Systems | Development | Analytics | API | Testing

Real-Time Fraud Detection Pipelines: How Fintechs Use ETL for Streaming Data

Your fraud detection system analyzes yesterday's transactions while criminals steal millions today. Financial institutions lose an estimated $33 billion annually to card fraud alone, much of it preventable with real-time detection capabilities. Traditional batch processing that analyzes data hours or days after transactions occur simply cannot keep pace with sophisticated fraud schemes exploiting the settlement window gap.

Automating the Embodied AI Pipeline: A ClearML and Dell Robotics Proof of Concept

Training models for physical robots is harder than training a typical model. The data has to be collected by hand through teleoperation, every change has to be tested on real hardware, and the loop from data to deployment runs constantly. In a recent proof of concept with a Singapore government agency, ClearML, Dell Technologies, and Hugging Face’s LeRobot framework turned that high-touch, manual process into an automated pipeline.

From Backlog to Breakthrough: Inova Scales Data & AI with Fivetran and Databricks

Healthcare organizations operate some of the most complex data environments, spanning thousands of systems across clinical, financial, and operational domains. At Inova Health, this complexity created an opportunity to rethink how data could better support analytics and AI at scale.

Open Data Infrastructure: Built for agentic AI

As AI accelerates the pace of change, demanding fresher data, diverse formats, and support across multiple engines, many teams discover their infrastructure was built for reporting, not real-time AI at scale. Open Data Infrastructure is redefining how organizations design for analytics, operations, and AI. By leveraging Fivetran as an interoperable data foundation, organizations can embrace open standards, separate storage from compute, and keep data portable across clouds and engines, preserving adaptability while scaling AI and operational workloads with Databricks.

Building an AI-ready data foundation at Superhuman with Databricks and Fivetran

As Superhuman expanded its AI platform across Grammarly, Coda, Superhuman Mail, and Superhuman Go, more of the business began to rely on timely data from Salesforce, Outreach, Pardot, Stripe, Zendesk, Qualtrics, and other third-party systems. The challenge went far beyond moving data into Databricks. Go-to-market, finance, and customer teams needed faster, reliable access to trusted data without turning every new data request into weeks of custom engineering.

AgentTAM: From Firefighting to Flight Control with Agentic AI

Ready to scale your corporate support from chaotic firefighting to structured flight control? In this comprehensive overview, we explore how Cloudera leverages its own technology stack to develop Agent TAM—a powerful suite of autonomous AI agents designed to unlock institutional knowledge, streamline customer workflows, and eliminate technical debt. Whether you want to build an automated Case Analyzer or an intelligent planning companion, this guide provides the exact architectural blueprint to transition your engineering teams from reactive firefighting to proactive, data-driven automation.

A Deep Dive into Lakehouse Catalogs

What exactly is a Catalog, and why has it become such a critical component of the modern Lakehouse architecture and AI workloads? In this episode, we break down the differences between technical catalogs (metastores) and business catalogs, explore how catalogs enable governance and interoperability, and explain why the Iceberg REST Catalog specification became the open standard for sharing Iceberg tables across platforms without vendor lock-in.

Spotter Memory: How Your AI Analyst Learns Your Business

You ask your agent a question. The answer is slightly off. You point out the gap. Spotter fixes it, and that fix doesn't disappear when the session ends. Your team doesn't re-explain the same thing tomorrow. The next analyst doesn't start from scratch. The correction stays, and the work gets better from here. That's what memory makes possible. Not just for you. For everyone who comes after.

Bring Your Crisp Conversations Into Your Stack: Announcing the Integrate.io Crisp Connector

Pull conversations, contact profiles, and customer events out of Crisp and into your warehouse, CRM, or AI pipeline, fully transformed, on schedule, with no engineering required. Crisp is a customer messaging platform built around a shared inbox: live chat, email, and social channels routed into one place so support, sales, and success teams can respond from a single view.