VIDEO ANALYTICS & OBJECT TRACKING
Turn Live Video Into Real-Time Awareness
Models that detect, track, and count objects across every frame of your video, so you learn what's happening as it happens, not hours later.
Let's ConnectA Single Frame Tells You What's There, Not What's Happening Over Time
Still-image detection loses the story that lives between frames. It can't tell one object from the same object a second later, so it can't count uniquely, follow something across a scene, measure how long it lingered, or catch an event as it unfolds. And no one has the hours to watch the footage that would.
We pair detection with tracking that gives every object a stable identity from frame to frame. That's what makes it possible to count things once, trace the paths they take, measure dwell time, and trigger the moment something crosses a line, enters a zone, or moves the wrong way, live on a stream or in batch over recordings.
The result is continuous, automated awareness from the cameras you already have, delivered as counts, metrics, and alerts instead of raw video nobody has time to review.
From Raw Footage to Live Metrics You Can Act On
Define the Objects & Events
We agree on what to detect, what counts as an event, and the zones or lines in the frame that actually matter.
Train Detection & Tracking
We train the detector on your own footage and tune the tracker to hold identities through occlusion and crowding.
Build the Analytics Layer
We turn raw tracks into the counts, dwell times, and triggers your team will actually use day to day.
Deploy to Your Streams
We connect the pipeline to your cameras or video feeds and tune it for real-time or batch throughput.
You get continuous, automated insight from your video feeds, counts, movements, and alerts in real time, instead of footage nobody has the hours to watch.
Multi-Object Tracking
We give every object a stable identity across frames, so one thing counted once stays one thing.
Real-Time Detection
We detect the objects you care about frame by frame, fast enough to act on while it's still happening.
Counting & Flow Analysis
We count unique objects and measure how they move through a scene, not just how many appear.
Dwell Time & Trajectories
We measure how long objects stay and the paths they take, turning raw movement into metrics.
Event & Zone Triggers
We fire alerts when objects cross a line, enter a zone, or behave in a way you've defined as worth knowing.
Edge or Cloud Deployment
We run the pipeline on-camera at the edge or centrally in the cloud, wherever latency and cost point.
How we work
Discovery & Feasibility
We start with your goals, data, and constraints, then pressure-test where AI actually adds value. You get a clear scope, success metrics, and a realistic plan before any model is built.
Build, Train & Integrate
We build, train, and evaluate the solution against your real data, then wire it into your existing systems and workflows. Regular checkpoints mean no black boxes, just steady, measurable progress.
Deploy, Monitor & Improve
After rigorous testing for accuracy, safety, and performance, we ship to production. Post-launch we monitor quality, retrain as your data shifts, and keep the system accurate, secure, and improving.
AI-Enabled Delivery
We combine real-time detection models with proven tracking algorithms and streaming infrastructure, so a live video pipeline comes together in weeks instead of being engineered, frame handling and all, from scratch.
Real-Time Detection Models
spot objects fast enough for live streams
Multi-Object Tracking Algorithms
hold identities across frames and occlusion
GPU-Accelerated Inference
keeps throughput high on busy feeds
Video Streaming Pipelines
ingest and process camera feeds reliably
Edge Deployment Runtimes
run models on-device to cut latency and bandwidth
Why OrganByte
Tracking, Not Just Detection
We follow objects across frames so counts and movements are accurate, not inflated by re-detecting the same thing.
Tuned for Real Time
We engineer the pipeline to keep up with live streams, balancing accuracy against the latency your use case allows.
Runs Where It Makes Sense
We deploy at the edge or in the cloud based on your latency, bandwidth, and cost, not a one-size default.
Robust to Messy Footage
We handle occlusion, lighting shifts, and crowding, the conditions that break naive frame-by-frame detection.
500+
projects delivered by OrganByte
24/7
monitoring across live video streams once deployed
Every
tracked object counted once, not once per frame
FAQS about Video analytics & object tracking
A detection-and-tracking pipeline connected to your feeds, the analytics layer that turns tracks into counts and alerts, and dashboards or an API to consume them.
Usually six to ten weeks, depending on the number of cameras, the events you want detected, and whether it runs at the edge or in the cloud.
A fixed fee for the build, scoped to camera count and complexity. Ongoing cloud or edge running costs are separate and estimated upfront.
No. A detector re-finds objects every frame with no memory, so it double-counts and can't measure movement. Tracking gives each object one identity over time, which is what makes counts and dwell times real.
In most cases, yes. We work with standard IP camera and RTSP feeds, and you own the deployed pipeline and the models inside it.
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