Systems | Development | Analytics | API | Testing

Ep 64 | AI Managed Services: A Smarter Path for SMEs

AI adoption is accelerating across small and medium-sized enterprises (SMEs), but many businesses lack the in-house expertise to build and manage AI infrastructure effectively. In this episode of The AI Forecast, Paul Muller speaks with Hyve’s Marketing and Operations Director, Charlotte Webb, about how managed service providers (MSPs) are reshaping AI adoption for SMEs. They explore the build vs. buy debate in AI solutions and why cloud computing alone doesn’t guarantee lower costs, better performance, or compliance.

Evolve25: Customer Fireside Chat with Banco do Brasil

Learn how the oldest bank in Brazil manages over 800 AI solutions and 5,500 GenAI use cases while maintaining a "Responsible AI" framework. Discover the bank's three-block ROI strategy focusing on operational efficiency, customer satisfaction, and new business models. This session is a must-watch for enterprise leaders navigating the intersection of legacy infrastructure, culture shifts, and Agentic AI.

How to Implement Your First ML Function in Streaming

The most effective way to adopt streaming machine learning (ML) is not by rebuilding your entire platform but by adding a single, high-value inference step to your existing data flow. This incremental approach allows you to transition from batch-based processing to real-time decision-making without the risk of a "big bang" migration, ensuring that your microservices architecture remains agile and responsive. What Is Streaming ML? ML in streaming is the practice of.

Why Your AI Pilot Won't Make It to Production (And What to Do About It)

Most AI pilots fail to reach production not because the models don’t work, but because enterprises struggle with data governance. While pilot-phase AI projects demonstrate impressive results in controlled environments, they hit governance walls when moving to enterprise-scale deployments. This post examines why AI initiatives stall before production and provides a governance-focused approach for breaking the cycle.

The top 11 AI-assisted automated testing tools for QA in 2026

When it comes to QA, AI-powered automated testing tools promise more speed, better coverage, and lower maintenance. But they don’t all solve the same problems, and their approach to solving problems can be fundamentally different. Some platforms lean heavily into autonomy. Others focus primarily on speed or aggressive self-healing. A smaller group applies AI in specific parts of the workflow while preserving test execution reliability and human control.

Stop GenAI Rate Limits: Model Routing & Token Throttling with WSO2 AI Gateway

Learn how to mitigate skyrocketing AI costs and prevent model outages using the WSO2 AI Gateway. This step-by-step tutorial shows you how to move beyond simple request limits and implement smart, token-based usage policies. We also demonstrate "Adaptive Model Routing" showing you how to automatically switch between models when rate limits are hit, and how to distribute traffic using weighted round-robin to optimize for cost and performance.

AI Input vs. Output: Why Token Direction Matters for AI Cost Management

In the burgeoning intelligence economy, AI tokens are a metered utility, but enterprise profitability now hinges on a critical distinction: output tokens can cost up to 10x more than inputs, creating a new, invisible risk for cost overruns, particularly with Agentic AI. Learn how Kong AI Gateway and Konnect Metering & Billing provide the essential financial control plane to enforce directional guardrails, protect margins, and turn token consumption into realized revenue.

Confluent Cloud for Government Achieves FedRAMP Moderate: Mission-Ready Data Streaming for Federal Agencies

Federal agencies must perform a high-stakes balancing act: Modernize legacy systems, break down data silos, and deliver real-time citizen services—all while operating under strict security and compliance requirements with constrained budgets and staff. Today, we're announcing that Confluent Cloud for Government (CCG) is now available on the FedRAMP Marketplace, with FedRAMP Moderate authorization achieved through the competitive FedRAMP 20x Pilot program.

From Dumb Pipes to a Smart Data Plane: Introducing Schema IDs in Apache Kafka Headers

Apache Kafka powers massive, mission-critical data streams at enterprises worldwide. But in many organizations, those streams still behave like dumb pipes: raw JSON or bytes flowing between services, limited governance, weak contracts between teams, and data that’s hard to reuse for analytics or artificial intelligence (AI).