Available for equity roles & select engagements

Darrell
Greenfield.

Technical Co-Founder/AI Systems Builder

I build what others scope out. 14 years across infrastructure, cloud, automation, and software — now focused on building AI-native products and systems that generate real business outcomes.

Darrell Greenfield

Full-stack execution.
From the idea to the infrastructure.

I don't just write code. I architect systems, make the right tool decisions, ship the MVP, and build in a way that doesn't fall apart when things get real.

[ 01 ]
AI Voice Agents

Intelligent phone systems built on GoHighLevel that handle inbound calls, qualify leads, and route conversations — trained for your business, running 24/7.

[ 02 ]
Automation Pipelines

End-to-end workflow automation with n8n: lead ingestion, data routing, internal ops, client-facing systems. The repetitive work gets handled so your team can focus on what moves the business.

[ 03 ]
SaaS Products

From validated idea to multi-tenant product — architecture, back-end, front-end, auth, billing, deployment. Built to scale, designed to sell.

[ 04 ]
Web & SEO Systems

High-performance sites and local SEO infrastructure built to rank, convert, and capture demand. Engineered, not templated.

Not a freelancer. Not an agency.
Not just an engineer.

Most technical people either write good code or think about the business. Rarely both. That gap is where most startups slow down or stall entirely.

A Generic Dev
Executes what's defined
  • Takes the ticket, ships the feature
  • Needs someone to define the product
  • Doesn't ask why something is being built
  • Optimizes for "done," not for "right"
  • Disappears at handoff
An Agency
Scoped to what you define
  • Works to exactly what you specify
  • Layers of PMs, QA, handoffs
  • Optimized for billing, not your outcome
  • Incentivized to expand scope, not simplify
  • Moves on when the contract ends
Me
Thinks from outcome first
  • Challenges scope when the approach is wrong
  • Deep infrastructure background means fewer costly surprises
  • Bridges technical decisions with business strategy
  • Engaged through iteration, not just delivery
  • Wins when you win — equity or outcome aligned

My background is systems that have to work — critical infrastructure, high-availability environments, production where downtime costs real money. That doesn't just make me a better engineer. It makes me a better product decision-maker. I know what breaks at scale, when to build custom, when to buy, and how to scope an MVP that's real enough to validate and tight enough to ship fast.

Real systems. Real problems. Shipped.

No manufactured case studies. These are actual builds — each one designed to solve a specific business problem.

AI Voice · Field Service
Voice agent deployed for a roofing contractor network

Built a GoHighLevel voice agent trained on job types, service areas, and booking logic. Handles inbound calls end-to-end — qualifies the lead, books the estimate, and gives the team a warm handoff instead of a voicemail.

↓ Response time: hours → seconds
Automation · Lead Gen
n8n pipeline processing hundreds of leads per week

Built a multi-source lead ingestion system that scores, deduplicates, and routes leads by priority — automatically. The team went from spending hours on data entry to focusing entirely on conversations that matter.

↓ Lead response: 24 h → < 5 min
Automation · Legal
Intake automation saving 8+ hours of admin per week

Automated the full intake flow for a boutique law firm — form submission to CRM to conflict check to attorney briefing, end-to-end. Every manual handoff eliminated. The team gets time back every single week.

↓ Admin load: 8+ hrs/week reclaimed

Products & systems
built outside of client work.

Ideas taken from concept to working product. Some are SaaS. Some are AI pipelines. Some are business tools. All of them started as a problem worth solving.

AI · Consumer Product
DrawDust

Turns a child's drawing into an animated video — no artistic skill required.

Problem Kids' drawings sit in a drawer and disappear. Parents want to preserve those moments in a way that actually feels alive.
Built An AI pipeline that photographs a drawing, preserves its original style and character, and outputs a short animated video.
Why Consumer AI with a clear emotional hook and a parent demographic that pays for moments. Product-first thinking in a category most AI builders ignore.
AI · Content Automation
PostGoblin

AI content engine that generates platform-native posts — videos, images, memes — built for volume and virality.

