Manage model, phone, and throughput cost without losing the business metric.
Track model usage, phone usage, throughput, and evaluations in one place. Set budgets, compare models, and use evals to decide when a smaller or open-source model is good enough.
That is how teams stay model agnostic, keep ROI visible, and save money without guessing which quality tradeoff is acceptable.
| Metric | GPT-5 mini | GPT-5 nano | GPT-OSS 120B Fireworks | GPT-OSS 20B Fireworks |
|---|---|---|---|---|
| Total Cost | $0.659436 | $0.225682 | $0.542208 | $0.390457 |
| Avg Request Duration | 14.020s | 11.986s | 10.805s | 10.908s |
| Total Tokens | 1,374,832 | 1,654,896 | 3,304,304 | 5,248,592 |
| Total Error | 0 | 0 | 0 | 0 |
| Total Calls | 376 | 392 | 536 | 616 |
| Percentage Passed | 81.12% | 73.72% | 71.27% | 55.84% |
Budgets and quality need to live in the same system
If model spend, phone spend, and throughput live in separate tools, teams optimize the wrong thing. BotDojo keeps cost, quality, and ROI visible together.
Budgets across model, phone, and throughput
Track LLM usage, telephony spend, and workflow volume together so budgets can be set before cost drifts.
Model-agnostic evaluations
Compare frontier, smaller hosted, and open-source models against the same workflow and the same eval suites.
ROI tied to the workflow
Measure quality, cost, call outcomes, and operator time saved against the business result that matters.
Evaluate before rollout, monitor after rollout, and route for cost with evidence
The goal is not just to ship a better prompt. The goal is to know which model should run which task, what it costs across model and phone usage, and whether the change moved the business KPI.
Run golden sets, regression checks, and rubric-based tests before you promote a change into production.
Track production quality, latency, safety, phone usage, and user outcomes continuously so problems show up as signals instead of surprises.
Use the eval results to decide when a smaller or open-source model is good enough, then route work there with evidence.
Save money by using the right model for the right work
BotDojo stays model agnostic, so you can compare frontier models against smaller and open-source models in the same environment. When the evals say the cheaper model is good enough, you can route the work there with confidence.
ContactWorks used BotDojo evaluation tools to identify tasks that could move to faster, cheaper models without sacrificing accuracy, cutting model costs by an additional 8x.
Track model, phone, and throughput
See model choice, phone usage, cost, latency, errors, and tool behavior at the workflow level instead of guessing where spend drift came from.
Set budgets and alerts
Budget against model usage, phone usage, and throughput so the team can act before overages become the story.
Save money with eval-guided routing
Once the pass rates are visible, move lower-risk work to cheaper models and keep higher-cost models only where they earn the spend.
Evals are only useful if they show up in real operating outcomes
These customer stories show the different ways BotDojo uses evaluations to improve quality, compress time, and prove the business case.
ContactWorks
BotDojo evaluation tools identified which tasks could move to faster, cheaper models without sacrificing accuracy.
Onramp
Structured merchant evaluation workflows prove quality and consistency while compressing underwriting time from hours to minutes.
Miva
Evaluation workflows verify response quality, surface outdated documentation, and keep answers grounded in source material.