AI coding savings inside a regulated perimeter.
Healthcare and life-sciences engineering teams face tight rules on where code and data can go. Routing routine work to self-hosted models can cut cost and reduce what leaves your network.
The challenge
What makes providers, payers, and pharma different.
01
Tight data rules
Code that touches patient data often may not reach external APIs. Worker models can run inside your environment.
02
Validated processes
Regulated software needs documented, reproducible development. Routing logs support that record.
03
Legacy systems
Older clinical and claims systems are large and costly for agents to read.
Where the tokens go
Work we route to cheap models.
- Reading large legacy systems
- Test generation
- Interface and integration boilerplate
- Documentation for validation
- Repo-wide impact analysis
- Upgrade scaffolding
Tools we route
Routing runs inside your environment — your cloud account, your data center, or an isolated network.
- Self-hosted worker models for code near patient data
- A log of which model produced every routed change
- Access controls through your identity provider
- Documentation to support validated development
Recommended path
How engagements typically unfold.
Start where the value is clearest. Most clients begin with a spend audit, then route one team before rolling out.
Start the conversation
Stop paying frontier prices for routine work.
Tell us which coding tools your engineers use and roughly what you spend. We'll show you where the tokens go and what routing would change.
We respond within 1 business day. Mutual NDA available before any data discussion.