Context.ai
  • What is Context.ai?
  • List of Trackable Metrics
  • Product Analytics
    • Overview
    • Topic Categorisation
      • LLM Topics
    • User Engagement Tracking
    • Foreign Language Support
    • PII Filtering
    • Custom Metadata Filtering
    • Backfill Analytics Data
    • Custom Events
    • API Ingestion Methods
      • Log Conversation
      • [deprecated] Upsert Conversation
      • Thread Conversation
      • Patch Thread Message
      • API Resources
        • Chat Message
        • [deprecated] Tool Message
        • Custom Event
        • Metadata
        • Conversation
        • Thread
    • Embedded API
      • Multi-Tenancy
      • Conversations
        • Series Data
  • Integrations
    • Getting Started
    • Python SDK
    • Javascript SDK
    • LangChain Plugin
    • Haystack Plugin
    • Authorization
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  1. Product Analytics

Overview

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Last updated 11 months ago

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Context.ai product analytics enables builders of LLM applications to better understand user behavior and product performance. This allows you to:

  1. Understand why and how people are using your product. What are they asking for?

  2. Monitor product performance using feedback signals from real users. How well are user needs being met?

  3. Identify areas of poor performance that you can improve. How can you make your product better?

To answer these questions, Context.ai annotates transcripts with that capture the meaning and purpose of the conversation. Context.ai then scores every conversation using a variety of success metrics. Combining these two allows product builders to groups of transcripts where the product is performing well, and areas where it needs improving.

Integration with our analytics product takes less than 30 minutes. You can get started with our or SDKs, or by calling our API directly.

topic labels
Python
Javascript