Documentation
Overview

Introduction to Altertable

Altertable is an AI-native data platform for analytics, product experiences, and agents. It combines storage, modeling, and analysis in one system so teams can work from the same underlying data whether they are building dashboards, powering in-product workflows, or giving AI agents direct access to data.

It includes an analytical database, a visualization layer, and AI agents that operate on the same lakehouse foundation. That makes it practical to support data analytics, product analytics, internal tools, and customer-facing features without splitting data across separate stacks.

The platform is built for continuous work where events, logs, telemetry, business data, and model outputs need to stay queryable and current. AI agents can monitor datasets, while applications can use the same data to power reporting, segmentation, automation, and in-product experiences.

Altertable uses DuckDB for compute and Parquet for storage. DuckDB executes vectorized queries over lakehouse data and local cache layers.

Agents rely on Anthropic, OpenAI, Google, and/or Mistral for their LLM capabilities.

Learn the Core Concepts

New to Altertable? Start by understanding the core concepts that power the platform:

  • Architecture: Explore Altertable's lakehouse architecture and infrastructure
  • Insights: Understand the insight types and when to use each one
  • Agents: Learn how AI agents automate data work
  • Dashboards: Combine insights and monitor metrics
  • Notifications: Review AI-generated findings

Getting Started

Choose your path based on what you are building:

For Data Analytics & BI

For Product Analytics

For AI and agent workflows

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