Introducing Glympsit: Motion Understanding for the Real World

We are surrounded by video streams. From security cameras on factory floors to quality control systems on assembly lines and analytics cameras in retail, our environments are captured 24/7.

Yet, for all this data, most organizations remain "information-poor."

The problem is noise. Critical events—a safety violation, a stocking error, a customer's gesture of intent—are buried in terabytes of mundane footage. Teams either spend countless hours manually reviewing video or, more often, these critical moments are missed entirely.

This is why we're building Glympsit. We believe the future of environmental awareness isn't about more video; it's about smarter video. The key? Micro-videos.

The Power of the "Glimpse"

Glympsit is built for 1–3 second clips. These aren't just short videos; they are high-signal bursts of activity, automatically captured when something important happens.

• A motion event triggers a camera.
• A voice command is issued.
• A sensor is tripped.

Micro-videos capture high-signal bursts of activity without the noise of continuous video monitoring. Instead of sifting through a data lake, you get a curated stream of data points that matter. With Glympsit, these bursts become structured JSON that your systems can trust and act on.

From "What Happened?" to "What's Next?"

The real power of Glympsit is its ability to transform that brief "glimpse" of motion into actionable data.

Instead of a human operator combing through hours of footage, your systems get the exact context they need to:

• Automate checklists: Was the package scanned and placed in the correct bin?
• Detect policy violations: Did a worker enter a restricted zone without the proper safety gear?
• Trigger downstream workflows: Did a customer pick up a specific product, look at it, and place it in their cart?

Glympsit provides the "who, what, and when" in a clean, machine-readable format, enabling true, context-aware automation.

How It Works: From Photons to JSON in Seconds

We designed the Glympsit platform to be a simple, powerful integration for your existing systems. In this post, we walk through how Glympsit ingests short-form video captures, processes them with our motion understanding models, and hands clean JSON events back to your platform within seconds.

1. Ingest: Your on-site device (a smart camera, a sensor-paired device) captures a few-second micro-video when a trigger occurs. It sends this small clip to the Glympsit API.
2. Process: Our motion understanding models analyze the video. We're not just doing simple object detection; we're analyzing movement, interaction, and intent over the full duration of the clip.
3. Return: Our API instantly returns a structured JSON payload. This event describes the action, the objects involved, and the context, ready to be fed into your WMS, safety dashboard, or automation platform.

Join the Motion Understanding Revolution

We are defining a new category: the Motion Understanding API.

This isn't about passive surveillance; it's about active, real-time understanding. We are rolling this out with partner teams across manufacturing, warehousing, and smart retail environments. The feedback has been clear: when systems can finally understand motion, entirely new levels of efficiency and safety become possible.

If you are exploring high-signal event streams and want to build the next generation of automated systems, we would love to hear from you.

→ Request access to the Glympsit Beta