Your cameras see everything.Your AI understands all.In under 300ms.
VisionCam plugs AI into your existing IP cameras. Intrusion detection, fire, license plate recognition, 99.7% accuracy, zero extra hardware.
- detection accuracy
- 99.7%
- false positives
- −94%
- response time
- 0.3s
- extra hardware
- 0
Orders of magnitude the installation aims for; they are measured on your premises during the audit, on your volumes.

Fully automated, nothing to manage.
Plug & play on your cameras
RTSP and ONVIF compatible, works on all IP cameras. No hardware swap. Connected to your existing infrastructure in under 30 minutes.
Multi-scenario detection
One stream, dozens of use cases. Intrusion, fire, license plates, crowd density, analyzed simultaneously, no extra configuration.
Instant alerts
The moment an event is detected, your team gets a sub-second notification with video snapshot, timestamp and AI confidence score.
Live in days, not months.
- 01
Connect your video streams
Drop your RTSP URL or enable ONVIF auto-discovery. VisionCam detects and imports your cameras in a few clicks, no downtime.
- 02
Define zones and scenarios
Draw your detection zones on the frame. Pick alert types: intrusion, fire, LPR, crowd. No code required.
- 03
Continuous monitoring and alerts
AI scans your feeds 24/7 and pushes alerts instantly via Slack, SMS, email or webhook. Central dashboard included.
The pipeline behind this offer.
We plug the agent into the tools you already use.
Opencv
Pytorch
GoogleCloud
Slack
Groq
Nothing to learn: we configure and operate these connections for you.
Your cameras roll. Nobody watches.
3:17 AM. On site C, a figure in a black hoodie skirts the north gate. Camera 12 catches him perfectly, as it has for four years. But the guard is staring at 84 simultaneous screens, the next desk is on break, and the physical alarm never tripped because the intruder touched no sensor. Tomorrow morning you find three pallets gone. You scrub back the video. The proof was there, intact, for seven hours. Nobody saw him walk in.
IHS Markit estimates that 70% of B2B surveillance footage is never watched in real time. A 2025 ASIS International report documents that CCTV operators lose 95% of their attention after 22 minutes in front of a video wall, a figure confirmed by cognitive psychology labs. Meanwhile, the AI-on-existing-IP video market is growing 28% per year: today, it is the software layer, not the camera, that defends the site.
Wikolabs installs AI systems built on open-source models, on your premises, paid once. No black box: your data, your prompts and your history stay in your infrastructure. We quote at a fixed price or on time and materials, never per ticket or per token, and we say before you sign what works and what does not yet.
Concretely: you give us your RTSP streams, we plug the AI in in under 30 minutes, you draw the sensitive zones. From there, every frame is analyzed in 0.3 seconds, intrusion / fire / LPR / crowd density run in parallel on the same feed, 99.7% accuracy, −94% false positives. When an event triggers, snapshot + timestamp + confidence score land in Slack in under a second. Your cameras already exist. VisionCam finally makes them useful.
Turn your surveillance cameras into intelligent control systems
Your IP cameras generate hours of video that nobody watches. A human operator can't effectively monitor more than 4 streams simultaneously. And incidents are detected after the fact, not in real time. Machine Vision on IP Cameras analyzes every frame in real time, detects relevant events (intrusion, non-conformity, counting, anomaly) and triggers instant alerts, directly from the camera or on an edge device.
Human surveillance is expensive, partial and reactive. Basic motion detection systems generate too many false positives. Commercial smart cameras are poorly customizable and expensive. And cloud processing of real-time video is latent and bandwidth-heavy.
We deploy object detection models directly on an NVIDIA Jetson or Raspberry Pi connected to your IP cameras via RTSP. The model analyzes streams in real time, detects configured events (person, vehicle, product defect, missing PPE) and sends an alert with annotated capture in under 500ms. Processing stays local.
How we deploy
- 01Detection event definition
Workshop to precisely define objects, behaviors or non-conformities to detect. Collection of video examples if available.
- 02Hardware selection & configuration
Edge device selection based on processing load. Installation and configuration of RTSP stream connection from IP cameras.
- 03Model training & optimization
Detection model fine-tuning on your specific scenarios. Optimization for target hardware (TensorRT, TFLite).
- 04Deployment & alert system
Pipeline deployment, alert configuration (webhook, Slack, email, SMS) with annotated captures and timestamps.
Concrete benefits
Every camera monitors permanently, without fatigue, without distraction. Important events no longer go unnoticed.
Detection and alert are instant. An intrusion, product defect or safety incident is flagged before any escalation.
Every detected event is archived with annotated capture and timestamp. Automatic visual audit for compliance and traceability.
Frequently asked questions
Which IP camera brands are supported?
Can behaviors be detected (fall, fight, PPE)?
Can local processing handle multiple cameras simultaneously?
Is video data stored?
Your smart cameras live in 30 minutes
Demo on your own streams. Zero extra hardware. Zero commitment. Reply within 24h.