Spanloom

NLP & Text Analytics Platforms

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This platform provides extensive observability and monitoring tools for large language model (LLM) applications, enabling detailed visibility into various stages of AI processing pipelines. Its key features include span-level tracing to track all requests from input to output, real-time token cost tracking to manage expenses effectively, prompt drift detection to identify regressions, RAG retrieval auditing for retrieval accuracy, latency breakdowns to pinpoint performance bottlenecks, and customizable alerts to ensure optimal operation. Designed for developers, data scientists, and AI engineers, it addresses challenges in debugging, cost management, performance optimization, and maintaining prompt consistency within production environments, ensuring AI systems run reliably and efficiently.

Spanloom can be found in NLP & Text Analytics Platforms categories.

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Spanloom Main Features

• Easy Setup
  Add tracking to your existing code with just a few lines of Python or TypeScript.
• Request Tracking
  Track each request made to your AI system to monitor its performance.
• Latency Breakdown
  Understand where the time is spent in each request to find slow parts.
• Production Alerts
  Get notifications when your AI system has errors, high costs, or slow responses.
• Full Trace Visibility
  See every step of your LLM applications to understand how they work.
• Token Cost Monitoring
  Watch the cost and usage of tokens for each request in real-time.
• Prompt Drift Detection
  Check if the prompts change over time and alert you about it.
• RAG Retrieval Auditing
  See which data chunks are retrieved and how they help produce answers.

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