AI cost governance for enterprises that can't afford shadow spending
56% of AI tool spending happens outside IT budgets (IDC). Your teams are calling OpenAI, Anthropic, and Google APIs across dozens of features — and nobody owns the bill. AI Vyuh FinOps gives finance and engineering a shared source of truth for every dollar spent on LLM inference.
Multi-team cost attribution
Know exactly which team, feature, customer, or agent is driving your AI spend. Attribution at every level of your organization — from individual API calls to quarterly P&L.
Team-level dashboards
Each team sees their own AI spend in real time. Product, engineering, data science, and customer support each get a dedicated view showing cost per feature, model, and time period. Finance gets the roll-up.
Feature-level cost tracking
Tag every LLM call with the feature that triggered it. See that your AI summarization feature costs $4,200/month while your chatbot costs $12,800 — and make informed build-vs-buy decisions on each.
Customer-level attribution
Track AI cost per customer or tenant. Identify which customers generate profitable AI interactions and which are burning margin. Essential for usage-based pricing models and enterprise SaaS unit economics.
Multi-provider consolidation
Aggregate costs across OpenAI, Anthropic, Google, AWS Bedrock, and self-hosted models in a single dashboard. No more reconciling 5 different billing portals at month-end. See our token cost tracking for details.
Budget controls that prevent overruns
Set guardrails before you overspend — not after. Hierarchical budgets from org-wide down to individual features.
Hierarchical budgets
Set org-level, team-level, and feature-level budgets. Team budgets roll up to org. Feature budgets roll up to team. Overspend at any level triggers the right alert to the right person.
Real-time alerts
Multi-threshold budget alerts via Slack, email, PagerDuty, or webhook. Get warned at 50%, 80%, and 100% — or set custom thresholds. Never discover a $50K bill after the fact.
Anomaly detection
AI-powered anomaly detection catches unusual spending patterns even when you haven't set a budget. A retry loop burning $800/hour at 3 AM? You'll know in minutes, not days.
Compliance and financial reporting
AI spending is the fastest-growing line item on most engineering budgets. Finance needs the same visibility and controls they have for cloud infrastructure.
Monthly executive reports
Automated monthly reports showing AI spend by team, trend vs. budget, cost optimization opportunities, and projected next-month spend. Formatted for board decks and CFO reviews.
Audit trail
Complete history of every budget change, alert trigger, and cost allocation decision. Exportable for SOC 2, internal audit, and financial compliance reviews.
Chargeback support
Generate per-team or per-department chargeback reports. Allocate AI costs to the teams that incur them — the same way you handle cloud infrastructure cost allocation today.
Cost optimization recommendations
Automated recommendations based on usage patterns: model routing, semantic caching, prompt optimization, and batch processing opportunities. Quantified savings per recommendation.
Get AI cost governance in place before the next bill surprise
Free tier includes cost tracking for up to 10K API calls/month. Enterprise plans include multi-team attribution, budgets, and compliance reporting.
Start FreePart of the AI Vyuh portfolio. Also see: AI Agent Security · AI Code QA