Open-source observability for AI agents, tracking cost, latency, and quality.
Product memo
AI developers and teams use Foglamp to monitor their AI agents, especially those built with the Vercel AI SDK. It provides detailed observability into LLM call performance, showing cost, latency, and quality. This helps developers identify issues like cost regressions or inaccurate outputs before they affect users.
For who
AI developers and teams
Solves what
Observability for AI agents, tracking cost, latency, and quality.
- Cost and latency tracking
- Distributed tracing
- AI agent evals
In their own words
Ship AI agents you can actually see
See the cost, latency, and quality of every LLM call. Catch bad output before your users do.
Commercial cues
Model
subscription
Free tier
Yes
Trial
Available
Pricing Strategy
- • A generous free tier removes friction for individual developers and small projects.
- • Enterprise handles custom requirements.
Operator context
Team
Indie / lean
Founded
Jun 2026
Platform
Web app
Audience
Developers
Builder Strategy
- Strategy Type
- Open Source Commercial
- Stage
- Bootstrapped Lean
- Effort
- Solo Buildable
About Foglamp Expand
Foglamp offers an open-source observability layer for AI agents, focusing on the needs of AI developers and teams. It provides crucial insights into the performance of LLM calls, including cost, latency, and quality metrics.
This helps teams identify and resolve issues such as unexpected cost increases or inaccurate AI outputs. By offering a transparent, developer-centric tool, Foglamp supports the development and deployment of more reliable AI agents, particularly for those using frameworks like the Vercel AI SDK.