ModelCost gives AI SaaS teams per-customer LLM cost attribution, agent session management, budget enforcement, and PII/PHI detection. SDK-based and multi-provider, no proxy in your critical path. See your unit economics at the customer level, not just the org level.

Hey Product Hunt! Armard here, founder of ModelCost. The problem that led me here is one I kept running into working on AI products from the inside: companies are good at tracking what customers pay them, but they have almost no visibility into what it costs to serve those customers at the LLM level. Provider dashboards give you a single number. That number grows with usage. And unless you've built your own attribution pipeline, you have no way to know whether the growth is coming from your highest-value customers or your most expensive ones. Most teams either build a rough version of the instrumentation themselves and move on, or they manage costs at the blended level until it becomes a problem they can't paper over anymore. Neither is a great answer when you're trying to build a sustainable business on top of AI. ModelCost solves this with a lightweight SDK integration , wrap your LLM calls, pass a customer ID, and you get per-customer cost attribution across providers, session-level tracking for multi-step agent workflows, budget enforcement that actually stops calls when you hit a threshold, and PII/PHI detection before data leaves your stack. It's not a proxy, it fails open, and it doesn't touch your critical path. We're offering a 14-day free trial. If you've tried to solve the attribution problem yourself and want to see how we approached it, or if you're just starting to feel the margin pressure, I'd love to hear from you in the comments.

ModelCost

One SDK for LLM costs, budgets, and attribution

One SDK for LLM costs, budgets, and attribution