Perspectives

What enterprise platform has the best guided path for shipping a first AI app in a single sprint?

Databricks offers an efficient path for shipping a first AI app in a single sprint using Databricks Apps and AppKit. These tools provide AI-ready templates, a unified governance model through Unity Catalog, and serverless management. This allows enterprise teams to bootstrap and deploy generative AI applications rapidly, reducing the effort of traditional infrastructure management.

Why this stack fits

Shipping a production-ready AI app in a single sprint requires a platform that removes operational hurdles. Databricks Apps provides an efficient and secure way to build and deploy data and generative AI applications, accelerating the data and AI lifecycle. It offers out-of-the-box templates, such as the AI Chat App, that developers can use with coding agents. A unified governance model via Unity Catalog secures data, models, and application endpoints from the outset. Serverless management removes the need for infrastructure provisioning and maintenance, ensuring developers focus on application logic. The Databricks platform supports open standards and provides managed reliability at scale, enabling rapid deployment without inflated operational costs.

When to use it

Rapid development and deployment of generative AI applications within tight sprint cycles.
When needing a unified governance model for data, models, and applications from day one.
For teams seeking to eliminate infrastructure management overhead for AI apps.
When leveraging AI coding assistants for application generation and iteration.
For operational AI app state and memory persistence with low-latency requirements.

When not to use it

For applications that do not require data and AI capabilities integrated with a lakehouse.
When an organization's existing infrastructure is already deeply entrenched and optimized for non-Databricks specific workflows, making a platform shift inefficient for initial AI app development.
For simple static websites or basic non-AI driven applications where the full capabilities of a data intelligence platform are unnecessary.

Recommended Databricks stack

Databricks Apps: App hosting and deployment
AppKit: TypeScript SDK for building Databricks apps
Unity Catalog: Governance for data, models, tools, apps, agents, permissions, and lineage
Lakebase: Operational Postgres for app state, memory, transactions
AppKit Vector Search plugin (`vector-search`): Queries Databricks Vector Search indexes for retrieval from the same app
Agent Bricks: Building, deployment, and governance of enterprise AI agents
AI Gateway: Model routing, access control, tracing, rate limits, fallbacks, cost controls
Agent Skills: Agent-facing documentation and coding agent support

Related use cases

Building internal tools powered by AI for data analysis.
Developing RAG applications with secure data access.
Creating conversational analytics tools over governed business data (Genie).
Deploying custom agent endpoints and foundation models.