Question 1

Can your video analytics systems run on our existing IP cameras?

Accepted Answer

Yes, our solutions are camera-agnostic and work with any modern IP camera that supports RTSP or ONVIF protocols. You do not need to purchase expensive new cameras to utilize our analytics software. We simply ingest the existing video streams directly into our processing pipeline.

Question 2

Do you run the video processing on-premise or in the cloud?

Accepted Answer

We offer flexible deployment models based on your bandwidth and security requirements. We can deploy on-premise edge hardware using NVIDIA Jetson devices to process video locally. Alternatively, we can route streams to cloud infrastructure for centralized processing and easier management.

Question 3

How do you handle privacy regulations like GDPR?

Accepted Answer

We design privacy-first systems by implementing automated redaction directly at the edge. The pipeline can automatically blur faces and license plates before the video is stored or analyzed. This allows you to collect valuable operational metrics without violating user privacy laws.

Question 4

What is the detection accuracy of your video analytics models?

Accepted Answer

Accuracy depends on lighting, camera positioning, and object density, but our custom-trained models typically achieve 95% to 99% accuracy. We conduct extensive testing on your actual environment to refine detection parameters. This ensures we minimize false positives from shadows or environmental changes.

Question 5

What kind of hardware is required for local processing?

Accepted Answer

For local edge processing, we typically recommend NVIDIA hardware such as Jetson Orin modules or industrial PCs equipped with TensorRT-compatible GPUs. These devices are optimized to run multiple deep learning streams simultaneously. We will help you select the most cost-effective hardware.

Question 6

Can the system detect complex behaviors like falls or fights?

Accepted Answer

Yes, we build action recognition models that analyze sequence frames to detect behavioral anomalies. The system can recognize specific actions like slipping, falling, fighting, or loitering. These triggers can instantly alert security personnel to take immediate action on-site.

Question 7

How long does it take to deploy a video analytics solution?

Accepted Answer

A standard deployment using pre-trained models for object counting takes 4 to 6 weeks. If we need to train custom models for specific proprietary objects, the project can take 8 to 12 weeks. This timeline includes setup, training, and onsite optimization.

Question 8

Can the video analytics system integrate with our CRM or ERP?

Accepted Answer

Absolutely. We build integrations that expose detected events via webhook or REST API. This allows video analytics metadata (like customer counts or anomaly alerts) to trigger workflows in your CRM, ERP, or warehouse management systems. Your business processes become automatically responsive to real-world events.

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