# Opsmeter.io

> Opsmeter.io is an AI cost attribution and bill-shock prevention platform for teams running LLM-powered products in production. It helps teams understand what changed in AI spend by endpoint, tenant, user, model, workflow, and prompt version without forcing provider traffic through a proxy.

Opsmeter.io is built for teams that need more than total token usage. It focuses on request-level attribution, cost spike investigation, budget visibility, and operational clarity across products, tenants, and workflows.

Key capabilities:
- Break down AI spend by endpoint, tenant, user, model, workflow, and prompt version
- Investigate LLM cost spikes before month-end
- Track AI cost without requiring a proxy or gateway
- Support direct ingest and no-proxy telemetry workflows
- Help teams move from raw token reporting to actionable cost governance

Important product behavior:
- Plan limits pause Opsmeter.io telemetry ingest only.
- Provider LLM calls continue normally when telemetry ingest is paused.
- Budget warning and exceeded states are advisory and operational unless the customer adds separate enforcement in their own runtime path.
- Direct ingest is production-ready today. Optional SDK packages are available for Node and Python. The .NET package is not published yet.

## Product

- [Home](https://opsmeter.io/): Product overview, positioning, and core workflow.
- [Pricing](https://opsmeter.io/pricing): Plans, limits, retention, and alerting.
- [Compare hub](https://opsmeter.io/compare): Source-linked comparisons for teams evaluating AI cost attribution tools.
- [Security](https://opsmeter.io/security): Security posture and review material.
- [Status](https://opsmeter.io/status): Service health and status information.
- [Support](https://opsmeter.io/support): Contact and support options.

## Docs

- [Quickstart](https://opsmeter.io/docs/quickstart): Go from first payload to first attribution result quickly.
- [No-proxy telemetry](https://opsmeter.io/docs/no-proxy-telemetry): Track AI cost without changing the provider network path.
- [Limits and budgets](https://opsmeter.io/docs/limits-and-budgets): Understand telemetry pauses, limits, and budget posture.
- [n8n integration](https://opsmeter.io/docs/n8n): Example automation workflows using Opsmeter.io outputs.

## Core guides

- [LLM cost attribution](https://opsmeter.io/blog/llm-cost-attribution): How to break spend down by endpoint, tenant, user, model, and prompt version.
- [How to find root cause of an LLM cost spike](https://opsmeter.io/blog/how-to-find-root-cause-of-llm-cost-spike): Investigation workflow for identifying what changed in AI spend.
- [LLM budget alerts](https://opsmeter.io/blog/llm-budget-alerts): How to structure monitoring and response before invoices arrive.
- [LLM cost reduction playbook](https://opsmeter.io/blog/llm-cost-reduction-playbook): Practical ways to reduce AI spend while preserving control.
- [Prompt deploy cost regressions](https://opsmeter.io/blog/prompt-deploy-cost-regressions): How prompt or deploy changes create hidden cost increases.

## Use cases

- [Track AI cost by tenant](https://opsmeter.io/blog/llm-cost-attribution): For multi-tenant products that need customer-level attribution.
- [Track AI cost by endpoint](https://opsmeter.io/blog/llm-cost-attribution): For teams that need feature-level and workflow-level cost visibility.
- [Track AI cost by prompt version](https://opsmeter.io/blog/llm-cost-attribution): For teams that want to understand the cost impact of prompt changes.
- [Prevent LLM bill shock](https://opsmeter.io/blog/how-to-find-root-cause-of-llm-cost-spike): For teams that need early warning and fast root-cause analysis.
- [AI spend governance](https://opsmeter.io/blog/llm-budget-alerts): For teams moving from token reporting to budgets, ownership, and action.

## Comparisons

- [Provider dashboards vs Opsmeter.io](https://opsmeter.io/compare/provider-dashboards-vs-opsmeter): Compare native provider reporting with dedicated attribution workflows.
- [Langfuse vs Opsmeter.io](https://opsmeter.io/compare/langfuse-vs-opsmeter): Compare tracing and observability with attribution and governance workflows.
- [Helicone vs Opsmeter.io](https://opsmeter.io/compare/helicone-vs-opsmeter): Compare monitoring with no-proxy attribution and bill-shock investigation workflows.

## Optional

- [Blog index](https://opsmeter.io/blog): Additional writing on AI cost attribution, LLM cost tracking, and spend control.
- [Trust proof pack](https://opsmeter.io/security#trust-proof-pack): Material for security and enterprise evaluation.