Systems | Development | Analytics | API | Testing

confluent

Thunai Automates Customer Support with AI Agents and Data Streaming

Jan 23, 2026 By Aditya Santhanam In Confluent
Support teams live in a world of repetitive questions, fragmented tools, and growing customer expectations. Customer service agents bounce between customer relationship management (CRM) systems, ticketing, email, and chat while customers wait, often repeating the same information across channels. Batch-based systems are unscalable for AI: Context is always a step behind, escalations pile up, and it’s difficult to intervene in time.
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InsightSoftware

Top Features of Business Budgeting Software & Planning Platforms

Jan 23, 2026 By InsightSoftware In InsightSoftware
Businesses of all sizes rely on detailed budgets to stay aligned on internal goals, monitor their spending, and make decisions that advance their company. Without an effective budget process, businesses increase their risk for costly errors, react more slowly to market shifts, and spend more time on managing numbers than on advancing strategy.
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alphabin

Top 45 Test Management Tools

Jan 23, 2026 By Pratik Patel In Alphabin
Have you ever managed test cases in spreadsheets and struggled to track what was tested and what was missed during a release? This is exactly why modern QA teams rely on powerful test management tools to bring structure, visibility, and control into their testing process. As applications grow with microservices and CI/CD pipelines, testing becomes harder to manage. This is where test management software brings structure, visibility, and control.
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integrate

How ETL Tools Reliably Load CSV Data into Custom Salesforce Objects

Jan 23, 2026 By Donal Tobin In Integrate
This guide explains how ETL tools reliably load CSV data into custom Salesforce objects with strong validation, structured error handling, and resilient recovery. It is written for data engineers, RevOps, and platform teams operating production integrations. Readers will learn core architectural components, a step-by-step implementation plan, and day-two operations. The guide assumes cloud-hosted ETL, API-accessible Salesforce orgs, and automated deployments.
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integrate

Microsoft Fabric vs MuleSoft vs Dedicated ETL for Salesforce Pipelines: 2026 Architecture Decision Guide

Jan 23, 2026 By Donal Tobin In Integrate
Selecting the right backbone for Salesforce pipelines is difficult because each option optimizes for different tradeoffs. This guide compares Microsoft Fabric, MuleSoft, and a dedicated ETL approach with Integrate.io from a Microsoft-first perspective. We explain when each shines, what to watch out for, and how costs and complexity scale. Throughout, we highlight where Integrate.io fits best for Salesforce-centric data movement without adding platform sprawl.
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qlik

Building the Foundation for Responsible Autonomy: Preparing for the Agentic Era of AI

Jan 23, 2026 By David Wilmer In Qlik
Over the past two years, generative AI has transformed how we create, learn, and interact. But a more profound shift is already underway—one that changes not just how we work but who (or what) does the work itself. We are entering the era of agentic AI, where systems don’t merely answer questions—they reason, decide, and act on our behalf.
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confluent

Starting With Purpose: In-Person Onboarding in a Remote-First World

Jan 23, 2026 By Colleen McCreary In Confluent
The hardest part about remote work is building real connection and purpose when everyone is not in the same room. At Confluent, we know flexibility is essential, but we also know that great work and a sense of belonging don’t just happen; they take effort. That’s why we’re intentional about how we bring people together, starting from day one.
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Common Kafka Anti Patterns and How to Avoid Them

Jan 23, 2026 By Perforce In Perforce
Kafka is powerful—but common Kafka mistakes can quietly undermine performance, reliability, and scalability. In this video, two OpenLogic experts break down the most frequent Kafka anti-patterns they see in real customer environments—and how to avoid them. Based on hands-on experience fixing production Kafka clusters, this discussion covers: If you’re running Apache Kafka in production—or planning to—this video will help you spot Kafka mistakes early and apply proven best practices to build a more stable, scalable event streaming platform.
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