LLMeter

StackSpend is a cloud and AI cost management platform that gives engineering, finance, and FinOps teams one daily view of the modern AI stack. It connects through read-only credentials to providers including AWS, Google Cloud, Azure, Snowflake, Vercel, ClickHouse Cloud, Elastic Cloud, OpenAI, Anthropic, Cursor, GitHub, Hugging Face, Grok, and Twilio, then automatically loads historical billing data and normalizes spend across services. Dashboards and explorers break costs down by provider, service, model, project, user, team, feature, and customer, helping teams understand AI COGS, cost per request, and product-level margins. Budgets and pace-to-forecast show where monthly spending is headed, while same-day anomaly detection catches unusual increases caused by traffic, prompt bugs, model changes, deployments, or individual users. Alerts and daily green, amber, or red spend signals can be delivered through Slack, Microsoft Teams, email, or webhooks.

Spanlens is an open-source (MIT) LLM observability platform that lets developers monitor every call their application makes to OpenAI, Anthropic, Gemini, Mistral, OpenRouter, Azure OpenAI, or a local Ollama model. Integration takes one line: swap your client's baseURL to the Spanlens proxy, or run "npx @spanlens/cli init" and the wizard rewrites your code automatically. From that moment, every request is recorded with its model, token counts, latency, cost, and full prompt and response body, with streaming responses reconstructed automatically. The dashboard turns that raw log into operational insight. Cost tracking breaks spend down per request, per model, and per end user, and parses prompt-cache tokens separately so you see real cache savings rather than sticker price. Agent tracing visualizes multi-step workflows as Gantt waterfalls and node-and-edge graphs, highlighting the critical path so you can find the slowest dependency chain in a fan-out.