Turning what cameras see into
reliable operational data and actions
Automatically filter noise, add context, and provide possible follow ups.
Trusted by innovative industry leaders:
Select your primary use case
For Safety Managers
Pro-actively detect safety risks early by monitoring possible hazards such as fire, smoke, spills, or unsafe behavior. Automate PPE compliance using multi-stage detection, for example identifying people first and then checking helmets or vests. Refine models to your site conditions and reduce manual safety checks.
For Security Directors
Automate your control room by detecting people and vehicles and applying logic such as dwell time to identify loitering and abnormal behavior. Use VLM to search incidents in natural language, and extend detections with custom classes when needed, for example identifying a person carrying a fishing rod near a restricted zone. Reduce false alarms and help operators focus on the incidents that matter.
For Operations Managers
Turn cameras into operational sensors. Detect specific objects, track assets using OCR, barcodes, or identifiers, monitor process flow with dwell time and zone logic, and detect bottlenecks or deviations in real time. Adapt detections and rules as operations evolve.
For Control Room Managers
Unify alarms, video, and context into a single AI-assisted workflow. Automatically filter duplicate events, enrich incidents with VLM context, and let AI agents guide or execute responses across VMS, access control, and operational systems.
Why teams choose visionplatform.ai
Click and deploy
Start with ready-to-use models and templates to quickly validate a use case without long setup projects.
Tailored to each environment
Improve accuracy and relevance by adding local examples and refining models and rules to match each location, while keeping ownership of your data as the only EU platform being EU AI Act proof.
Ownership and control
Keep control over your data, models, and deployment. Can be easily integrated with existing systems.
Easy to iterate and expand
Update models, logic, and workflows yourself as needed, without rebuilding systems avoiding lengthy development cycles.
The Vision Intelligence Stack
A modular architecture that lets you start with simple detection and scale up to fully autonomous control room AI agents.
1 Detection & Training
The Foundation. Use 15+ ready-to-use models to detect people, vehicles, and objects instantly. Combine these with logic like dwell time (loitering) for actionable alerts. Need something specific? Train custom objects in minutes—like detecting a “person with fishing rod” near restricted water zones.
2 Business Logic
Operational Context. Add areas of interest for alarms and go beyond simple detection—read text (OCR), scan QR and barcodes, and measure dwell time (loitering) to digitize physical operations.
- ✓ OCR / License Plate Recognition
- ✓ Barcode & QR Scanning
- ✓ Dwell Time & Line Crossing
3 GenAI (VLM) Analytics
Our GenAI Vision Language Model (VLM) turns video into structured, human-readable descriptions of objects, behavior and interactions. This enables forensic search, investigation and decision support.
Example Query:
“Show me all instances where a person wearing a cap in our building was acting suspicious”
4 Control Room AI Agent
The Control Room AI Agent uses the situational analyses from step 3 to verify alarms, consult procedures and execute actions across systems. A unified brain that connects detections, GenAI VLM insights, incident manuals, and external control room software to execute workflows and guide or even mimic operators.
1. Received alarm from VP object detection pipeline.
2. Verified with VLM: “No suspicious behavior detected.”
3. Verified with access control system: “No doors opened.”
4. Verified: “Person has not been spotted by cross camera logic on other unauthorized places.”
5. Action: Close alarm in Milestone XProtect.
6. Action: Create incident report about false alarm.
Thanks to multiple security camera’s that were made into smart AI camera’s at both the entrance and exit of the gate, as well as on the reach stackers, we can be sure that the right container departs on the right booking. All container numbers are in our system and each has an owner linked to it. That system is then linked to the cargo cards of the drivers. If this number matches, only then will the barrier open. This prevents the release of incorrect containers and thus saves additional costs.
With the use of a simple security camera with AI software that reads the data from the train wagons and automatically forwards it to our system. If this goes well, we plan to expand it to other locations. We expect to save a lot of time in the process this way.
The implementation of AI-based Gate OCR system is a significant milestone for our terminal. We see this moment as a crucial step in the digitalization of our logistic processes within Broekman Logistics.
The quality of the products that supplai & visionplatform.ai delivers is very good. They are able to switch quickly, like to think along with you, and are open and transparent. Working with them is very pleasant, and we gladly do so in our data lab. Together with all our suppliers and railway users, ProRail continues to innovate for a safe and reliable railway.
From Raw Video to Resolved Action
A continuous pipeline that filters 99% of noise to deliver only the verified insights that matter.
Detect
Use library models, refine them, or add custom areas with own video data to detect exactly what you need.
Filter
Apply logic rules (e.g. dwell time, OCR, zone crossing) to discard 90% of noise.
Understand
Analyze the remaining events with VLM for intent and context.
Resolve
Execute automated responses or guide operator action.
Secure, Real-Time Infrastructure.
Maximize speed and data privacy. Run lightweight on-site detection and GenAI VLM analysis on your secure On-Premise servers.
Integrations
- VMS Milestone XProtect
- Standard RTSP / ONVIF
- Rest API
- MQTT (dashboarding)
- AI agents
Next step? Plan a free consultation
Leave your details and we’ll plan a 30 min session.