Domo has introduced App Catalyst, a new feature in its AI and Data Platform. It helps businesses quickly turn their AI ideas into real applications using simple language, all while keeping things secure and easy to scale.
With generative AI, software development has become faster and easier, but many early projects don’t make it to the final version because of weak code and issues with maintaining security and data management. App Catalyst focuses on fixing this by turning ideas into apps that can be trusted and scaled across the company.
Using App Catalyst, you can describe the app you want in plain language, as well as it will instantly create a working app based on your data. It connects to data from cloud platforms like Snowflake, Google Cloud, and Oracle, and it keeps your existing security and governance settings intact.
App Catalyst is different from earlier "vibe coding" tools. Instead of just quickly creating raw code, it helps make apps that meet enterprise standards and can grow with your business. It helps teams build production-ready apps faster, without hasseling about code breaking or needing extra work later.
Key Benefits of App Catalyst:
- Fast app creation: Create simple language to create apps quickly.
- No heavy coding: Create professional apps without a lot of engineering work upfront.
- Easy prototyping: Go from idea to working app in minutes.
- Automatic security: The app respects all data access and security rules.
This launch shows Domo’s vision for the future: using AI to help organizations build secure, scalable apps that bring together data, workflows, and people.
Executive Statement
According to Josh James, CEO at Domo, vibe coding showed how fast ideas can turn into software, but speed alone does not create durable value. The next evolution is moving from raw code generation to composing applications that are grounded in trusted data and governed by design. App Catalyst is an important step in that direction. It’s more like vibe-orchestrating, as it gives teams a production-ready foundation they can extend confidently, while continuing to work with data in the platforms they already rely on.
