telemetry.dev — AI for Cybersecurity & IT Infrastructure

When you run AI applications or agents in production, tracking failures, latency, and token costs across multiple model calls and tool steps quickly becomes complex. telemetry.dev addresses this by consolidating your metrics, logs, and traces into a single workspace view, allowing you to trace model calls, tool steps, and retrievals together. The platform calculates the cost of each model call at ingest using a pricing catalog covering thousands of models, breaking down expenses by provider, model, and user. You can configure alerts for unexpected cost spikes, monthly budget breaches, agent loops, or model and tool errors before your users notice them. For data security, you can turn off prompt capture for specific environments like production, though you should note that redaction does not catch all sensitive data. Integration is handled via first-party SDKs for TypeScript and Python, standard OTLP/HTTP exporters, or direct setups for frameworks like Vercel AI SDK, LangChain, and CrewAI. It also features a read-only MCP server that lets your AI agent investigate errors, latency, and costs directly. While the platform deletes data after your plan's retention period (ranging from 14 to 90 days) without providing an audit log of user actions, it offers practical plans ranging from a free tier up to team packages with unlimited projects and seats. If you need deeper visibility into your AI agents, token spend, and tool failures without configuring a massive observability stack from scratch, telemetry.dev provides a straightforward, developer-focused environment.