Truth boundary
This is an operational diagnostic package, not a real US AI startup client case study, not a testimonial, not a cloud savings result, not runway-extension evidence and not security, privacy, legal, tax, accounting or compliance advice. AICS does not claim SOC 2, HIPAA, ISO, FinOps certification, cloud-provider partnership, funding approval, margin improvement, uptime improvement, AI accuracy, ranking, revenue or guaranteed savings.
Best-fit buying moment
AI bills are hard to explain
LLM/API, embeddings, inference, evaluations, agents, vector databases, GPU jobs and observability spend are spread across vendors and cloud accounts.
Owners are unclear
Finance can see invoices, engineering can see workloads, but product, customer segment, experiment status and shutdown criteria are not tied to named owners.
Tool decisions are stalled
The team is comparing native AWS, Azure, Google Cloud, FinOps platforms, LLM observability tools, advisers or internal dashboards without a shared evidence pack.
Board or founder review needs discipline
The business needs a practical monthly CFO/CTO queue for actions, specialist questions, risk notes, tagging gaps and next sprint decisions.
Diagnostic deliverables
| Deliverable | What it helps decide |
|---|---|
| Spend-source inventory | Which AWS accounts, Azure subscriptions, GCP projects, Kubernetes namespaces, LLM vendors, GPU providers, vector databases and SaaS invoices need review. |
| Owner and product allocation map | Which rows have founder, CFO, CTO, product, engineering, environment, customer-segment and shutdown-owner coverage. |
| AI/cloud evidence boundary checklist | Which evidence can be reviewed safely using exports or screenshots, which secrets or personal data should be redacted, and which formal decisions stay with qualified advisers. |
| CFO/CTO decision queue | Which items are ready for tagging cleanup, architecture review, tool evaluation, commitment planning, vendor review, shutdown review or specialist advice. |
| One-page review dashboard spec | Fields needed for a monthly owner cadence: source, service, product, owner, variance, risk note, action, status, due date and next review. |
Inputs AICS can work from
- Read-only billing exports, invoices, screenshots or summarized usage reports.
- LLM usage exports, GPU utilization snapshots, Kubernetes namespace summaries and observability cost views.
- Product, customer-segment, environment, experiment, demo and research labels where available.
- Existing FinOps, accounting, security, legal, privacy or engineering notes that the buyer is authorized to share.
Use this before another platform purchase or optimization sprint.
The package turns scattered AI/cloud spend evidence into an owner-reviewed queue without pretending to replace cloud tools, FinOps platforms, LLM observability, engineers, accountants, lawyers, auditors or security advisers.
More AICS resources · AI spend board review checklist · LLM/GPU spend owner dashboard demo · US AI startup FinOps comparison · Request scope