SERVICE · CUSTOM AI
For the problem that fits no template.
When your problem does not match an off-the-shelf tool, the Lab designs and builds the system for it — specced up front, built fast, and handed off as something you own and can run.
The problem
Some problems do not fit a template. The workflow is unusual, the data is yours, or the value is in exactly the part a generic tool will not do.
That is where a custom build earns its keep — a system designed around your problem, not bent to fit someone else's product roadmap.
What you get
- A system designed around your specific problem, from data and integrations to the interface your team uses.
- A fixed-scope spec agreed up front — what gets built, what it costs, and when it ships.
- Observability built in, so you can see what the system is doing in production.
- Documentation, a walkthrough, and a bounded support window — then you own it outright.
How it works
Discovery call
Thirty minutes on your problem and whether an AI system actually fixes it. If it does not, you will hear that.
Fixed-scope spec
What gets built, what it costs, when it ships — no open-ended retainers.
Build and ship
A working system, deployed with observability built in, iterated against real use.
Handoff
Documentation, a walkthrough, and a bounded support window. You own the result.
Where it fits
Full-stack AI products
Search, retrieval, and LLM pipelines wired into a real product — the kind of build behind the Lab's own tools.
Multi-agent operations
Systems where several agents carry work end to end, constrained by deterministic rules and human approval gates.
Bespoke internal tools
The internal system that no vendor sells, built around how your team actually works.
Proofs that had to work
Reliability comes from constraining the system, not from a smarter prompt — a lesson baked into every build.
Proof from the Lab
Mojo: a 7-agent WhatsApp ops system.
A two-person creative team needed agency-scale output. Mojo is a 7-agent orchestration system running real client work, built in 36 hours.
Read the case studyCreativePromere: a prompt intelligence platform.
The intelligence layer under AI image prompts. Search, reverse-engineer, organize, and connect prompts across models, built and operated by the Lab.
Read the case studyGrowth & GTMMarketMinute: cited GTM strategy in two minutes.
Research-backed go-to-market strategy in under two minutes, with every claim cited to a real source pulled from Reddit, Twitter, and YouTube.
Read the case studyQuestions you might have
How do you scope a custom build?
It starts with a discovery call and a fixed-scope spec: what gets built, what it costs, and when it ships. No open-ended retainers.
Do we own the system at the end?
Yes. You get documentation, a walkthrough, and a bounded support window, then you own and run it.
What if AI is not actually the right answer?
You will hear that on the discovery call. The Lab is run by an operator who has carried a P&L, not someone selling AI for its own sake.
Have a problem that fits no template?
Bring it to a discovery call — you will get an honest read on whether a custom system is worth building.