Product: Resources

If you've ever built a product that handles video uploads, screen recordings, or live streams, you've probably encountered FFmpeg. Most teams start using it for quick conversions and six months later find it running their entire media pipeline. Once you're in production, you can't just run ffmpeg -i input.mp4 output.webm and walk away. You need

As agents become more commonplace, new protocols are being invented to simplify and standardize complex workflows. With so many emerging standards, it's increasingly important to know which to use and how they fit together. This guide breaks down the most widely recognized AI agent protocols and explains how they interoperate, overlap, and complement each other.

If your app doesn't engage users where they already are, you risk losing them. That's why most successful apps use both activity feeds and in-app notifications, yet teams can blur how each should be used. It's common to see overlap in implementations for both features, such as surfacing every new comment or update twice. This

Getting users to download your app is just the first part of the equation. Keeping them active and engaged takes thoughtful, ongoing communication. And notifications play a central role in that. In-app and push notifications are two of the most effective ways your app can interact with its users. They can inform, motivate, and retain

Like remote work and home deliveries, the telemedicine industry experienced a surge in demand during the COVID-19 pandemic due to the need for distance and self-isolation. In fact, telehealth usage grew from 37% pre-COVID to 67% during the height of the pandemic. But have those adoption levels remained stable or continued to grow as the

WebRTC has become the standard transport layer for AI agents requiring real-time voice and video. Originally designed for browser-to-browser video calls, WebRTC is a protocol stack that enables real-time audio and video communication over UDP. Because it prioritizes low latency over guaranteed delivery, it is ideal for the sub-500ms response times that natural conversation requires.

Object detectors such as YOLO and EfficientDet treat each video frame independently. This works fine for static images, but in real-time video streams, it causes detections to flicker. Bounding boxes jitter, confidence scores oscillate near thresholds, and objects "blink" in and out of existence. In a display overlay, this is merely annoying. In a closed-loop

When building multimodal systems that need to sync audio and video in real time, one question matters more than you'd expect: Can the lips match the voice? Get it wrong, and your AI character looks like a dubbed foreign film. Get it right, and it feels real. And getting it right depends heavily on your