The cost-to-outcome platform for AI builders
Measure what every AI workflow delivers
and what it costs.
botanu measures whether AI workflows deliver results, identifies the ones that break, and gives engineering teams the data to fix them. Full-stack cost tied to every outcome, every customer.
Built by experts from
The LLM bill is one line item. The actual cost of an AI outcome includes compute, orchestration, embeddings, storage, and data pipeline spend. Without measuring what each outcome cost and whether it succeeded, there is no way to know if AI is worth deploying.
Why botanu
You don't have a cost tracking problem. You have a cost-to-outcome problem.
at the workflow level
Tracing tools log spans. botanu evaluates whether the workflow achieved its goal, calculates what it cost across every service involved, and shows whether cost-to-quality is improving or degrading over time.
/workflows
Cost per outcome by workflow. See which features create ROI and which ones don't.
/infrastructure
LLM, compute, embeddings, and pipeline costs attributed to each run
/attribution
Every AI call traced to the outcome it produced, the customer it served, and the cost it generated.
/margins
Daily alerts when cost-per-outcome spikes or success rates drop. Catch degradation before it hits renewals.
Why AI ROI is hard to measure
The LLM bill is 40% of the cost
Teams deploy AI to resolve tickets, generate reports, and qualify leads. Without per-workflow cost data tied to actual outcomes, there is no way to know if the workflow is worth running.
Averages hide the runs that break
The blended cost per outcome looks fine. But P50 and P99 costs can differ by 20x. The outlier runs fail silently and cost 20x more, invisible until botanu surfaces them.
Outcomes and cost live in different systems
Your observability tool shows traces. Your infra bills show spend. Neither tells you whether the outcome was achieved or what it cost to produce. Connecting the two takes a week of spreadsheet work, per customer.
Beyond LLM cost tracking
| Traditional | botanu | |
|---|---|---|
| Measure outcome success and cost per workflow | ||
| Correlate full infrastructure stack | ||
| See which workflows fail and which cost more than they deliver | ||
| Attribute costs across LLM + cloud + data | ||
| Real-time cost-to-outcome tracking per workflow | ||
| No proprietary agents, just OpenTelemetry |
Use Helicone, Langfuse, or Datadog for tracing and monitoring. Use botanu for outcome measurement and cost-to-quality optimization. They're complementary.
Simple pricing. Start today.
Starts small for startups and scales for enterprises. Includes outcome measurement, full-stack cost attribution, and alerting.
Book a demoWhat we're hearing
“We sell per resolved ticket. But our costs fragment across five vendors, and nobody can tell me what a single resolution actually costs for a specific customer. The board asks about gross margin per account and we're guessing.”
Works with your entire AI stack
See it on your data. 20 minutes.
Book a demo. We'll walk through:
- Outcome measurement and full-stack cost per workflow
- Which workflows deliver results and which ones break at scale
- Threshold-based alerts for cost spikes and quality degradation, daily