Custom AI-powered video surveillance and computer vision systems with real-time object detection (YOLOv8, EfficientDet), multi-object tracking (DeepSORT, ByteTrack), edge AI deployment, and predictive analytics — from V.A.L.T (2,500+ cameras, 770+ police departments) to MindBox (50+ retail locations). 600+ projects since 2005.
We design and develop custom AI video surveillance, computer vision, and analytics systems that detect objects, track events, and extract intelligence from live or recorded video streams.
From edge AI deployment to cloud-scale processing, we build systems that perform under real-world conditions.
Detect people, vehicles, license plates, PPE compliance, intrusions, and custom events in real time using YOLOv8, EfficientDet, and custom CNNs with DeepSORT/ByteTrack multi-object tracking — as deployed for V.A.L.T (2,500+ cameras, 770+ police departments) and MindBox (50+ retail locations with AI analytics).
Using cutting-edge AI models like YOLOv8, EfficientDet, and custom CNNs, combined with DeepSORT and ByteTrack for multi-object tracking, our systems maintain high accuracy and reliable tracking across cameras in real time.
Transform video streams into actionable intelligence. Our AI analytics engines analyze patterns, detect anomalies, monitor queues and dwell times, and provide predictive risk alerts.
Enrich video data with speech-to-text, NLP metadata extraction, and real-time BI dashboards. Proven with Meetric (25% higher close rates through AI video analysis) and VocalViews (800K+ video research participants).
Deploy on edge devices (NVIDIA Jetson, Intel OpenVINO), on-prem servers, or cloud platforms like AWS, Azure, and Google Cloud.
Production architectures delivering sub-200ms inference latency, handling thousands of concurrent camera streams, optimizing GPU utilization (CUDA, TensorRT), and securely managing multi-site deployments — as proven with V.A.L.T (50K daily users across 650+ organizations).
Unlike traditional CCTV, which relies on human monitoring, AI video surveillance detects, tracks, and analyzes events in real time. It reduces false alarms, improves accuracy, and scales across locations, turning video into actionable intelligence.
Manual monitoring
Automated real-time detection
Human-dependent
90-98% model accuracy (trained)
High
Reduced with AI filtering
Limited
Multi-site cloud scaling
Video playback only
Behavioral & predictive analytics
Our AI video surveillance and computer vision solutions solve real-world challenges across retail, industrial safety, smart cities, healthcare, and law enforcement.
From real-time object detection with YOLOv8/EfficientDet to predictive analytics and edge AI deployment, we transform video feeds into actionable intelligence — helping organizations prevent losses, ensure compliance, and optimize operations at scale.
Custom AI Video Recognition apps for every case. Secure, scalable, and packed with smart features – built by the pros who started it all.
![[background image] image of logistics control room (for a trucking company)](https://cdn.prod.website-files.com/64e8910adc5a63966a68acc1/68e7dfd17638aaf511162f7a_f841ed23dc31eb8a94e23195c64f4acb_develop.webp)
Build your AI video surveillance platform from scratch — object detection models, tracking pipelines, edge deployment, and cloud dashboards. From concept to production with 600+ projects delivered since 2005.
Upgrade existing CCTV/VMS systems with AI analytics — add real-time detection, multi-object tracking, behavioral analysis, and predictive alerts without replacing your camera infrastructure. 10× more insights from the same hardware.
![[digital project] image of a showcased project (for a ai robotics and automation)](https://cdn.prod.website-files.com/64e8910adc5a63966a68acc1/68e7e04abb8f1a3770a8625e_fix.webp)
Rescue stalled AI surveillance projects with model optimization, accuracy improvements, false positive reduction, and edge deployment fixes. We’ve rescued dozens of computer vision projects — improving detection accuracy from 70% to 95%+.
Startup 💡
Core AI detection MVP: single-camera object detection, basic tracking, alert system, and cloud dashboard. YOLOv8/EfficientDet model training with your data. Edge or cloud deployment. 4-6 week delivery.
from
$10,000
from 1 month
Growth 🚀
Multi-camera AI system: advanced object detection, DeepSORT tracking, behavioral analytics, ANPR/LPR, BI dashboards, and multi-site deployment. Supports 100-1,000+ cameras with sub-200ms latency. 2-4 month delivery.
from
$24,000
from 2 months
Enterprise 🏢
Enterprise-grade AI surveillance: thousands of cameras, edge+cloud hybrid architecture, real-time analytics, predictive risk alerts, HIPAA/SOC II compliance, and 99.9% uptime. Multi-region deployment on AWS/Azure/GCP. 4-8 month delivery.
from
$48,000
from 4 months
Building AI video surveillance, computer vision, and real-time video processing systems real-time processingsince 2005. From V.A.L.T (2,500+ cameras for law enforcement) to MindBox (AI retail analytics at 50+ locations) — proven computer vision expertise at production scale.
Computer vision engineers, ML/AI specialists, edge deployment experts, DevOps, QA, and UI/UX designers — all in-house. We think like product owners, not just coders.
Over 600+ projects delivered, V.A.L.T (2,500+ cameras), MindBox (50+ retail locations), 90-98% detection accuracy, 100% Upwork Success rate, and 400+ client reviews.
Get the scoop on AI, advanced models, and custom development – straight talk from the top devs
MVP AI detection systems start from $10,000 (4-6 weeks) for single-camera setups with basic tracking. Multi-camera growth systems from $24,000 (2-4 months) with DeepSORT tracking and analytics. Enterprise-grade platforms from $48,000+ (4-8 months) for thousands of cameras with edge+cloud hybrid architecture. We provide a free detailed estimate after consultation.
Yes. We integrate AI analytics (YOLOv8, EfficientDet, custom CNNs) into existing CCTV cameras, VMS platforms, and NVR systems — adding real-time object detection, multi-object tracking, behavioral analysis, and predictive alerts without replacing your camera infrastructure. As done for V.A.L.T (2,500+ existing cameras upgraded with AI).
Absolutely. We deploy on NVIDIA Jetson (Nano, Xavier, Orin), Intel OpenVINO, and custom edge hardware with TensorRT optimization for sub-200ms inference latency. Edge AI reduces cloud costs by 60-80% and eliminates bandwidth bottlenecks while maintaining 90-98% detection accuracy.
Our models achieve 90-98% detection precision depending on environment, training data, and use case. We use YOLOv8 and EfficientDet for detection, DeepSORT/ByteTrack for multi-object tracking with consistent identity across cameras, and TensorRT for optimized inference. Custom model training with your specific data further improves accuracy.
Yes. We integrate with BI dashboards (Grafana, custom), SIEM/SOAR security platforms, ERP/WMS systems, and alerting channels (SMS, email, Slack). Metadata enrichment using NLP and speech-to-text transforms video streams into structured, searchable intelligence — as proven with Meetric (25% higher close rates) and VocalViews (800K+ participants).
MVP AI detection systems are ready in 4-6 weeks. Multi-camera growth systems with advanced analytics take 2-4 months. Enterprise deployments with multi-site scaling and compliance take 4-8 months. Our Agentic Engineering process accelerates development 2-10× faster than traditional approaches.
