Systems | Development | Analytics | API | Testing

7 Steps to Build an AI-Powered Personalization Engine With Confluent & Databricks

The advancement and widespread availability of new artificial intelligence (AI) capabilities—through platforms like the Databricks Data Intelligence Platform and Mosaic AI—has completely reset expectations for engineering teams across every industry. Business now moves at a new pace, demanding rapid delivery of intelligent, real-time applications—instead of slowly stitched-together systems solving problems defined and scoped months prior.

The Easiest Way to Power Real-Time AI: Confluent Announces Delta Lake Support & Unity Catalog Integration for Tableflow

In the age of AI, the hunger for fresh, reliable data to power machine learning (ML) models and real-time analytics is insatiable. Yet, organizations frequently hit roadblocks when trying to bridge their operational data in motion, typically flowing through Apache Kafka, with their data at rest in data lakehouses. On one side, you have the data streaming platform, the central nervous system managing the real-time flow of business events.

Allium's Blueprint for Scaling Blockchain Data with Data Streaming | Life Is But A Stream Podcast

Blockchain may be decentralized, but reliable access to its data is anything but simple. In this episode, Ethan Chan, Co-Founder & CEO of Allium, shares how his team transforms blockchain firehoses into clean, queryable, real-time data feeds. From the pitfalls of hosting your own data streaming infrastructure to the business advantages of Confluent Cloud, Ethan reveals the strategic decisions that helped Allium scale from 3 to nearly 100 blockchains, without burning out their engineering team.