FinopsAI

AI-native companies are creating a new problem for finance teams: infrastructure spend is becoming deeply tied to individual customers, agents, models, and product features, but traditional finance systems only see the final cloud or API invoice.

At the same time, engineering teams understand tokens, GPUs, model routing, latency, and utilization, while the Office of the CFO understands gross margin, COGS, R&D, budgets, contracts, and profitability. These two worlds rarely share the same context.

Our goal was not to build another cloud-cost dashboard or accounting copilot. We wanted to create a self-learning Finance + FinOps agent that can understand why AI infrastructure costs exist, determine how those costs should be treated financially, recommend ways to reduce them, and learn from every decision made by controllers, accountants, and FinOps engineers.

The core idea is simple:

Every human finance decision should make the agent better at the next one

Built With

• ai
• evals
• llm
• maximor
• neatlogs
• python
• tensormux
• typescript
• vectordb
• vercel