Problem Consistent, high-volume content creation is a full-time job. Manual production doesn't scale — most brands either grind or go quiet.
Built An AI system that takes an input — topic, brand, product — and generates ready-to-post content across formats, optimized by what performs, not just what looks good.
Why Treats content as a repeatable system, not a creative exercise. Built for operators who want output, not process.
Lead Gen · Local Business
OKCsite

Productized lead generation system for local service businesses — site, AI answering, and automated follow-up bundled as one deployable package.

Problem Local service businesses get traffic and lose leads. No capture, no follow-up, no conversion logic — just a brochure that ranks.
Built A repeatable product stack: fast-load site, AI phone and chat layer, automated follow-up sequences — pre-integrated and deployable for any local market.
Why Turns a one-off service into a scalable product. Same system, new city, new vertical — deploy and repeat.
Automation · Sales Systems
AI Outreach Agents

Multi-agent pipeline that identifies targets, scrapes context, and sends personalized outbound at scale.

Problem Outbound sales is labor-intensive and inconsistent. Most teams either skip it or send generic blasts that convert at near zero.
Built A multi-agent system that scrapes leads, enriches each with relevant context, and generates and sends personalized outbound messages — human-quality copy, automated execution.
Why Makes systematic, high-quality outbound accessible without a full sales operation. Scales the thing most founders know they should do but don't.
AI · Health Tech
NovaShift

Voice-analysis system that reads nervous system state and delivers a personalized reset protocol.

Problem Stress and mental overload are invisible. Most people can't accurately assess their own state — and generic wellness tools don't help.
Built An AI system that analyzes voice patterns to assess physiological stress indicators, then delivers a personalized recovery protocol based on current state — not generic advice.
Why Early application of voice biomarkers in mental performance — a category getting serious clinical and consumer attention. Built before the trend, not after.
AI · Fintech
DividendPilot

AI scanning system that monitors ETFs and surfaces optimal dividend capture windows automatically.

Problem Dividend capture strategies require precise timing and continuous data monitoring — it's been an institutional play by default. Retail investors can't execute it manually.
Built An AI system that scans ETF dividend schedules, evaluates yield-to-timing ratios, and surfaces actionable entry and exit windows — automated analysis running continuously.
Why Brings systematic dividend strategy to a retail audience. Democratizes an approach that has historically required institutional infrastructure.
Automation · Field Service
Storm Funnel Systems

Rapid-deploy conversion funnels built for roofing companies to capture and close storm leads before the window closes.

Problem Roofing companies have a narrow window after a storm event. Most aren't set up to move fast — leads go cold, competitors win jobs, and the opportunity closes in days.
Built Purpose-built storm-response funnels: fast-deploy landing pages, automated lead capture, immediate follow-up sequences, and team routing — built to go live within hours of a storm event.
Why Timing is the entire product. A roofing company that responds in minutes beats one that responds in hours, every time. This system makes that possible.

I work best with people
who are serious about building.

If you're still deciding whether you want to build something, this isn't the right moment. If you know what you want and need someone who can actually execute it — read on.

You're a good fit if
  • You have a real idea with a real market
  • You want a technical co-founder, not a contractor
  • You value speed and execution over endless planning
  • You're pre-seed to Series A with urgency behind it
  • You've validated the problem or have a strong hypothesis
  • You want someone who thinks about the business, not just the stack
Probably not the right fit if
  • You're still figuring out whether you want to build
  • You need a dev to ship something rough with no plan
  • You're looking for an agency-style relationship
  • You want someone to manage, not someone to lead
  • You have no timeline, no urgency, and no budget awareness
  • You need a yes-man, not a technical partner

Two ways in. One standard.

Regardless of the structure, you get someone who's fully engaged — not a resource on rotation.

Fractional / Contract
On-demand · Defined scope
  • Fractional CTO for teams without a full-time technical lead
  • Specific builds: AI systems, automation pipelines, SaaS MVPs
  • Engagements from two weeks to six months
  • Full technical ownership of the scope, start to finish
  • Best fit: operators with a specific problem and real urgency

Have a real idea?
Let's make it real.

Pre-seed to Series A. Operators with urgency. Founders who want a builder at the table.