AI + Data = Governance You Can't Ignore
As AI agents act on enterprise data, governance failures become business liabilities. Learn why fixing them downstream won’t work anymore.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
Your Guide to EU AI Act Compliance with ClearML
A practical guide to building traceability, governance, and evidence across the AI lifecycle.
CMS Interoperability : Reimagining Prior Authorization with Conversational AI
Prior authorization has long been one of healthcare’s most time-consuming and costly administrative processes, creating friction between payers, providers, and patients. Manual data entry, back-and-forth faxes, and complex coverage rules often delay care delivery and frustrate both clinicians and members. In this webinar, we'll explore how conversational AI — combined with FHIR-based interoperability, contextual understanding, and an agentic approach — can revolutionize the prior authorization process. Discover how AI-driven, human-like interactions can transform prior authorization into a seamless, intelligent workflow.
Sauce Labs Product Roadmap 2026: AI-Driven Path to Quality
Discover what's next for continuous quality testing! Join Larry Goldman (Director of Product Marketing) and Ed Lavalette (Senior Product Manager) as they unveil Sauce Labs' exciting 2026 roadmap and dive deep into new AI-powered testing innovations.
Top 5 AI-Powered SAST Tools for 2026
Static Application Security Testing has survived multiple cycles of skepticism, reinvention, and disappointment. For years, SAST was criticized for producing noise, slowing development, and failing to reflect real-world risk. Yet in 2026, SAST has not disappeared. It has changed its role. The shift is not that static analysis suddenly became perfect. It is that organizations finally stopped asking SAST to do the wrong job.
Why AI Connectivity Matters
Join us for a clear, actionable blueprint for AI infrastructure, where AI strategy becomes production reality.
Connect Databox MCP to n8n: Build Smarter AI Agents
In this video, we show you how to connect Databox to n8n using the Model Context Protocol (MCP). Learn how to give your n8n AI Agents direct access to your business metrics to automate reporting, analysis, and data-driven workflows.
Connect Your Local AI Model to Enterprise Databases with DreamFactory: A Real-World Integration Story
A mid-sized enterprise had a straightforward but powerful idea: use their locally-hosted AI model to automatically generate summaries of employee performance review data stored in their SQL Server database. The workflow seemed simple enough: The reality? This "simple" integration touches on some of the thorniest problems in enterprise software: database security, API orchestration, authentication, timeout management, and reliable data transformation.
Why transparent AI is the only AI you can trust in QA
AI fosters speed. Transparency fosters confidence. AI for QA testing is suddenly everywhere. Every tool claims it’s “AI-powered.” Every demo promises smarter test generation, faster maintenance, and fewer bugs. Plus, with AI accelerating the pace at which developers write and ship code, QA leaders are under growing pressure to keep up. It makes sense that teams are looking for AI for QA testing. But here’s the uncomfortable truth: AI in QA only works if you can trust it.
Introducing the Kong MCP Registry: Connect AI Agents with the Right Tools
In the rapidly evolving landscape of AI-driven development, the Model Context Protocol (MCP) has emerged as the critical standard for connecting AI applications to the data and tools they need. We are excited to announce the Technical Preview (TP) of Kong MCP Registry, a major milestone in our mission to provide the most comprehensive platform for modern API and AI management.