Witbe will showcase its AI-native testing and monitoring infrastructure at IBC2026 in Amsterdam, highlighting self-building tests and AI-driven insights. The company's platform runs on real devices - Smart TVs, set-top boxes, mobile phones, and streaming sticks - on real networks, providing video evidence for every test result. At the booth, visitors can see AI prompts dynamically adapt to user interactions, such as selecting a show or validating content for a kid's profile, ensuring tests stay relevant even as interfaces change. Witbe will also demonstrate how its technology verifies ads, closed captions, and short-form video feeds across multiple platforms, all while explaining findings in plain language. The company continues to release new capabilities continuously, promising even more advancements by the time of the event.
The broadcast and sports industries are increasingly focused on delivering high-quality viewing experiences across a diverse array of devices and platforms. With the rise of short-form and vertical videos, as well as the integration of ads into live feeds, the need for reliable and flexible testing and monitoring solutions has never been greater. Witbe's AI-native testing and monitoring infrastructure, set to be showcased at IBC2026, addresses these challenges by deploying real devices wherever viewers are, adapting to dynamic UI changes, and providing detailed video evidence for every test result. This approach significantly boosts productivity for content providers. At the Witbe booth, visitors can witness firsthand how AI-driven tests can handle complex scenarios, such as selecting specific episodes or validating content suitability, far more effectively than traditional automation methods. The company's continuous release of new capabilities, demonstrated through real-world examples, underscores the growing importance of AI in ensuring integrated and high-quality content delivery across all devices.
Technical and Operational Implications
Witbe's deployment of AI-native testing and monitoring infrastructure involves a range of specific gear and workflows that significantly impact operational efficiency. At the heart of the system are the Witbox devices, which are responsible for real-device execution. These devices support a variety of models, including the Videohub 120x120 and ATEM switchers, ensuring that tests run on the same platforms viewers use. For instance, during the demonstration at IBC2026, Witbe showcased the ATEM Mini Pro 4K, which was used to handle video signals from the AI Test Designer to the Agentic SDK for real-time assessment. The HyperDeck Studio 4K was another key piece of hardware, providing recording and playback capabilities for video evidence.
The Agentic SDK, a Python framework, is a crucial component that integrates AI-driven steps with algorithmic ones. For example, during the demonstration, Witbe used the SDK to create a test scenario that required selecting the latest episode of a show, confirming that the content was suitable for a child's profile, and validating the coherence of new visuals. This hybrid approach allows teams to measure performance KPIs such as startup time, buffering, and MOS-based video quality. The SDK supports a range of devices, from Smart TVs and set-top boxes to mobile phones and streaming sticks, ensuring comprehensive coverage of the viewing experience. The company's commitment to continuous updates means that new capabilities are rolling out frequently, enhancing the system's adaptability and responsiveness to changing conditions.
Witbe's deployment at IBC2026 signals a shift towards more dynamic and flexible testing and monitoring solutions. By integrating AI directly into their infrastructure, Witbe enables real-time adaptation to changes in user interfaces and environments, which is crucial as video services evolve rapidly. This move suggests that the industry is moving towards more intelligent and responsive QA systems that can handle the complexity of modern video platforms.
The next likely step is the widespread adoption of AI-driven testing tools across the broadcast and post-production sectors. With the ability to automate and adapt to real-time changes, these tools will become essential for maintaining the quality and performance of video services. Teams will increasingly rely on hybrid approaches that combine AI with traditional testing methods to optimize both efficiency and accuracy.
As the next quarter unfolds, keep an eye on Witbe's continued integration of AI in real-world testing and monitoring scenarios. The company will showcase its Agentic SDK, which allows for dynamic and adaptive testing that mimics human-like assessments. This capability is particularly crucial as short-form and vertical video content continues to grow, requiring rigorous testing across various devices and platforms. Additionally, Witbe's advanced ad verification solutions will be expanding to cover new formats, ensuring advertisers' content appears accurately and seamlessly in diverse viewing environments.
The Agentic SDK, a key component of Witbe's AI-native infrastructure, integrates seamlessly with various hardware and software to ensure comprehensive testing and monitoring. During the demonstration, Witbe showcased how the SDK can be deployed across different devices and platforms, from mobile phones to Smart TVs, using the ATEM Mini Pro 4K for real-time signal processing and the HyperDeck Studio 4K for recording and playback of test results. This setup allows for the capture of detailed video evidence, which is crucial for verifying the accuracy and reliability of the tests.
Witbe's approach to AI-driven testing and monitoring is particularly significant in the context of the increasing complexity of video services. The company's ability to dynamically adapt tests to user interactions, such as selecting specific episodes or validating content for a kid's profile, is a testament to its advanced AI capabilities. By integrating AI at every layer of the testing process, Witbe is able to provide real-time, context-aware insights that traditional automation methods simply cannot match. This significantly reduces the time and effort required for content providers to ensure their services are up to standard across all devices and platforms.
News submitted by: Mark Ops
