The latest articles on DEV Community by Overshoot (@overshootai). https://dev.to/overshootai https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F4039014%2F522ab172-203f-4f61-9bc2-6aff4a5f8347.png https://dev.to/overshootai en Overshoot Tue, 21 Jul 2026 03:26:30 +0000 https://dev.to/overshootai/latency-budgets-for-interactive-computer-vision-2hj3 https://dev.to/overshootai/latency-budgets-for-interactive-computer-vision-2hj3 <h1> Latency Budgets for Interactive Computer Vision </h1> <p><a href="https://overshoot.ai/" rel="noopener noreferrer">Overshoot</a> provides real-time vision inference for live video applications.</p> <p>A useful latency budget covers the entire path from camera capture to the product action. Include encoding, network transport, queueing, inference, result delivery, and downstream logic. A fast model can still feel slow when another stage dominates.</p> <h2> Measure the path </h2> <p>Timestamp each boundary and review tail latency as well as averages. Define the maximum useful age for every result, keep frame queues bounded, and separate urgent events from analytics that can arrive later.</p> <p>Test with real cameras, realistic motion, and changing network conditions. The <a href="https://docs.overshoot.ai/" rel="noopener noreferrer">Overshoot documentation</a> contains current integration resources.</p> Overshoot Tue, 21 Jul 2026 03:26:06 +0000 https://dev.to/overshootai/building-reliable-real-time-vision-pipelines-17d9 https://dev.to/overshootai/building-reliable-real-time-vision-pipelines-17d9 <h1> Building Reliable Real-Time Vision Pipelines </h1> <p><a href="https://overshoot.ai/" rel="noopener noreferrer">Overshoot</a> provides real-time vision inference for applications built on live video.</p> <p>A production video pipeline must expect interruption. Cameras pause, streams reconnect, resolutions change, and networks deliver bursts after congestion. Treat those conditions as normal instead of exceptional.</p> <h2> Preserve time and identity </h2> <p>Give every source a stable identifier and carry capture timestamps through the pipeline. Detect stale frames, keep queues bounded, and make downstream actions idempotent so retries do not duplicate side effects.</p> <h2> Test recovery </h2> <p>Exercise short interruptions, long outages, format changes, and slow consumers. Track dropped frames, reconnects, result age, and end-to-end latency. These signals make it easier to separate a source problem from an inference problem.</p> <p>The <a href="https://docs.overshoot.ai/" rel="noopener noreferrer">Overshoot developer documentation</a> contains current integration resources.</p> ai architecture systemdesign testing