Your finance team cannot tell you which customers are profitable after AI cost.
We can, in 30 minutes.

Spendline maps every AI dollar to the customer, feature, and workflow that caused it. See which customers, features, and workflows are unprofitable due to AI spend. Fix it before the bill arrives.

Built for AI-native companies routing $50K to $500K per month through OpenAI, Anthropic, Gemini, or xAI.

Most teams know their total AI spend. Almost none know their AI gross margin.

Integration: swap your base URL. No SDK required.

Works alongside LiteLLM, Helicone, Portkey, or direct provider APIs.

No rewrite to your model logic or application flow.

Get your AI margin diagnostic →

Free 30-minute call. No integration. We send you a 5-page report on the AI gross margin and attribution gaps in your stack within 48 hours.

The math · $50K/month AI spend
Unattributed or ungoverned spend typically identified$7,500–$10,000
Spendline feemax $1,000
Net margin impact+$6,500–$9,000
The problem is not just overspend. It is not knowing which customers or features caused it.
“The math is not subtle.”
Case
study
“One company we evaluated was generating $32M in revenue while spending $39M on purchased AI services. Zero attribution. Engineers saw tokens. Finance saw invoices. The board saw the gap too late.”
Observed during investment due diligence. AI spend was real, but no one could say which customer, team, or workflow caused it.
Diagnostic

The 6 questions your finance team probably cannot answer.

  1. 01Which of your customers is the most expensive to serve on AI?
  2. 02What was your single largest workflow cost last week, and who caused it?
  3. 03How long did it take finance to reconcile your last LLM invoice?
  4. 04If a code push 10x'd your token usage tomorrow, when would you find out?
  5. 05What is your gross margin on AI features, by customer segment?
  6. 06Can you cap a team's spend automatically before it breaches budget?

If you answered no, do not know, or kind of to two or more of these, you have a financial visibility gap that is going to surface on your next board deck. The diagnostic call surfaces these gaps formally. You leave with a 5-page report you can show your CFO.

Book your 30-minute diagnostic →
The problem

AI costs are created inside product flows.
Finance only sees the total after the fact.

Every prompt, retry, and tool call is a spend decision made by code in production. For AI features, that happens continuously across your user base. In agentic workflows, thousands of those decisions happen overnight with no human in the loop. By the time finance sees the number, the spend has already happened.

Provider dashboards show totals. They do not show which customer, team, or feature caused the cost.

Which customers are actually profitable after AI costs?

Most teams cannot answer this.

AI spend is becoming a COGS line. Most companies are still treating it like infrastructure.
Why Spendline

Observability tools show tokens. Spendline shows gross margin per customer.

That is the number your board actually cares about.

Engineering tools tell you what happened. Spendline tells you what it cost the business.

The difference is not visibility. It is financial accountability.

Engineering installs it for visibility. Finance adopts it for control. The business uses it to protect margins.

Pricing

Value-linked.
Not seat-based.

AI workloads do not map cleanly to seats. Spendline is priced as a base fee plus a percentage of AI spend under management. If we do not improve your margins by more than we cost, the product should not exist.

Pricing is aligned to AI spend because that is the risk being managed.

Growth
$500/mo
+ 1.0% of AI spend · variable capped at $500/mo
max total $1,000/mo
AI-native startups · $5K–$50K/mo AI spend
  • In-path proxy with attribution
  • Real-time cost dashboard
  • Hierarchical budgets (org, team, agent)
  • Policy engine with budget guardrails and spend alerts
  • Anomaly detection and alerts
  • 60-day free pilot to start
Platform
$1,500/mo
+ 0.75% of AI spend · variable capped at $1,500/mo
max total $3,000/mo
High-growth AI companies · $50K–$200K/mo
  • Everything in Growth
  • Customer margin analytics
  • Cost optimizer with reroute rules
  • AI month close workflow
  • Budget override approval flows
  • Slack, Discord, webhook alerts
Enterprise
From $5,000/mo
+ 0.5% of AI spend · custom annual agreement
Large AI orgs requiring governance and compliance
  • Everything in Platform
  • SSO and SCIM provisioning
  • Approval workflow automation
  • Accounting exports and integrations
  • Private deployment options
  • Dedicated onboarding

Customers move to Enterprise because they need deployment, compliance, and workflow features, not because spend crossed a threshold. Enterprise is feature-gated, not spend-forced.

What Spendline does

Financial attribution at the moment of execution.

Every request is mapped to a customer, workflow, or cost center before finance sees the invoice.

Core
Real-time attribution
Every request is tagged at execution with the business context that caused the cost: customer, agent, workflow step, or cost center. In multi-agent chains, attribution traces to the specific execution, not just the top-level call. No post-hoc allocation. The record is created when the spend happens.
Core
Hierarchical budgets
Set caps by org, team, agent, or customer. In agentic workflows, budget gates fire mid-execution, stopping runaway spend before a workflow completes, not after. Trigger alerts, webhooks, and approval flows the second a budget is breached, without dropping production traffic.
Core
Policy engine
Set usage guardrails, set token limits, and trigger instant Slack and webhook alerts when spend thresholds are breached.
Finance
Customer margin analytics
Track AI cost per customer, feature, and workflow in real time. See revenue against LLM cost, understand gross margin, identify unprofitable usage, and quantify AI's impact on your P&L.
Optimization
Cost optimizer
Reroute eligible traffic, track savings, and identify duplicate-query waste without changing application code.
Finance
AI month close
Validate allocation completeness, post adjustments, and move from open to closed in a workflow finance can actually run.
How it works

Attribution runs in the request, not in the report.

Every request becomes a financial event.

  1. Request enters Spendline
  2. Business context attaches
  3. Attribution and policy checks run
  4. Request routes to provider
  5. Financial record is created
  6. Shared visibility updates
01
Request enters Spendline
02
Business context attaches
03
Attribution and policy checks run
04
Request routes to provider
05
Financial record is created
06
Shared visibility updates
Ready when you are

Understand your AI cost structure
from the first request.

Add guardrails once you see the data.

Swap your base URL. No SDK required. Fast time to first visibility. No commitment until you have seen your real AI cost breakdown.

Get your AI margin diagnostic →fida@spendline.ai

Currently accepting pilot partners across B2B SaaS and enterprise, especially teams where AI spend is becoming a real cost line.