Tailor open-source tools.
An open-source AI tool already exists for most work. Capable in a demo, short of the auth, data, policies, and scale a real business needs. The tailored deployment closes that gap.
The tool already exists. The tailoring closes the gap to production.
The open-source AI ecosystem has filled out. Hundreds of tools you can run on your own servers, each for a specific job: chat, retrieval, agents, document processing, transcription, internal search.
Each one runs as a demo out of the box. Production-ready inside a real business is a different distance.
The work worth tailoring.
Most AI work sits on top of open source that already does the heavy lifting.
An existing tool covers the core.
The capability is solved by something already public. The work that remains is the gap to your business.
The specifics are yours.
Your data sources, your auth, your policies, your brand, none of which come in the download.
Production, not demo.
Logging, monitoring, backups, scale-testing, the parts a demo skips.
The download is a demo. Production needs more.
The tool arrives with the capability. Tailoring adds the layers a business actually runs on.
Data connectors
Your data sources in place of generic loaders.
Authentication
Your single sign-on, your identity provider, your roles.
Branding
Your mark inside the UI. It reads as your product.
Policy layer
Guardrails for PII, role-based access, audit logs, retention.
Model choice
Frontier model where the work earns the cost. Open-weight model on your servers where it doesn’t.
Production hardening
Logging, monitoring, backups, scale-testing.
Two ways to run AI inside a business. One keeps your data home.
AI in a vendor cloud is convenient. A tailored open-source tool runs on your own servers, under the policies you already wrote.
A working version every week. Live in weeks.
Short cycles. Each week ends with the tailored tool running on your data. Deployed on your own servers in weeks.
Evaluate
We map the work and the open-source tools that fit. We test the most promising ones against your data.
Tailor
We take a copy of the tool. Wire it to your auth, your data sources, your model. Apply your policies.
Demo
You see the tailored tool running on your data, inside your perimeter. We walk through what works and what to refine.
Ship
Deployed on your servers. We hand over the copy of the tool, the docs, and the steps to pull in future updates.
Connected to what you already run.
The tailored tool ties to your existing stack: your identity provider, your data sources, your storage, your monitoring.
Anything with an API connects directly. The rest connects through the systems that already link your tools.
The open-source AI ecosystem we deploy from.
Mature tools where they fit. Each one tested in real deployments. The right answer is whichever one already does the work.
You own
everything.
The copy of the tool, in your code repository. The deployment, on your infrastructure. Docs written for your engineers. Future updates pull in cleanly, by your team or by us, your call.
Let's talk about the work.
Book a call with the founders. We listen first. Then we come back with what we'd build.