The research that backs everything we claim.

Depth over sound bites. Original research, deployment analysis, and practical frameworks for enterprise AI leaders who need evidence.

Configurable Organization Meets the Lakehouse

WHITE PAPER

Coordinated Multi-Agent Software Engineering at Scale

This whitepaper documents Covasant Partyline, a lightweight, durable coordination layer for independent AI agent fleets built on Databricks Lakebase, and the six requirements no chat tool, orchestration framework, or classic distributed system satisfied at once.

WHITE PAPER

Configurable Organization Meets the Lakehouse: How Tenant-Scoped Delta Paths Enable Single-Source-of-Truth Retrieval

Most multi-tenant data platforms enforce isolation through row-level filters, query interceptors, and access-control middleware.

WHITE PAPER

DeltaBus: A Lakehouse-Native Event Bus Pattern for Data Platforms

Most data platforms built on the Lakehouse add a separate message queue. Kafka, SQS, Azure Event Hubs. It’s an another cluster to manage, separate billing line and another governance gap, because events flowing through an external bus exist completely outside your Unity Catalog boundary.

WHITE PAPER

Semantic Documentation Search for Agentic Platforms

AI coding agents are only as useful as the knowledge they can access. When an agent hits an unfamiliar question how tenant isolation works, where a data contract is defined, what the full authentication flow looks like it falls back to keyword search.

WHITE PAPER

Auraa Semantic Flow: Transient, Data-Driven Interfaces for Agent-Human Collaboration

Every new agent capability your team ships eventually runs into the same constraint: the frontend. Building the review page, wiring state management, handling confidence scores and approval gates for every agent feature that takes hours on the backend, the interface takes days.

WHITE PAPER

Auraa, An Agentic Data Activation Platform for Databricks

Most enterprise data platforms today were built for humans, UIs, notebooks, scheduled jobs. Adding an AI copilot on top doesn't change the architecture underneath. The agent suggests.

WHITE PAPER

Auraa and Genie Code: Better Together - An Agentic Data Platform Meets Databricksʼ AI Coding Agent

Genie Code writes SQL and Python, builds Lakeflow pipelines, debugs failures, and monitors production workloads.

WHITE PAPER

Auraa & Databricks: The Agentic Substrate for the Intelligent Lakehouse

Databricks gives you one of the most capable data platforms available. Delta Lake, Unity Catalog, serverless compute, Lakeflow pipelines. The infrastructure is solid.

WHITE PAPER

Rethinking Data Engineering: An AI-First, Metadata-Driven Platform for Databricks

Auraa is Covasant’s Databricks-native, agent-driven data platform that automates ingestion, data quality, governance, and analytics across the Lakehouse through a modular suite of components orchestrated by AI agents.

WHITE PAPER

Sub-Second on the Lakehouse: How Auraa Serves APIs from Databricks Without Breaking the Single Source of Truth

Your data platform has one job: be the single source of truth. But as your teams build more on top of it, APIs, AI agents, real-time applications, a quiet tension emerges.

WHITE PAPER

Data Observability: The Backbone of Reliable AI Systems

Building a strong foundation for data observability helps you identify issues early, maintain data integrity, and create AI systems you can truly trust.

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The research that backs everything we claim.

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