Who We Are
Builders. Not Consultants.
AI Labs was born from 1,265 stuck points, six weeks of 18-hour days, and the realization that making AI work for a specific business is the hardest part. We already did the hard part.
1,265 Stuck Points
Our founder spent six weeks -- 12 to 18 hours a day -- building AI systems for his businesses. He wasn't starting from zero. He was already using ChatGPT for research, audio compilers to generate notes, LLMs as thought partners for analysis and brainstorming. He knew what AI could do. That wasn't the problem.
The problem was making AI do what he needed, consistently, for his specific business, without the context window resetting and giving phantom results. Everything he built in a ChatGPT conversation disappeared when the context reset. Nothing connected to his actual tools. Nothing remembered what he taught it yesterday. Nothing deployed.
So he went all in. Six weeks. 12-18 hour days. Nothing else. And he kept taking screenshots every time he got stuck -- when a build crashed, when an integration broke, when adding one thing caused three things to fail. Architectural drift. Frankenstein bolt-on projects. Code that worked yesterday and didn't today.
After six weeks he had 1,265 screenshots. That's 1,265 stuck points. That's the tax anyone pays who tries to go from "AI can do this" to "AI is doing this for my business, on my terms, every day."
What came out the other side: Agent Orchestra -- a platform with recursive learning, self-repair systems, and voice integration, three memory systems, and a full creative pipeline. A platform that now builds and deploys AI agents for clients in weeks instead of months.
Our founder used the platform to replace his graphics design and marketing employee. He replaced his controller. Not hypothetically -- actually. The same platform AI Labs deploys for clients runs our founder's own businesses every single day.
Resend dashboard — "Delivered"
Sunday night, 8:47 PM
The Finish Line
Resend email dashboard showing "Delivered" on a Talent Optimization Report. Sunday night at 8:47 PM. The system works.
GitHub commit f83dc78
d_nat crash fix
The Grind
GitHub commit f83dc78 -- fixing a d_nat crash in route.tsx. "UNIVERSAL RECEIVER: Forces data to exist so the d_nat crash stops." Stuck point #847.
GitHub commit f52dabd
+28 / -38 lines
The Rewrite
GitHub commit f52dabd -- +28 lines added, -38 lines removed. Ripping out what didn't work. Replacing it with what did.
Our Values
Ship It.
Working AI beats perfect plans. We deploy in weeks, not quarters. Get it live, get feedback, iterate.
Own It.
We build it, deploy it, and make sure it actually works. If something breaks, our platform catches it at 3 AM and fixes it before you wake up.
Say It Straight.
If AI isn't the right answer for your problem, we'll tell you. We'd rather lose a deal by being honest than win one with a promise we can't keep.
By the Numbers
These are our real numbers from the same platform we deploy for clients. Not vanity metrics.
What We Run On
We eat our own cooking. Here's the production stack that powers AI Labs and our clients' businesses every day.
Multi-Model AI
Grok, Claude, GPT-4 -- cascading between providers for reliability, cost optimization, and best-fit task routing. Never locked into one vendor.
Voice AI
Real-time conversational AI on actual phone calls. Native telephony integration with zero transcription lag. Custom voice personas per brand.
Semantic Memory
Every agent learns from interactions. Vector-based memory that gets smarter over time without retraining. Teach it once, it remembers forever.
Self-Repair
Our agents detect issues, log bugs, and kick off automated repair sessions. Systems that fix themselves before you even notice a problem.
Microservice Architecture
10 operational sheds running independently. If one module needs an update, the rest keep running. No single points of failure.
Recursive Learning
Agents don't just follow instructions -- they learn from feedback. Correct an agent once, and it remembers across all future interactions.
Want to Build With Us?
We have clients who need AI agents built. You have the skills. Our platform generates 70% of the architecture. You handle implementation -- connecting client systems, testing workflows, building custom components. We handle sales, client management, and ongoing support.
Compensation: Competitive compensation with revenue share on every client you build for. No sales calls. No client management. Just build.
If you're a developer who wants to build real AI systems for real businesses without the overhead of finding clients or managing accounts, this is the deal.
Want to Work Together?
See What We'd Build
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Join The Bullpen
Build AI agents for real clients. Competitive compensation, revenue share, no sales calls.
Apply to The Bullpen