Spending caps
Limits per project and per seat are enforced in code, so there are no surprise bills.
Solution
From training to measurement,
one team covers the whole path of adoption.
01 / EDU · VIBECAMP
Onboarding training
It starts with learning to define your own work as AI work. You see what the training changed in the records, not by guesswork.
vibecamp.us ↗ 02 / PRODUCTWork-Agent AI work pipeline
Run AI work on the web, CLI, or desktop with a single company account. Outputs and their sources are recorded automatically.
See the product lineup ↓ 03 / MEASUREWork-Metric AI impact measurement
Spending caps, cost tracking, model policies, and measure-then-reduce. We use data to find usage that isn't working and cut it.
Preview a sample report (Korean) →BEFORE · TODAY
A different personal account for every employeeA different AI service in every departmentNo record of what was runPayments and costs scattered everywhere
AI work and spending end up fragmented across the company.
AFTER · UNIFIEDWork-Agent: the Baryon AI work pipeline
✓Onboarding: see who has completed how much
✓Work-Knowledge · connected company knowledge: work gets done faster
✓Impact measurement: find the agents that actually work
Getting the most out of AI cost savings: spending caps, cost tracking, model policies, and the 6-step pipeline
Maximizing AI cost savings
Cost tracking
Spending is tallied automatically by task and by agent, so you can see where the money goes.
Model policies
Locking expensive models and setting the order in which models are used prevents unnecessary overuse.
Measure → reduce
Run data shows which usage isn't paying off, so you can cut it.
- 01Task
- 02Run
- 03Output
- 04Review
- 05Measure
- 06Scale up
Run log · automatic
Source citations · traceable
Cost tracking · per project
Output history · archived
Next
Where should your company start?
Tell us which AI tools you use today and which tasks you repeat, and we'll work out with you which step of the pipeline above to start from.