FinOps for AI
Stop guessing what AI costs, start managing it
AI cost management from a single checkpoint on every AI request. See and attribute all AI spend by team, agent, and customer, before the bill arrives.
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Cost savings with Smart Router, caching, and context compression
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of FinOps teams actively manage AI spend
Real-time
Spend visibility and attribution
One
Gateway for all AI traffic
Trusted by teams managing AI spend at scale
The AI spend problem
Cloud spend had this problem first. AI is repeating it, faster
AI FinOps
The same pattern, faster: more providers, more teams, and agents spending around the clock.
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more tokens per task for agents
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of enterprise AI budgets go to inference
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of agentic AI projects forecast to be canceled by 2027
Sources: 5-30x tokens per task: Gartner, March 2026. ~85% inference share: AnalyticsWeek 2026 Inference Economics report. 40% cancellation forecast: Gartner, 2025.
How it works
One gateway, full control over every AI request
Orq.ai sits between your teams and every model they use - one entry point for cost visibility, budgeting, and optimization across your entire AI stack.
What’s included
Everything you need to manage AI spend
Cost controls, routing, attribution, and analytics in the same gateway that already handles your AI traffic.
Real-time cost attribution
Every token attributed to a customer, feature, team, or task as it happens, not in next month’s invoice.
CFOs & FinOps teams
Real-time spend attribution and chargeback by team and project. No more surprise bills.
CTOs & platform teams
Control which models each team can use and at what cost - without slowing down engineers.
Product teams shipping AI features
Attribute cost per customer and feature. Protect gross margin before it disappears into LLM bills.
AI transformation leads
Track spend and ROI per agent. Route investment toward what works and cap what doesn’t.
Social proof
Trusted by teams managing AI at scale
Cost, governance, and routing controls for production AI teams.
We chose Orq.ai to replace our internal setup with a production-ready AI Gateway that meets our governance, scalability, and cost-monitoring requirements.
Benjamin Kleppe,
GenAI Lead at bunq
With one gateway, teams get the visibility they need to manage AI usage before it becomes a surprise bill.
Platform leader,
Enterprise AI team
Trusted by teams managing AI spend at scale
FAQs
What teams ask us about AI cost management
Open answers for finance, platform, and product teams evaluating AI FinOps.
What is FinOps for AI?
AI FinOps brings financial accountability to AI: knowing what every request costs, who drove it, and controlling it before the invoice lands. Where cloud FinOps managed compute hours and storage, AI FinOps manages tokens, model tiers, agent loops, and per-customer inference costs. As AI spend has grown from experimental budgets to a primary cost line, the same controls enterprises applied to cloud in 2018-2022 are now being applied to AI.
Why is my AI bill rising while token prices are falling?
Per-token prices keep collapsing, with average cost per million tokens down roughly 75% in a single year, but total spend keeps climbing. The reason is consumption. Agentic workflows trigger 10-20 model calls per user request, each of which resends the full conversation history. A simple query that cost pennies in 2024 now runs as a multi-step agent loop that costs dollars. The unit that matters is no longer cost per token, it’s cost per completed task.
How do AI agents change cost management?
Agents consume 5-30x more tokens per task than a standard chat interaction. Every tool call, reasoning step, and retry re-sends the full context window, so costs compound as loops grow longer. A 20-step agent loop can cost 10x what a per-step estimate suggests. This makes per-task budgets, loop controls, and model routing - sending simple steps to cheaper models and escalating only when needed - essential rather than optional.
Why can’t I just use my model provider’s billing dashboard?
Provider dashboards show total spend, not which team, project, customer, or agent drove it. Orq.ai gives one unified view across every model and provider, attributed in real time.
What is Smart Router and how much does it save?
Smart Router analyzes each prompt and routes it to the most cost-effective model that can handle it well. Teams see 10-40% cost savings without changing prompts or code.
Can I set different budgets for different teams?
Yes - at the organization, department, team, project, model, and agent level. When a limit is hit, Orq.ai enforces it automatically and alerts the relevant team.
What happens when a budget cap is hit?
Orq.ai can alert, reroute to a cheaper model, or block further requests depending on the policy you set.
How quickly can I get visibility into current AI spend?
Change your base_url to Orq.ai’s endpoint and you’re live in under two minutes - with AI traffic attributed by team, model, and project immediately.
How does Orq.ai help product teams protect margin?
By attributing spend per customer, feature, and task, product teams can see true AI unit economics before gross margin disappears into LLM bills.
Can finance export AI cost data?
Yes. Monthly chargeback and showback data is exportable to your own BI tools or finance systems.
Does Orq.ai work across multiple model providers?
Yes. Orq.ai gives one gateway for all AI traffic, so teams can observe, route, govern, and optimize spend across providers.
