Count is an agentic BI platform that replaces rigid dashboards with a multiplayer canvas where analysts, operators, and stakeholders explore data together in real time. It combines SQL, Python, and AI-driven analysis in a single notebook-style workspace connected directly to your data warehouse.
Product Overview
Count reimagines business intelligence as an open canvas rather than a static report — analysts write SQL or Python in cells, layer in visualizations, and share a live workspace where non-technical collaborators can add comments, sticky notes, and filters without touching the underlying queries. An AI agent can interpret natural-language prompts, write queries, and build charts autonomously, while DuckDB handles in-browser query caching so most downstream exploration never hits the warehouse. Count Metrics adds a governed semantic layer so that KPI definitions stay consistent across every canvas.
Key Features
- Multiplayer Canvas: A real-time shared workspace where analysts, business users, and stakeholders collaborate simultaneously — editing, commenting, and exploring the same living analysis.
- AI Agentic Analysis: An AI agent reads your data schema, writes SQL or Python, builds visualizations, and chains multi-step analytical operations from a plain-English prompt.
- SQL + Python Cells: Analysts write raw SQL or Python inline on the canvas, with results rendering immediately as tables or charts without leaving the workspace.
- Count Metrics Semantic Layer: Version-controlled, governed metric definitions that ensure every canvas and report references the same KPI logic, eliminating conflicting numbers across teams.
- In-Browser DuckDB Engine: After the initial warehouse query, downstream exploration runs entirely in the browser via DuckDB — making iteration fast without repeatedly hitting Snowflake, BigQuery, or Redshift.
Best For
Data teams at mid-market companies who want analysts and business stakeholders to collaborate inside the analysis itself rather than in separate Slack threads or slide decks.
Pricing
Free tier available; paid plans start at $34/editor/month. Viewer and collaborator roles available at lower cost. 14-day trial, no credit card required.
Key Integrations
Snowflake, BigQuery, Databricks, Redshift, PostgreSQL, MySQL, dbt, DuckDB
Pros
- Combines SQL, Python, and collaborative whiteboarding in one interface, eliminating context-switching between tools.
- AI agent is schema-aware, making it genuinely useful for exploratory analysis rather than just autocomplete.
- In-browser DuckDB caching speeds up iterative exploration without extra warehouse compute costs.
- Customer support is consistently praised for responsiveness and willingness to incorporate feedback quickly.
Cons
- Performance can degrade on very large initial dataset pulls when working with tens of millions of rows.
- The open-canvas model is less intuitive than traditional dashboard tools for purely report-consumption use cases.
- Chart styling and layout customization is limited compared to dedicated visualization tools like Tableau.
