LP Diligence
What is AI actually costing your portfolio companies?
Full-stack cost per outcome per workflow. Not just LLM bills. Total cost including compute, embeddings, infrastructure, retries.
Responsible AI
Every AI agent runs on compute. An agent that retries five times uses five times the electricity for a single outcome.
botanu measures the cost-to-outcome of every agent, every retry. Cutting AI waste cuts emissions. The same data layer is the foundation for Scope 3 disclosure under ISSB and EU CSRD.
The Pillars
LP Diligence
Full-stack cost per outcome per workflow. Not just LLM bills. Total cost including compute, embeddings, infrastructure, retries.
LP Diligence
5-10x cost scaling tracked in real time. Budget alerts, cost anomaly detection, P99 tail risk analysis, and threshold-based governance.
ESG & Emissions Alignment
AI compute has a carbon footprint. By reducing retries and waste, botanu directly cuts Scope 3 emissions from portfolio AI use. Measurable, reportable, aligned to ISSB and EU CSRD.
Governance & Auditability
Every AI action is logged with full provenance: which model, which vendor, which retry, at what cost. GPs get a complete audit trail ready for LP diligence at any time.
ILPA RAI Guide
Real-time cost monitoring, outcome measurement, vendor attribution, audit trails, and threshold-based alerts across the portfolio.
Foundation
Most responsible AI frameworks ask the right questions but leave GPs with qualitative answers. botanu provides the data layer that turns policy commitments into evidence.
When an LP asks how AI costs are controlled, botanu doesn't offer a policy document. It offers a live dashboard. When an auditor asks about AI risk, botanu doesn't describe a process. It exports a log.
This is the difference between responsible AI as a promise and responsible AI as a practice.
Responsible AI isn't a policy statement. It's a measurement system.