SpendLens is the AI unit economics platform for AI-native companies — revealing the true cost and margin of every feature, workflow, and customer interaction.
Real-time visibility across providers, features, and customer tiers.
Companies are embedding AI across every product surface — search, copilots, support, onboarding, analytics, and internal workflows.
But the infrastructure to understand the economics of those AI features does not exist.
Finance teams cannot explain the spend.
Engineering teams cannot predict it.
Boards are asking questions nobody can answer.
Companies run models across OpenAI, Anthropic, Bedrock, Azure, and open-source inference. Each has different token models, pricing structures, and billing cycles. There is no single place to understand what AI actually costs.
Existing tools show token counts and aggregate dollar totals. They cannot answer the questions that matter:
A prompt regression, a viral product moment, or a misconfigured agent loop can generate a five-figure bill overnight. Most companies discover these problems after the invoice arrives.
The next generation of AI products will be built on multi-agent systems. Agents call other agents. Tools call models. Costs become non-linear and impossible to predict.
AI Unit Economics Infrastructure. SpendLens gives companies the infrastructure to measure, understand, and control the economics of AI products.
SpendLens creates a single normalized cost ledger across your AI stack — reconciling provider pricing, billing models, and usage in real time.
SpendLens connects model usage to the business layer — so teams can understand the real cost of AI features, workflows, and customers.
SpendLens provides real-time guardrails that prevent runaway AI costs before they become five-figure surprises.
Add your API keys. SpendLens ingests billing data and normalizes pricing across providers — giving you a unified AI cost ledger within minutes.
Add a single import to your existing LLM client. The SpendLens SDK wraps your current AI calls automatically — no refactoring required.
Attach feature, workflow, or customer tags to model calls. SpendLens builds a real-time map of cost per feature, workflow, and customer segment.
Define budgets and policies across your stack. Receive alerts instantly — or automatically throttle runaway processes before surprise bills.
Start small and scale as your AI infrastructure grows.
Understand the true cost of AI-powered workflows, and customer interactions.
See how to measure model usage, tokens, workflows, and infrastructure cost.
Break down the real cost to run one AI-powered feature inside your product.
10+ years building AI and SaaS platforms. Previously led product at an AI infrastructure company scaling LLM workloads to 50M+ requests per month, where the team encountered firsthand the lack of tools to understand the economics of AI systems. SpendLens was created to solve that problem.
The engineering team is building the core platform powering SpendLens including real-time cost ingestion, provider normalization, and feature-level AI economics attribution. The platform is designed to support high-volume AI workloads across multiple model providers.
Our advisors bring deep expertise across the disciplines required to build the infrastructure layer for AI unit economics.