AI · 27 min read
Meter
Your AI bills are out of control. Let's put a meter on them.
The right model for each task, with limits and monitoring in place.
See pricing- SummariesSmall model
- Support repliesMid-size model
- Contract reviewLarge model
Cost limit
Who it's for
Who Meter is for
For products already running AI features (chat assistants, summaries, search or agents) whose AI bill grows faster than their users. Meter suits teams on OpenAI, Anthropic or other model providers who want the right model for each task, caching where answers repeat, and limits that stop runaway costs.
Works with apps built in
- Claude
- ChatGPT
- Replit
- Bolt
- Lovable
- v0
- Cursor
- Figma
- Supabase
- Firebase
- Vercel
What's going wrong
Signs you need Meter
- The largest model handles every request, simple or not
- The same answers are generated again and again
- No limit stops a runaway loop or a heavy user
- Nobody can say which feature drives the bill
What you get with Meter
- A review of AI usage and cost by feature
- The right model chosen for each task
- Caching where answers repeat
- Usage limits and fallbacks
- Cost monitoring and alerts
- A written savings plan, and the changes made
How it runs
How Meter runs
- First: we review how your app calls AI models
- Then: you receive the written savings plan
- Next: agreed changes are made and tested
- After: monitoring stays in place so spikes are caught early
Agents involved
ScoutMaps a codebase or idea and drafts the Scan reportBuilderWrites code to the agreed BlueprintKeeperWatches live apps for errors, downtime and AI cost spikes
Signed off by a TechTose architect.
Related reading
Guides for Meter
Meter: questions
Will answer quality drop?
Model changes are tested against your real tasks before they ship. Where a smaller model isn't good enough, we keep the larger one.
Which AI providers do you work with?
The providers your app already uses. The plan covers model choice per task, whichever provider that is.
How much will we save?
That depends on how your app uses AI. The written savings plan sets out what can change before anything is built.
AI tools are everywhere. Teams running them reliably in production are still rare. We're one of them.
See how a Scan works