GreyScape.ai

Solutions · AI Budget Control

AI budget control for the whole organisation

Set budgets, attribute spend, and gate new workloads with a one-minute approval flow. Built for IT, FinOps, and Finance teams who want OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, and Vertex AI spend to behave like every other line of the P&L — predictable, attributable, governable.

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Why AI budget control matters

AI spend is the fastest-growing, least-governed line in your P&L

Most finance teams discover AI spend the way they used to discover SaaS — through a frantic mid-quarter call from the CFO. Provider bills land monthly, they reference team-level keys with names like production-key-2, and there's no way to chase a $40,000 line item back to the engineer who launched it. By the time procurement gets involved, the company has signed three overlapping vendor contracts and is hitting the next tier on each one.

Traditional FinOps tools were built for cloud, not AI. They assume usage data is tagged at source, that costs are visible per-resource, and that you control the underlying infrastructure. None of that holds for AI providers — the usage tagging is whatever the engineer named their key, the cost-per-token unit is a moving target as model prices fall, and there is no resource you control. AI budget control has to start one layer up: attribute spend to people, gate new workloads with light-touch approvals, and set right-sized budgets as guardrails. That's the entire shape of what GreyScape.ai does.

How it works

Four pillars of AI budget control, in one product

No single control prevents AI overspend. Budgets without attribution become noise. Approvals without budgets become theatre. Attribution without forecasting tells you the damage after it's done. We run all four together.

1 · Per-team and per-user budgets

Set monthly budgets at three scopes: per user, per team, per workload. Soft alerts at 50% and 80%; hard alerts at 100%. Carry-over or reset is your choice. Budgets work across providers — one budget can cover OpenAI plus Anthropic plus Azure OpenAI spend for a single team.

See the budget surface

2 · Per-person cost attribution

Every dollar of AI spend is attributed to a person via API-key naming convention, SSO mapping, or explicit team tagging. Powers the per-user dashboards your CFO actually wants to see — sorted, ranked, and exportable to your accounting system for chargeback.

See attribution scenarios

3 · One-minute approval workflow for new workloads

When an engineer wants to launch a new AI workload, they describe it in three sentences. The advisor recommends a model, estimates monthly cost, and routes it to the right approver — IT for security, finance for spend. Decisions in under a minute, archived in the audit log.

See the approval flow

4 · Forecasting and anomaly detection

Run-rate forecasts to month-end, model-mix shifts (eg. an engineer accidentally switching from a cheap model to a flagship one), and per-key spike alerts. Catches the $40,000 forgotten cron-job before the bill lands, not after.

See anomaly detection

Coverage

Every AI provider that bills you, under one budget

AI budget control works across all the providers most organisations consolidate on. Today you can connect: OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Google Vertex AI, Manus, GitHub Copilot. Plus the long tail captured through shadow AI discovery — Midjourney, Suno, Perplexity, Cursor, Replicate, ElevenLabs, Runway, v0, Lovable, and the rest. One budget; many providers; clean per-user attribution.

See the full integrations list →

Outcomes

What AI budget control unlocks for your finance function

A defensible AI spend number

The single answer to “what did we spend on AI this month?” that survives audit, board questions, and your next funding round. Including the shadow AI tools that aren't on your provider list.

Right-sized budgets that grow with the team

Start with last quarter's actuals as the budget baseline, then ratchet up or down based on per-user trends. The dashboard tells the story; you make the call.

Chargeback that finance will actually run

Per-team and per-user totals export to your accounting system in formats finance can drop into existing chargeback flows — no rebuild required.

Approval audit trail for compliance

Every new AI workload approval is logged with the requester, approver, advisor recommendation, and decision rationale. Useful for SOC 2 change-management evidence and EU AI Act Article 13 transparency obligations.

Start controlling AI spend this week

Connect a provider key, name your scopes, and you'll see real spend, real attribution, and your first budget in under an hour. Read-only on day one. No procurement required.

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Frequently asked

AI budget control — common questions

What is AI budget control?

The combination of budgets, cost attribution, and approval workflows that turn AI spend from an unpredictable monthly surprise into a governable P&L line. In practice that means per-team and per-user budgets, alerts before you overspend, attribution of every dollar to the person who drove it, and a lightweight approval flow for new workloads.

How is AI budget control different from cloud FinOps?

Cloud FinOps assumes you control the infrastructure and that resources are tagged at source. Neither holds for AI providers — you don't control the model, and tagging is whatever the engineer named their API key. AI budget control has to start with attribution and approvals rather than resource-level cost analysis.

Which AI providers does GreyScape.ai cover?

OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Google Vertex AI, Manus, and GitHub Copilot today, plus the long tail of consumer-tier tools captured through shadow AI discovery (Midjourney, Suno, Perplexity, Cursor, and many more). Budgets work across all of them.

Can I set budgets per project or per workload, not just per team?

Yes. Budget scope has four levels: organisation, team, user, and workload. Most customers start at team-level for predictability, then add per-user caps for the heaviest spenders.

What happens when someone hits their budget cap?

By default we alert — at 50%, 80%, and 100% — but we don't gate API calls. Hard gating happens at the provider level (eg. OpenAI's organisation-level limits). Many customers prefer alerting because gating mid-workload breaks production. Both modes are configurable.

Does AI budget control work with my existing finance tools?

Yes. Per-team and per-user totals export to CSV, JSON, or directly into accounting systems. Approval audit trails export the same way. The aim is to feed your existing month-end close, not replace it.

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