====== Databricks Apps ======
**Databricks Apps** is a component of the Databricks platform designed to host secure user interfaces and workflows that integrate with agentic AI systems and Agent Bricks. The platform enables organizations, particularly in the financial services sector, to build compliant and auditable interfaces for agentic workflows while maintaining governance boundaries and regulatory oversight (([[https://www.databricks.com/blog/banks-dont-have-ai-problem-they-have-data-platform-problem|Databricks - Banks Don't Have an AI Problem, They Have a Data Platform Problem (2026]])).

===== Overview and Purpose =====
Databricks Apps serves as an enterprise-grade interface layer for deploying agentic AI systems within regulated environments. The platform addresses the specific needs of organizations that require strict compliance, auditability, and governance controls when implementing autonomous AI workflows. Rather than treating AI as an isolated capability, Databricks Apps positions agentic interfaces as integrated components of a broader data platform ecosystem (([[https://www.databricks.com/blog/banks-dont-have-ai-problem-they-have-data-platform-problem|Databricks (2026]])).

The primary function of Databricks Apps is to facilitate the deployment of secure, user-facing interfaces that interact with Agent Bricks—Databricks' framework for building agentic AI systems. This integration allows organizations to expose agentic workflows through governed, auditable channels that comply with industry-specific regulatory requirements.

===== Integration with Agent Bricks =====
Databricks Apps works in conjunction with Agent Bricks, the platform's agentic AI framework, to create end-to-end solutions for autonomous task execution. This integration enables developers to expose agent capabilities through secure UIs while maintaining the control and visibility required in regulated industries. The relationship between Apps and Agent Bricks represents a full-stack approach to agentic AI deployment, where the interface layer (Apps) and the execution layer (Agent Bricks) operate within a unified governance framework.

The platform's architecture supports complex workflows where multiple agents or workflow steps may be orchestrated through a single UI, allowing organizations to manage autonomous processes without sacrificing visibility or control.

===== Compliance and Governance =====
A core design principle of Databricks Apps is its focus on compliance and auditability, particularly relevant for financial services organizations. The platform maintains governance boundaries that preserve audit trails, enforce access controls, and enable compliance teams to monitor agentic activity in real time. This approach addresses a fundamental challenge in regulated industries: deploying advanced AI capabilities while maintaining the oversight mechanisms required by regulators.

Databricks Apps achieves this through tight integration with the broader Databricks platform's governance features, including role-based access control, data lineage tracking, and activity logging. These mechanisms ensure that agentic workflows executed through Apps instances remain fully auditable and compliant with industry standards such as those applicable to banking and financial services.

===== Target Use Cases =====
Databricks Apps is positioned primarily for use cases in financial services, where regulatory compliance and operational risk management are critical. Common applications include customer service workflows, transaction processing, risk assessment processes, and other business-critical functions that benefit from automation while requiring full auditability and compliance oversight.

The platform enables organizations to implement agentic AI without building custom infrastructure for governance and auditability, reducing time-to-deployment and technical risk for regulated organizations deploying autonomous systems.

===== See Also =====

  * [[databricks_marketplace|Databricks Marketplace]]
  * [[agent_bricks|Agent Bricks]]
  * [[databricks|Databricks]]
  * [[databricks_ai_research|Databricks AI Research]]
  * [[databricks_week_of_agents|Databricks Week of Agents]]

===== References =====