Analytics Agent is a web platform for interactive visual analytics: fast dashboards and reports from your data, with deep drill-down, AI right in the interface and built-in Python. It resembles Grafana, but the focus is not on monitoring — it is on real analysis: here you don’t just watch metrics, you dig deeper — filter, cross-check, calculate, ask the AI.
Who it is for
Analytics Agent is made for analysts and teams who find “look-only” dashboards not enough. The product was created by an analyst with more than 25 years of experience in data and visualization — it shows in the details: from the block grid to server-side histogram calculations.
System requirements
Any Linux host with Docker: the app deploys as a single container, all data in the /data volume, and Python for Jupyter Notebooks is already in the image. Step-by-step instructions are in the Installation section.
First sign-in
The login and password are set by the ANALYTICS_ADMIN_LOGIN and ANALYTICS_ADMIN_PASSWORD environment variables (the variable holds the SHA-256 hash of the password). Without them, signing in is impossible. Sessions work through JWT tokens with a 90-day lifetime.
The interface
- Documents — the report tree with breadcrumbs for nested folders, search across all documents as you type, recent history;
- Templates — a library of 257 ready-made analysis templates: forecasts, segments, scoring and an analytics course (details in Analysis Templates);
- Data Sources — SQLite, PostgreSQL, ClickHouse;
- Lakehouse — a file browser for your data: Parquet, SQLite, Markdown;
- Alerts — rules, contact points, histories and silences;
- at the bottom of the sidebar — active agent chats and the prompts queue; settings (font, sign-out) live in the gear menu.
The interface language (English or Russian) is chosen by the brand at install time; the theme — dark or light — switches in the interface. Sound notifications about new agent messages can be turned off with one button in the header.
Your first report
- create a document with the “New document” button;
- add blocks: a chart, a table, a metric — and drag them around the grid;
- connect a data source in the “Data Sources” section;
- write a SQL query in the block configuration — or ask the AI to do all of it for you in plain language.
A report can be made interactive: put filters and what-if fields into the header, enable click-to-drill, assemble tabs for different readers and export the finished result to PDF. Details in the Reports & Documents section.
What’s next
How documents work is described in Reports & Documents, what they are made of — in Block Types and Charts. Connecting databases — in Data Sources, how the AI works — in the agent in the report, ready-made solutions — in Analysis Templates.