# Computer vision development | Slash Digital Lab, Bogotá Source: https://slash-digital.io/en/computer-vision/ Artificial intelligence Detection, tracking, OCR and store analytics: models built on your real data, cloud or edge, tied to decisions that change when the model is right. - Deploy Cloud · edge - Cases Retail · DOOH · CCTV - Evaluation On real data Start a project See real work In short Slash Digital Lab builds computer vision for companies, and it only pays when it answers a decision: how many people entered, which product is missing from the shelf, whether content reached the screen. We build and deploy models on your data, with accuracy and cost per inference reported. Published cases: Peoplesnap processes selfies with live moderation; L'Oréal Guardians combined vision and GenAI for brand avatars. What we deliver ## Vision problems we solve From corporate CCTV to the stadium screen: wherever there's a camera, there's a decision to improve. 01 ### CCTV analytics Occupancy, queues, hot zones and alerts, with privacy by design and defined retention. 02 ### Retail Planograms, shelf availability and traffic heat maps in store. 03 ### DOOH & events Interaction detection, live mosaics and moderation before anything hits a screen. 04 ### OCR & documents Structured extraction from documents into your systems. How we work ## From pilot to production - ### Define the decision Scope starts from the metric that changes when the model is right. - ### Data Collection, labeling and honest splits; no leakage, no inflated metrics. - ### Model Architecture chosen by accuracy, latency and cost; cloud or edge deployment. - ### Operation Drift monitoring, retraining and alerts: the model stays alive. Scope and deliverables ## What the project delivers - **Use cases:** Retail, DOOH, CCTV, industry and documents. - **Deployment:** Cloud (API) or edge (on-device) by latency and compliance. - **Metrics:** Precision, recall, latency and cost, per class and condition. - **Privacy:** Data minimization, anonymization and defined retention. - **Hardware:** We integrate standard cameras and edge boxes; we don't manufacture. - **Languages:** Spanish, English and French. Proof in production ## Vision in production Read more LA LOGE · Voice cataloguing ### LA LOGE: show the garment, talk, and the record fills itself A PWA with a French voice assistant (OpenAI Realtime) that catalogues second-hand film costumes from a phone, and LA LOGE Source, where costume teams search that stock. Learn more → Read more CENOMI · MAPIC 2026 ### An AI kiosk that puts visitors in Jeddah Park An iPad kiosk in French, English and Arabic for CENOMI's MAPIC 2026 stand: Gemini places the visitor in a Jeddah Park spot, and the 2:3 souvenir comes out in print or by QR. Learn more → Read more Peoplesnap ### From smartphone to DOOH mosaic, without a single booth Peoplesnap is Slash Experience's photobooth product: a white-label web app that turns each guest's phone into the activation. QR, selfie, AI editing (100+ parameters), social share, print and mosaics on event screens. Already live for Mouton Cadet, La French Tech Bordeaux, CEA Marcoule, Denver Pub Crawl, With Agency, We Love Beer and CES Las Vegas 2024. Learn more → Read more L'Oréal · Guardians ### From GenAI selfie to a 3D brand mosaic Guardians program for L'Oréal: GenAI face-swap in Celebrate Consumer Care (pick a Guardian, selfie → brand avatar) and, as the centerpiece, a gigapixel Three.js mosaic where hundreds of avatars form the logo, navigable in 3D for demos and lobbies. Learn more → Frequently asked questions ## The questions we hear often **Will it work with our current cameras?** Almost always; discovery evaluates streams, resolutions and network constraints. **Local or cloud?** Depends on compliance and latency; both routes are part of the proposal. **How do you guarantee accuracy?** Evaluation on real data with temporal splits, reported per class and condition. **Do you process video at the edge?** Yes, where latency or privacy requires it; cases are in production. **How long is a pilot?** Weeks; scope depends on the quality and volume of available data. **What do you need to start?** The decision you want to improve and the metric that changes when the model is right, plus real images or video from your operation. From there we handle collection, labeling and honest data splits, and discovery reviews your streams, resolutions and network constraints. **How do you comply with personal-data rules?** We count without recognizing: the image is personal data while it is processed, so we design with minimization, anonymization and defined retention. In Colombia we apply Law 1581 and the SIC's video-surveillance guide, with a visible notice and a defined purpose, and in Europe, the GDPR.