01
Reuse approved work
Start from current answers and procedures when the company has already resolved the task.
Solutions / AI Cost
Stop paying every AI app to solve the same work again.
Lower cost by reusing approved answers and procedures, sending less unnecessary information, sharing infrastructure, and using expensive models only when the work requires them.
- System
- Workload economics
- Focus
- Reduce the work before the model.
- State
- Route measured
- Output
- Predictable spend
ECO-610Route measured
Start with the bill. Find the repeated work underneath it. Measure what changes.
The model invoice is only part of the cost. Repeated data retrieval, tool calls, retries, duplicate integrations, repeated application work, quality testing, operations, and manual review all add to what one AI task costs the company.
Tribble reduces avoidable work across that path while preserving the required quality, evidence, and company rules. Savings depend on the workload, so every production proof begins with a measured baseline.
02
Send less
Give the model only the facts and evidence the request actually needs.
03
Use the right model
Reserve stronger, more expensive models for work that actually needs them.
04
Share the foundation
Reuse data connections, company rules, quality checks, system monitoring, and deployment controls.
One costly workload reveals the repeated work underneath the model bill.
Measure the current path, remove avoidable retrieval and calls, then compare approved alternatives against the same quality bar.
Baseline
Measure
Map current task, token, tool, retry, and operating cost.
Brain
Reuse
Identify repeated context and procedures.
Relay
Route
Compare approved ways to run the task against the same quality bar.
Proof
Evaluate
Confirm cost, latency, evidence, and answer quality.
Map one high-cost workload and establish a credible baseline.
In one working session, we map the current applications, model spend, repeated work, and the first result worth proving. You keep the map either way.