PromptLayer - Observability & Tracing for LLM Apps
Real-time prompt versioning, latency tracing, and regression testing for production AI agents.
Alex Chen
Founder
Full-stack engineer & AI researcher building open source developer infrastructure.
Problem
Engineers debugging production LLM pipelines lack structured tracing, latency breakdowns, and regression checks when prompts change.
Audience
AI engineers and software teams shipping agentic applications
Existing alternatives
- Manual logging to Datadog or ad-hoc spreadsheet prompt comparisons.
Milestones
- Q1
Drop-in TypeScript/Python SDK
- Q2
Automated prompt regression evaluator
- Q3
Team prompt playground
Pitch
Tip: use **bold**, bullet lines starting with - , and [label](https://…) for links.
A drop-in SDK that wraps OpenAI, Anthropic, and Gemini calls to automatically log token usage, latency, and system prompt versions with instant diff tracking.
Backing progress
₹12,450 raised of $500.00 goal
Stripe settles in USD; shown approx. in INR @ ₹83/USD.
₹70,550 capacity left (incl. pending)
Feedback
Specific, kind suggestions help founders improve. Mention what resonates, what is unclear, or what you would pay for.
- EElena Rostova·
Super excited about this! Will there be support for self-hosted Ollama models as well as cloud providers?
- Alex Chen·
Yes, absolutely! The proxy layer supports any OpenAI-compatible API endpoint, including Ollama and vLLM.