and centers of excellence so capability outlives the engagement

Selected Transformations

End-to-end systems that survived contact with reality — real users, real audits, real 3 a.m. incidents.

🎙️

Autonomous Service Operations Platform

AI as the First Responder for Enterprise Support

Internal

A production agentic layer that acts as the first responder for enterprise support: listens in real time, extracts intent, checks urgency against runbooks, opens tickets in the PSA, and routes to a human only when the AI can't safely resolve. Live inside a security-first MSP serving businesses since 2012.

✅ Key Highlights:

SIP-integrated voice front door with Twilio & Asterisk
GPT-4o reasoning with tool-use and structured outputs
Human-in-the-loop escalation with full audit trail
Guardrails, evals, and observability from day one
Azure-hosted, zero-trust network posture
Deep integration with PSA, RMM, and identity stack

🛠️ Tech Stack:

Agentic AI
GPT-4o
Twilio SIP
FastAPI
Azure
Python
🔒 Live in production | Demo on request

Performance Metrics

60%
L1 Auto-Resolved
−45%
Mean Time to Resolve
99.9%
Uptime
🧠

Enterprise Knowledge Copilot (RAG)

ChatGPT For Your Company — With Access Control That CISOs Sign

Internal

Production RAG platform serving multi-tenant departments with clause-level citations, role-based retrieval, and full audit logs. Designed so answers are not just correct — they are provably correct, traceable to source, and safe to expose to auditors.

✅ Key Highlights:

LangChain + GPT-4o with dynamic per-tenant namespaces
Row-level access control mapped to identity provider
Chat memory with intelligent summarization
Streaming React frontend, dark-mode by default
Kubernetes deployment on Azure AKS
Full evals, red-team, and citation traceability

🛠️ Tech Stack:

React
FastAPI
LangChain
GPT-4o
Azure AKS
Pinecone
🔒 Live in production | Code sample on request

Performance Metrics

40-50
Concurrent Users
< 2s
Query Latency
92%
Cited Accuracy
🧪

AI Quality Assurance & Coaching Engine

Making Quality Audits Autonomous — Not Just Cheaper

An automated review pipeline that transcribes, evaluates, and scores support conversations against SOP, tone, and outcome — then feeds coaching prompts back to individual engineers. Cut human QA review time by 80% while raising, not lowering, standards.

✅ Key Highlights:

Automatic transcription of call and chat recordings
GPT-4o review against SOP + tone + resolution rubric
Advanced scoring with per-engineer coaching output
Daily leader summaries with trend detection
Integrates with existing QA and HR workflows
Feedback loop to continuously refine the rubric

🛠️ Tech Stack:

OpenAI Whisper
GPT-4o
FastAPI
Power Automate
Python
Azure
🔒 Live | Rolling out to additional teams

Performance Metrics

80%
Review Time Reduced
5× faster
Processing Speed
94%
Rubric Accuracy

Also In Production

💬

Saava.ai — Conversational AI Lead Engine

Dual-agent platform — Ava handles inbound web chat, voice, and live avatar; Adam calls back within minutes via Twilio. n8n backbone orchestrates quoting, PSA ticketing, and category-routed email. Live with customers; being spun out as a standalone SaaS.

ElevenLabs ConvAIHeyGen AvatarTwilion8nMS GraphAutotask PSA

Identity Lifecycle Automation

Zero-touch onboarding and offboarding across Entra ID, Intune, and Azure — from Forms trigger to signed-off audit trail

PowerShellEntra IDIntuneAzureMS Forms
🔒

SOC Response Copilot

Form-based alert confirmation with location intelligence and auto-suppression — turns MDR/SIEM noise into signal in seconds

Power AutomateSentinelLocation APIs
📊

Profitability & FinOps Dashboards

Executive-grade Power BI dashboards on top of MySQL models — client-level margin, cost drift, and AI-driven anomaly flags

Power BIMySQLAzureAnomaly Detection
📄

Document Intelligence for Compliance

Retrieval + extraction platform with clause-level citations and human checkpoints — turned days of review into minutes, audit-ready by construction

RAGGPT-4oVector SearchAudit
🎯

Revenue Operations Agent Platform

Multi-agent layer for lead enrichment, proposal drafting, and forecast hygiene — sales ops as a background process

Multi-AgentCRM APIsn8nAnalytics
Bets I'm Making Right Now

Where AI Goes Next

The four transformation bets I'm actively architecting for enterprise — not demos, not decks. Real platforms, real budgets.

Live pilots · scaling
Now → 2026

Fully Autonomous Service Operations

Multi-agent systems that own routine incidents end-to-end — triage, diagnose, resolve, document — with humans reserved for the judgment calls only humans should own. The next frontier of self-driving IT.

Progress25%
Building
2026

Enterprise-Grade Agent Governance

The missing operating system for agentic AI in regulated environments: identity, permissions, cost caps, red-team evals, and full audit trails — so agents earn the right to run at 3 a.m.

Progress45%
R&D
2026

Self-Curating Knowledge Fabric

Vector estates that curate themselves — de-duplicate, freshness-score, and prune based on real usage. The end of stale RAG answers and the birth of knowledge platforms leaders can actually trust.

Progress15%
Design
2026

AI That Adapts To Who's Asking

Role-, region-, and risk-aware AI: dynamic retrieval and response scopes bound to identity and compliance context. Same platform. Every user gets the truth they're allowed to see.

Progress10%

The Operating Belief

"The next decade of AI won't be won by the most powerful model — it will be won by the leaders who can name the problem worth solving, ship the answer through a real production floor, and leave behind a team that keeps shipping. That's the discipline. That's the whole job."

4
Active Transformation Bets
6+
Industries Live
2026
Horizon In Delivery

Have a business problem that smells like AI? Let's find out.

Let's find your problem worth solving

Have A Business Problem That Smells Like AI?

First conversation is a working session, not a sales call. Bring the problem, I'll bring the questions.

Start The Conversation

Advisory, transformation engagements, and hands-on architecture — a paragraph is enough to get started.

Open To Advisory

Enterprise transformations, architecture reviews, and CoE build-outs

Response: usually within 24 hours

At A Glance

12+
AI Systems Live
6+
Industries
E2E
Idea → Deploy
1
Accountable Owner