Spotonix for Databricks

From lakehouse to answers.
Without writing SQL.

Databricks unified your data and AI. But business users still can't get answers without an analyst writing SQL or a notebook. Spotonix sits on top of your lakehouse and turns notebooks, tables, and business logic into a composable context graph — so anyone can ask questions in plain English.

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The Problem

Databricks is powerful.
But the knowledge is fragmented.

Unity Catalog organizes, doesn't reason

Unity Catalog gives you governance and discovery. But knowing a table exists is not the same as knowing what "active customer" means or how to calculate quarterly retention. Organization is not understanding.

Notebooks are islands of logic

Critical business logic lives in hundreds of notebooks across dozens of workspaces. Each is a silo of tribal knowledge — useful to the author, invisible to everyone else.

AI/BI dashboards can't compose

Databricks AI/BI generates SQL from scratch every time. It doesn't know your team's definitions, can't reuse validated logic, and produces different answers to the same question on different days.

How It Works

From lakehouse to context graph in three steps.

01

Connect

Point Spotonix at your Databricks workspace. It reads your Unity Catalog schemas, notebook logic, and table definitions — no data leaves your environment.

02

Build

Notebooks become Calculations. Tables become Segments. Business logic scattered across workspaces becomes a unified, composable Context Graph.

03

Ask & Compound

Ask questions in plain English. Spotonix discovers relevant building blocks, composes the answer from proven logic, and shows its interpretation before executing. Every validated answer compounds the graph.

Your lakehouse holds the data.
Spotonix unlocks the answers.

See how Spotonix turns your Databricks investment into accessible, composable business intelligence.

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