An AI-powered decision intelligence platform, Tellius recently announced a collaboration with Databricks to provide its Tellius natural language search queries and automated insights on the Databricks Lakehouse platform, powered by Delta Lake without transferring any data to their customers.

Ajay Khanna, Founder, and CEO of Tellius said, “With our partners at Databricks, we are delivering cloud-native data analytics to accelerate positive business impact from AI and machine learning. Business users and data professionals can now focus on deriving insights across their multiple data sources and enterprise applications and on taking action based on automated recommendations without compromising on analytics performance.”

Users from both business and technical backgrounds will be able to connect to Tellius and directly interact with the data and models in Databricks. Tellius helps organizations quickly find what’s happening with their natural language queries, understand why metrics are changing with artificial intelligence (AI) insights, and determine the next best action with deep insights and machine learning (ML). Using Databricks, users can easily connect to Delta Lake and perform natural language searches of their unaggregated data in order to answer their own questions. Tellius gives users the flexibility to drill down infinitely to gain granular insights, use AI technology to identify trends, key drivers, and anomalies in their data, and create predictive models via AutoML. As a result, insights can be exploited to write back into source applications and to drive action.

The following are the benefits of deploying Tellius and Databricks:

Augmented lakehouse analytics – Integrates Databricks Lakehouse Platform to analyze petabytes of live data without having to move it elsewhere

Zero-data movement insights – Identifies actionable insights across a wide range of sources, using AI-powered analysis of disparate structured and unstructured data on the Databricks Lakehouse Platform

Faster data collaboration – allows data access across entire analytics teams without compromising performance or IT maintenance

More accessible AI and ML – Insights, and predictions from machine learning workloads built-in Databricks can be accessed through natural language search, getting them into production with business users quicker than ever