LLM cost attribution dashboard

Attribute LLM bills to features, teams, and intents, then get concrete cost-cutting actions.

Problem

After teams add LLM-powered support bots and internal agents, token usage grows but bills grow faster. The invoice only shows model names and totals, so no one knows which feature, team, or intent is burning money. Teams want to cut costs but do not know whether to switch to smaller models or add caching first.

Solution

A lightweight gateway or SDK that tags every call with feature, team, and intent, then aggregates costs into attribution reports. It suggests caching for high-frequency similar system prompts, recommends cheaper models for simple intents, and simulates the savings.

Users

Small B2B teams and indie SaaS developers using LLMs for support, internal tools, or agents.

MVP

Proxy layer supporting major model APIs; tagging by feature, team, and intent; cost trend and top-spend dashboard; similar-prompt clustering with cache suggestions; model-switch savings simulator.

Revenue

Usage-based SaaS subscription or self-hosted annual license; free tier with call limits.

Why now

As LLMs move from experiments to production, cost control becomes a real budget issue, and existing observability tools are engineer-centric, lacking attribution and actionable advice for small teams.