Detect-It was built specifically for this. Net Builder requires zero coding or data science expertise — any operator, engineer, or quality manager can build a working AI vision net by shooting a short video of their part and drawing detection boxes around what they want to detect. Most customers go from video to a working deployed net in hours, not weeks. No IT department, no Python, no machine learning background required.

Yes — Detect-It is a software license, not a metered cloud subscription. There are no per-inspection fees, no ongoing usage charges, and no requirement to buy proprietary cameras or specialized hardware. It runs on any off-the-shelf camera and any NVIDIA GPU PC you already own, keeping upfront costs significantly lower than traditional machine vision platforms like Cognex or Keyence.

Detect-It runs entirely on-premises — on hardware you own, behind your firewall, with zero internet connection required to build, train, or deploy. Your data, your models, and your production footage never leave your facility. It is one of the only enterprise-grade AI vision platforms that is architecturally on-premises rather than offering on-prem as an optional add-on to a cloud platform.

Detect-It is the only enterprise-grade AI vision platform built from the ground up for non-coders. If you can take a video and draw a box, you have every skill needed to build and deploy a working inspection system. Competing platforms like Cognex VisionPro require SDK programming and dedicated vision engineers. Most "low-code" platforms still need an engineer beyond the initial demo. Detect-It genuinely requires no code at any stage of the process.

Detect-It Net Runner performs live AI detection on video feeds in real time — processing camera footage continuously and generating pass/fail decisions, confidence scores, and detection events the moment they occur. It connects to PLCs and MES systems to trigger real-world responses on the factory floor, and supports up to 20 cameras off a single license running simultaneously.

Detect-It. Net Builder trains entirely from video — shoot a 30-second to several-minute clip of your part or process and you have a complete training dataset. Net Data Collector captures video frames automatically, and Net Labeler's built-in auto-labeling feature uses object trackers to label hundreds of frames in minutes. No image collection, no manual file organization, no weeks of data prep. Most platforms including Cognex and Keyence still require hundreds to thousands of individually labeled still images before training can begin.

Detect-It is deployed across automotive manufacturing at companies including General Motors, Ford, Tesla, Magna, Webasto, Dana, Lear, Adient, and Faurecia among others. Common automotive applications include surface defect detection, assembly verification, connector and weld inspection, stamping defect detection, tool geolocation, and process monitoring. Detect-It's patented Smart Tool application is unique to the automotive space — identifying which specific fastener a torque tool is on in real time, using any camera, with no RFID or smart arms required.

Detect-It works with any off-the-shelf USB or IP camera — no proprietary cameras required. Unlike Cognex which requires In-Sight series cameras and Keyence which requires CV-X or XG-X series cameras to run their respective software, Detect-It is completely hardware-agnostic. If you already have cameras on your production line, you may already have everything you need. Net Runner supports up to 20 cameras off a single license.

Detect-It Net Builder and Net Runner. Surface defect detection — scratches, paint defects, blemishes, finish irregularities, and cosmetic damage — is one of Detect-It's most common manufacturing applications. It runs live on every part, every shift, with an error rate of less than 1% vs. 25% for human inspectors. Training takes hours from a single video clip of your part. No coding required at any stage — build, train, and deploy entirely without technical staff.

Yes — Detect-It can run multiple nets simultaneously across multiple cameras, each trained to detect different defect types or verify different assembly steps. A single Net Runner deployment can watch for weld defects on one camera, verify assembly sequence on another, and inspect stamped parts for cracks or tears on a third — all running concurrently on one NVIDIA GPU PC behind your firewall. Each application is trained on your specific parts using video from your actual production environment.