AI Cost & Carbon Baseline
Understand what your AI workloads cost, and whether that spending creates business value. GreenPilot combines cost, estimated carbon impact, quality, and business outcomes in one business-readable assessment.
Scoped for AI workloads running on AWS, Azure, and Google Cloud — including managed AI services, LLM APIs, and cloud-hosted model inference.
Your AWS bill isn't the only cloud cost that's hard to see anymore.
AI/LLM spend is growing fast and is rarely attributed to a team, workflow, or business outcome. Most mid-market companies have no dedicated practice for it — the same gap GreenPilot already addresses for AWS infrastructure.
Opaque token spend
Input, cached input, output, reasoning, and tool calls all bill differently. One user action can trigger several models and retries without anyone noticing the cost.
No attribution to teams
Without tagging and quotas, nobody can say which team, product, or use case is actually driving the bill — let alone whether it's producing business value.
Carbon claims without evidence
Most "AI carbon" numbers on the market don't disclose whether they're measured, provider-allocated, or modeled. That distinction matters, and it's usually missing.
Dashboards without policy
Observability tools show you the numbers. Few help you turn that into budgets, model-selection rules, and quotas your teams actually follow.
A 30-day assessment, delivered as a report — not another dashboard to maintain.
GreenPilot runs the assessment; you get a structured report and a set of policies you can act on immediately.
Import usage data
API logs and cloud billing exports, read-only.
Attribute spend
See which teams, workflows, and models actually drive cost.
Identify waste
Unnecessary context, missing caching, retries, and premium models used for simple tasks.
Estimate carbon impact
Using EcoLogits and provider methodology, every figure labeled by evidence quality.
Deliver the report
Savings, emissions, and governance recommendations your finance and sustainability teams can use.
Every number is labeled by where it actually came from.
AWS does not provide unified request-level cost attribution today — Bedrock invocation metadata, for example, doesn't appear in Cost Explorer or your bill. GreenPilot reconciles these as separate evidence streams and never blurs the line between them.
Measured
Direct billing or usage data from the provider itself — AWS Cost Explorer, CUR, and equivalent sources. Used as-is wherever it's available.
Provider-allocated
Data a provider allocates at the account or service level, not per request — used as their own allocation, clearly labeled as such, not presented as a direct measurement.
Modeled
Where no direct data exists — per-token carbon impact, for example — GreenPilot estimates using recognized methodologies like EcoLogits, and labels the result as modeled, never as measured.
Start with a conversation
This is a paid 30-day engagement. Pricing is defined after an initial scope review — there isn't a fixed number published yet, because there isn't enough validated demand yet to justify one. If your team runs meaningful AI workload spend and wants a business-readable view of what it costs and what it's worth, get in touch.
info@greenpilotai.comCurrently onboarding a small number of design-partner engagements. English-language delivery.