Systems | Development | Analytics | API | Testing

The missing transport layer in user-facing AI applications

Most AI applications start the same way: wire up an LLM, stream tokens to the browser, ship. That works for simple request-response. It breaks when sessions outlast a connection, when users switch devices, or when an agent needs to hand off to a human. The cracks appear in the delivery layer, not the model. Every serious production team discovers this independently and builds their own workaround. Those workarounds don't hold once users start hitting them in production.

Introducing AI-Powered Automation with Xray's AI Test Script Generation

Test automation is essential for modern software delivery. It supports faster feedback loops, strengthens release confidence, and enables continuous integration at scale. Yet despite its importance, many teams struggle to expand automation at the pace they need. The biggest obstacle is not validating functionality. It is converting structured manual tests into actionable automation scripts. Manual tests already represent validated logic.

WSO2 AI Guardrails: PII Masking, Prompt Injection & Safety

Generative AI offers incredible potential, but it comes with real risks like data leakage and prompt attacks. In this video, we demonstrate how WSO2 AI Guardrails act as an intelligent filter to secure your AI integrations and ensure compliance. We walk through the configuration of four critical advanced guardrails to inspect both incoming requests and outgoing responses, helping you move from risky experiments to safe, reliable production services.

Enterprise AI Infrastructure Security Series - 5) Compute & Data Access Governance

Securing ClearML for the Enterprise — Part 5: Compute & Data Access Governance In this video we walk through ClearML's compute governance layer — resource pools, resource profiles, and resource policies — and how they work together to give every team fair, governed access to your GPU infrastructure while keeping it fully utilized. What we cover: Previous videos in this series.

Enterprise AI Infrastructure Security - 4) Service Accounts & Automation Security

Securing ClearML for the Enterprise — Part 4: Service Accounts & Automation Security In this video we walk through ClearML's service accounts — the identities behind your automated workloads — and how impersonation ensures least-privilege execution across your agents, pipelines, and schedulers.

Launching Project SnowWork - Bringing Outcome Driven AI to Every Business User

Project SnowWork empowers business teams to automate multi-step workflows end-to-end, and drive real outcomes. Create revenue snapshots, diagnose missed forecasts, and generate summary slides with next steps — all without any coding experience needed.

Meet SmartBear BearQ - QA for the Age of AI

The AI revolutionized coding, but software testing hasn’t caught up. Until now. Meet BearQ: QA built for the age of AI. BearQ introduces a new paradigm of autonomous, agentic quality assurance. Instead of static scripts and brittle frameworks, BearQ’s specialized AI agents – the QA Lead Agent, Tester Agent, and Explorer Agent – work continuously to: Testing was a static checkpoint. Now it’s a living, learning system that ensures application integrity.

SmartBear Application Integrity Core | Redefining software quality for the AI era

Agent-powered code generation is happening at unprecedented speed, creating a growing gap between development velocity and your ability to validate what's being built. This leaves organizations unsure if their applications are doing what's intended or missing what's required. That's why SmartBear delivers application integrity for the AI era – ensuring continuous, measurable assurance that your software just works as intended, with governance to operate at AI speed and scale.

Ep 65 | The Vibecoding Liability: How Unchecked AI Can Kill Cloud ROI

Cloud computing promised efficiency, scalability, and reliability. But as AI workloads grow more complex, many enterprises are learning the hard way that these promises don’t come automatically. In this episode of The AI Forecast, Paul Muller sits down with Linthicum Research founder David Linthicum to talk through the real state of hybrid cloud strategy and enterprise architecture in the age of cloud computing and AI.

Operationalizing the Model Context Protocol: Unified Governance with the WSO2 MCP Gateway

The WSO2 API Platform offers an MCP Gateway that sits between MCP clients and the MCP servers they use, applying security, access control, rate limits, observation, and policy enforcement across all tool calls. Instead of requiring teams to write these controls directly within their MCP servers, the platform extends its existing API governance layer to cover MCP traffic.