Same output, proven on your code.
Cheaper is only useful if the work is still right. We run routed and unrouted sessions side by side on your own tasks, check both against your tests and review standards, and keep any job on the frontier model where the cheap route falls short.
You keep
- Task test set built from your own repositories
- Routed vs. unrouted comparison report
- Per-job quality gates
- Routing log with the model behind each change
Who it's for
Built for teams paying real money for AI coding tools.
- Teams that won't accept a cost cut that shows up later as bugs.
- Engineering leaders who need evidence before they approve a rollout.
- Regulated organizations that must document how AI-generated code is produced.
The problems we solve
- 01
Quality regressions surface late
A cheaper model that is slightly worse shows up weeks later as rework. The check has to happen before rollout.
- 02
Public benchmarks aren't your codebase
Leaderboards say little about your languages, frameworks, and conventions. The test set should come from your own backlog.
- 03
No record of what ran where
When something breaks, you need to know which model produced which change.
Process
How the engagement runs.
Clear stages, explicit decision gates, and an artifact at every step — so progress is visible and nothing depends on trust alone.
Step 01
Pick real tasks
Assemble a test set from recent tickets and pull requests in your own repositories.
Step 02
Run both ways
Execute each task routed and unrouted under the same conditions.
Step 03
Check the work
Compare against your tests, builds, and review standards, with engineer spot-checks.
Step 04
Set gates
Keep a job on the cheap route only where it meets the bar; send the rest back to the frontier model.
Step 05
Log it
Record the model behind every routed change so it's traceable later.
Deliverables
What you own at the end.
- Task test set built from your own repositories
- Routed vs. unrouted comparison report
- Per-job quality gates
- Routing log with the model behind each change
Typical outcomes
What changes for your business.
- Evidence, not assurances, that routed work meets your standard.
- Quality gates that keep protecting you as models and prices change.
- An audit trail for AI-generated code.
FAQ
Questions leaders ask us.
Does this slow down rollout?
It runs before and alongside the pilot, so the first team is protected from day one and wider rollout is backed by data.
Other services
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.