// SYS_INIT: TECHNICAL_ARCHITECT
I'm a Technical Architect and Fractional CTO. I take early-stage startups from 0 to 1: set the architecture, build the AI stack, stand up DevOps, and ship an MVP people will actually pay for. For scaling businesses, I trace how work flows through the org and automate the parts that shouldn't need a person.
For funded founders and operators who need someone who builds, not just someone who advises.
90% of technical debt comes from over-engineering. The same first-principles thinking I used to guarantee 4,000+ trades per second and zero-latency LLM orchestration applies whether you're building your first product or trying to stop duct-taping SaaS tools together.
| The standard approach | My approach |
|---|---|
| Picking trendy frameworks without understanding what's underneath | Optimizing at the compiler, memory, and runtime level |
| Over-engineering MVPs, then wondering why they're impossible to change | Architecture built around what the business actually needs right now |
| Stacking SaaS subscriptions to patch broken workflows | Full workflow audits, then custom integrations that fix the actual problem |
| Hiring more people to hit growth targets | Automating the work so revenue scales without the headcount |
“My philosophy is simple: dare to stay with the chaos long enough, and the elegant order emerges.”
I act as a technical co-founder from day one. I set the technology direction, architect the AI pipelines and LLM orchestration layers, build out DevOps, and build the engineering culture that gets you to Series A ready. Typical engagement: 60 to 90 days. Two meetings a week max; everything else async.
I map how work actually moves through your business, find where it breaks, and build custom tech to fix it: real integrations, not another subscription. Example deployments: SMAD AI, CashUrDrive, InvoiceProPay.
// Staff augmentation and UI reskinning engagements go to Brahma Labs.
Chief Technology Architect
THE PROBLEM
Organizations needed a multi-tenant system to measure employee skills dynamically, without getting killed by LLM API latency on every request.
WHAT I BUILT
A centralized full-stack SaaS with asynchronous MongoDB job records. AI generation runs in the background; the front end never waits.
WHAT IT DID
Killed the latency problem, scaled to enterprise multi-tenant without exponential cloud costs, and pushed platform adoption up.
Process Automation Architect
THE PROBLEM
Mid-market restaurants were losing bookings because staff manually read and responded to unstructured email requests. Slow, inconsistent, and expensive.
WHAT I BUILT
An email interception layer integrated with IMAP streams. An AI parser pulls booking intent and capacity data out of unstructured text and creates the booking automatically.
WHAT IT DID
Response time went from 4 hours to 2 minutes. Teams got back 15 hours a week on admin. Platform stopped crashing under load.
Lead Architect
THE PROBLEM
Event photographers needed shots on attendee phones almost instantly. Manual ingestion made that impossible.
WHAT I BUILT
Edge-computing scripts that watch physical storage writes and push to cloud the moment a file lands. Concurrent AI facial recognition microservices index incoming media in real time.
WHAT IT DID
Zero-latency delivery from camera to phone, with no human in the loop.
Head of Technology
THE PROBLEM
A fintech exchange needed extreme transaction throughput without dropping trades or mismatching ledgers. Standard database schemas weren't going to hold up.
WHAT I BUILT
A matching engine from scratch using RabbitMQ, Sidekiq, and tuned daemon jobs. Deep cache optimization and queue management built to survive real production load.
WHAT IT DID
4,000 trades per second, guaranteed. Clean ledger under load, no dropped trades, no regulatory exposure.
| Deployment_ID | System_Nomenclature | Core_Architecture | Processing_Metric | Status |
|---|---|---|---|---|
| ARCH_05 | CryptoniumX P2P | Ruby on Rails, RabbitMQ, Sidekiq | Guaranteed processing of 4,000 trades/sec via daemon jobs. | ARCHIVED |
| ARCH_06 | UATU Query API | 20+ Microservices, Cassandra, NLP | Distributed cross-chain data aggregation and semantic parsing. | DEPRECATED |
| ARCH_07 | SMAD AI (Zooby) | FastAPI, pgvector, Celery/Redis | RAG architecture over multi-tenant knowledge bases. | DEMO_ENV |
| ARCH_08 | Video Automata | Python, Browser Automation APIs | Non-linear automated media generation and orchestration. | PROPRIETARY |
| ARCH_09 | Polygame Stream | Node.js Microservices, Tencent Cloud | Real-time WebRTC video ingestion and decentralized indexing. | ACTIVE |
| ARCH_10 | Pedagog EdTech | Laravel, BigBlueButton API | High-load concurrent streaming and adaptive gamification. | ACTIVE |
| ARCH_11 | MEW Identity | Node.js, EVM Smart Contracts | Zero-knowledge physical proximity cryptographic handshake. | ACTIVE |
| ARCH_12 | InvoiceProPay | Python, OCR, Document Parsing | AI-powered GST invoice generation and compliance tracking. | ACTIVE |
| ARCH_13 | Baaman AI Lab | Next.js, Multi-Agent LLMs, Vector DB, WebSockets | Persona-driven pedagogical agents with educator oversight and adaptive assessment. | ACTIVE |
// Truncated: and more 70+ projects.
// INITIATE_DIAGNOSTIC
Download the diagnostic framework I run in the first 14 days of a Fractional CTO engagement. Covers how to spot technical debt that isn't obvious, lock down early-stage database architecture, and keep engineering sprints tied to funding milestones. I'll send it to your email.