Opsmeter.io
AI cost attribution and monitoring for LLM apps
Hi everyone, I’m building Opsmeter.io — an AI cost attribution and monitoring tool for teams shipping LLM applications.
The problem I kept noticing is that most teams can see the invoice, but not what actually drives it. AI spend gets buried across tenants, users, features, prompts, and workflows, so cost problems often show up only after the bill arrives.
With Opsmeter.io, the goal is to make AI costs easier to understand and control with attribution, monitoring, and alerts for production AI apps.
Still early, but I’d love feedback from anyone building with OpenAI APIs, LLM features, or usage-based AI products. I’m especially interested in how you currently track AI spend and where visibility breaks down for your team.
1 Comment
The interesting tension is whether visibility actually changes behavior — knowing which users, features, or workflows drive AI costs is useful, but the real value is whether teams act on that information. Curious what progress you’re seeing so far — are early users actually changing architecture or usage because of Opsmeter’s insights?