Our approach to AI
AI is a tool, not a product category. We use it when it's the best way to solve a problem — and skip it when it's not.
We use AI to build faster
Our build velocity has accelerated dramatically. Projects that used to take weeks now ship in days. We're not embarrassed about that — we're excited.
We use AI inside our products
Six of our projects integrate LLMs, image generation, or intelligent automation. In every case, the AI solves a specific problem — it's not a checkbox feature.
We self-host when it matters
Some clients need air-gapped systems. Some need data to never leave their building. We've built AI-powered tools that run entirely on local hardware with no cloud dependency.
We don't trust AI blindly
Every line of AI-generated code gets reviewed. Every LLM output gets validated. The AI proposes; a human decides.
AI doesn't replace taste
Knowing what to build is harder than building it. AI makes the building faster — it doesn't tell you what's worth building.
The cost curve is our friend
What was expensive last year is cheap this year. We design systems that ride that curve — swapping models, adjusting context windows, choosing the right tool for the right job.
We're practitioners, not evangelists
We won't pitch you an "AI strategy." We'll build you something that works and show you why AI was — or wasn't — the right choice for each piece.
What we work with
Specific tools, models, and hardware we have hands-on production experience with.
NVIDIA hardware
Running inference models on local NVIDIA hardware — RTX consumer GPUs and DGX Spark workstations. Real deployments, not cloud rentals.
Workflow integration
Integrating AI into real workflows — both human-in-the-loop processes and fully autonomous OODA loops that observe, orient, decide, and act without waiting for a person.
Text & language models
Production experience across the major open and commercial model families. We pick the right model for the job — not the most expensive one.
Image generation models
Running image generation locally and via API. From product photography to creative assets — real output, not demos.
AI in our projects
Six public projects use AI in production. Here's what it actually does in each one.
Manta Make
AI-powered web IDE that builds and previews apps in real time
How AI is used: LLM generates, compiles, and previews full applications inside a browser-based IDE.
Vivid
Lightweight AI image generation with a simple web UI and REST API
How AI is used: Image generation models behind a clean interface — no prompt engineering degree required.
AI-powered CMS
A monorepo where LLMs build, containerize, and deploy web applications
How AI is used: LLMs commit code, trigger CI/CD, and deploy containers. Humans review and approve.
ZimContext
Serve offline knowledge bases to humans and LLMs with MCP integration
How AI is used: Bridges offline ZIM archives to LLMs via Model Context Protocol — fully air-gapped.
Careful Sort
Automated Shopify collection sorting by 30+ signals
How AI is used: Signal weighting and scoring algorithms — AI-informed design, deterministic execution.
GoodCart AI
Shopify CRO tool with charitable donation selection
How AI is used: Intelligent product matching and conversion optimization with LLM-assisted recommendations.
What we don't do
Need AI that actually works?
We'll tell you honestly whether AI is the right tool for your problem — and if it is, we'll build it, deploy it, and make sure it keeps working.