Documentation Index
Fetch the complete documentation index at: https://docs.chartcastr.com/llms.txt
Use this file to discover all available pages before exploring further.
Overview
Chartcastr AI Chat provides a conversational interface for deep analysis of your data. It goes beyond simple snapshots, allowing you to ask complex questions that leverage the full Context of your workspace.Context Discovery
The AI automatically discovers context from your connected sources and documents to make every interaction smarter. It doesn’t just look at the numbers; it reads your strategy docs and metric definitions to explain why the numbers are changing.Context-Aware Analysis
The power of Chat analysis comes from its ability to synthesize multiple information sources:Pulse and Connection Data
Chat has direct access to your latest pulse data and connection history.- “Why did revenue drop yesterday compared to the same day last week?”
- “Which items are currently trending in our inventory?”
External Context Integration
If you’ve linked External Context (like Google Docs or Sheets), Chat incorporates that information into its analysis.- “Based on our Q1 Strategy document, how are we tracking against our growth goals?”
- “Explain the latest revenue numbers in the context of our pricing update definitions in Sheets.”
Comparing Data
You can use Chat to compare performance across different sources or time periods.- “Compare the conversion rate of our Facebook ads vs Google ads over the last 30 days.”
- “Show me how the new product launch in London compares to the Manchester launch.”
Interactive Exploration
Analysis in Chat is iterative. You can start with a broad question and drill down into specific details.- Start Broad: “How was our performance last week?”
- Drill Down: “Break down that revenue spike by category.”
- Analyze Root Cause: “Was that increase driven by new customers or existing ones?”
- Get Recommendations: “What should we focus on next week to maintain this momentum?”
Visualizing Insights
While Chat is primarily text-based, it can help you prepare data for visualization.- “Summarize these findings into a list of bullet points for my weekly report.”
- “Format the revenue comparison as a table.”