SaaS Subscription Tracker
Internal tool for tracking team SaaS subscriptions, owners, costs, and renewals with Lakebase persistence and Genie spend analytics.
Build with AI
- Copy the prompt below
- Paste into Cursor, Claude Code, Codex, or any coding agent
- Your agent builds it — asking questions along the way so the result is exactly what you want
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Includes a working starter app
Real, runnable code lives on GitHub. When you copy the prompt above, your coding agent clones it as the starting point and adapts it to your data and use case.
This template demonstrates a straightforward internal CRUD tool built on Databricks: a SaaS subscription tracker where teams log the tools they use, who owns each subscription, what it costs, and when it renews. A Genie space provides self-serve analytics over the subscription data.
Data Flow
All subscription data lives in a single Lakebase Postgres table and is served directly to the app:
- Lakebase Postgres stores the
saas_tracker.subscriptionstable with name, vendor, cost, billing cycle, owner, status, and renewal dates. - The SaaS Tracker App (Databricks App) reads and writes subscriptions through Express API routes backed by Lakebase.
- SQL Warehouse queries power the analytics dashboard (spend overview, spend by category).
- A Genie Space configured over the subscriptions table lets users ask natural language questions about spend, owners, and renewals.
What to Adapt
Setup and provisioning are documented in the repository’s README.md.
To make this template your own:
- Lakebase: Point the app's
databricks.ymlat your own Lakebase project, branch, and database. - SQL Warehouse: Set the warehouse ID for the analytics queries.
- Genie Space: Create a Genie space over the
saas_tracker.subscriptionstable and set the space ID. - Categories: Adjust the category list in the server routes and form component to match your organization's departments.
- Seed Data: The seed script creates 18 realistic demo subscriptions. Replace with your own data or use the app's Add form.
Built on these templates
This example's codebase and the agent prompt above both build on top of the templates below. Open one to dive into a specific technique on its own or apply it to a different project.
[TEMPLATES]
App with Lakebase
Wire up a Databricks App with Lakebase for persistent data storage. Includes schema setup and full CRUD API routes.
[TEMPLATES]
Genie Conversational Analytics
Embed a Databricks AI/BI Genie chat interface so users can explore data through natural language. Configure a Genie space, wire up server and client plugins, declare app resources, and deploy.
