LLMetrics
LLMetrics is LLM cost tracking software for teams shipping AI products, bringing model spend, token usage, feature attribution, and usage alerts into one live dashboard. It supports more than 100 models across OpenAI, Anthropic, Google Gemini, Mistral, Cohere, Together AI, Groq, and other providers, with pricing data synchronized daily. Teams tag each model call with a feature name, provider, model, input tokens, and output tokens, allowing them to see exactly whether a chatbot, summarizer, search feature, lesson generator, or other workflow is driving spend. Real-time updates and daily trend charts reveal how costs change after releases, prompt edits, traffic growth, or model swaps. Spend thresholds and spike-detection rules can alert teams through email or Slack when usage patterns look wrong, helping them catch runaway loops and unexpected cost increases before the provider invoice arrives.
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Spanlens
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.
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StackSpend
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.
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bolt.diy
bolt.diy is an open-source platform that enables developers to easily create, run, edit, and deploy full-stack web applications with a variety of large language models (LLMs). It supports a wide range of models, including OpenAI, Anthropic, Ollama, OpenRouter, Gemini, LMStudio, Mistral, xAI, HuggingFace, DeepSeek, and Groq. The platform offers seamless integration through the Vercel AI SDK, allowing users to customize and extend their applications with the LLMs of their choice. With its intuitive interface, bolt.diy is designed to simplify AI development workflows, making it a great tool for both experimentation and production-ready applications.
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