Laminar Reviews — Discover what people think of this product.
Laminar
Developers struggle to debug, monitor, and improve AI applications due to lack of visibility into LLM execution steps.
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What does Laminar help with?
Observability
Tracing is crucial for debugging and improving AI apps, providing visibility into every execution step while collecting data for evaluations and fine-tuning. Laminar enables tracing with just a single line of code.
Automatic Framework Integration
Simply initialize Laminar at the project start to automatically trace popular LLM frameworks and SDKs. Supports real-time traces for immediate debugging of AI workflows and agents.
Browser Agent Observability
Automatically records high-quality browser sessions and syncs them with agent traces, improving debugging experience and allowing 10x faster issue resolution.
Key Features
- LLM playground for experimenting with prompts and models
- Dataset building from span data for evals and fine-tuning
- Custom span labeling for better information organization
- Open-source architecture with easy self-hosting options
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Scale globally with less complexity
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