Auraa on Databricks

Auraa, An Agentic Data Activation Platform for Databricks

Most enterprise data platforms were built for humans: UIs, notebooks, scheduled jobs. Adding a copilot on top does not change the architecture underneath. The agent suggests. The human still executes.

Read the white paper

Key takeaways

Governance is structural

Not bolted on after the fact, and not arriving late.

Twelve components

Data Plane, Control Plane, and Shared Foundations, walked through in full.

Months to weeks

Capabilities built once and reused, not reimplemented per project.

Failed call, not bad data

The worst outcome of a bad plan is a failed tool call.

About this white paper

Built for agents, not adapted for them

Every capability in Auraa is a tool: typed, discoverable, governed. Agents plan, tools execute, and humans set strategy, define policy, and audit outcomes. This paper walks through all twelve platform components across the Data Plane, Control Plane, and Shared Foundations, and the six-stage roadmap for replatforming onto it.

Written by the team that built and operates the platform
Includes the trade-offs we accepted, not only the wins

Read the architecture before you build it.

Twenty minutes of reading that can save a migration. No form, no gate, straight to the PDF.

Read the white paper Book a demo

A copilot is added on top of a platform built for humans: UIs, notebooks, scheduled jobs. The copilot suggests. The human still executes. The backlog, pipeline failures, and late governance remain. Auraa was designed from the start with agents as the primary operators. Every capability is a typed, discoverable, governed tool. Agents plan. Tools execute. Humans set strategy, define policy, and audit outcomes. The architecture is different at the foundation, not at the interface layer.

Auraa's 12 platform components are organized across three layers. The Data Plane handles the actual data work: ingestion, transformation, quality validation, and serving. The Control Plane manages the platform itself: tenant provisioning, agent orchestration, configuration management, and governance enforcement. The Shared Foundations provide the infrastructure that both planes rely on: DeltaBus for messaging, the metadata medallion for configuration, the GovernanceWriter for consistent writes, and the tool registry for agent discovery. The whitepaper includes a complete walkthrough of all 12 components.

When an agent makes an incorrect plan in a traditional data platform, it may execute SQL that writes incorrect data to a production table, a corruption that can propagate silently through downstream pipelines before detection. In Auraa's tool-first architecture, a bad agent plan results in a failed tool invocation: the tool's preconditions are not met, the execution does not proceed, and the failure is logged with full context. The data is never touched. For regulated industries where data integrity is a compliance requirement, this failure mode boundary is architecturally significant.

Databricks is a production fraud detection deployment documented in the whitepaper. It uses Auraa as its agentic data platform on Databricks for a real enterprise fraud detection workload. The whitepaper uses this deployment to validate every architectural claim made about Auraa: multi-tenant isolation, DeltaBus messaging, GovernanceWriter pattern, metadata-driven pipelines, and structural governance. It is included specifically to demonstrate that the architecture performs as described under real production conditions, not just in controlled scenarios.

The six-stage replatforming roadmap is designed for organizations migrating from existing data and analytics platforms (such as traditional data warehouses, legacy Spark platforms, or cloud data platforms with manual engineering workflows). It covers the sequence of decisions and migrations required to move from the existing platform to Auraa's agentic architecture without disrupting live data products. The stages address infrastructure preparation, metadata migration, pipeline conversion, governance transition, agent onboarding, and full production handoff.