Process hundreds of video feeds simultaneously without performance compromise
Software development with end-to-end competence
Computer Vision Platform
Analyse video streams at scale, reuse existing cameras, and deploy new analytics capabilities
without rebuilding your camera environment.
100x
Camera streams analyzed in parallel
20 fps
True real-time processing
Capture every critical event with high-frequency, low-latency analytics
10x
Easier to maintain
Simplified architecture reduces operational effort and lifecycle cost
Existing camera infrastructure is the most cost-effective foundation for scalable computer vision.
Common challenges we help solve
Existing camera environments are costly to replace just to gain new analytics capabilities.
Fixed camera-based analytics can limit flexibility, scalability and future development.
Updating analytics device by device creates lifecycle complexity and operational overhead.
Video insights often remain isolated instead of becoming part of wider operational data and decision-making.
What the platform is
Wapice Computer Vision Platform is a scalable software-based approach to video analytics.
It processes and analyses hundreds of video streams in real time and supports city-wide, industrial, property, traffic and infrastructure environments where performance, flexibility and lifecycle efficiency are critical.
Why a platform approach
With our platform you can use your existing standard IP cameras. You do not need to purchase, install and connect new dedicated AI cameras to get started.
Reuse existing cameras
Save costs: Start with the camera infrastructure you already have instead of replacing it with new dedicated AI cameras.
Centralise analytics development
Deploy new analytics models and functionalities centrally across connected streams instead of upgrading cameras one by one.
Support multiple use cases on the same stream
Use the same camera feeds for traffic analysis, occupancy, safety detection, ANPR, site monitoring and other analytics needs.
Reduce lifecycle complexity
Simplify software updates, improve consistency and avoid device-by-device maintenance across growing camera fleets.
Keep architecture flexible
Combine standard IP cameras, existing fleets and smart cameras in the same solution instead of locking the customer into one hardware model or vendor path.
Open and interoperable
The platform is fully open and interoperable. Detected events and analytics results can be delivered to IoT-TICKET, other cloud platforms, data lakes, command centers, dashboards or enterprise systems through standard interfaces.
This ensures flexibility to integrate with existing customer architectures and avoids unnecessary vendor lock-in.
Supported use cases
The platform supports a wide range of computer vision use cases and can evolve as new analytics needs emerge. Typical use cases include:
Traffic flow and speed analysis
Crowd and occupancy monitoring
Parking monitoring, automatic number plate recognition (ANPR)
Safety risk and hazardous situation detection
Unauthorized access detection
Missing PPE detection, unsafe worker behavior detection
Site monitoring and situational awareness
Process and operations optimization
Real-time intrusion detection and perimeter security
Flexible deployment options
The platform can be deployed according to customer needs. It can be installed on-premises in the customer’s own environment or delivered as a service from Wapice’s secure data center environment.
This allows the solution to support different requirements related to data management, security, latency, integration architecture and operational responsibility.
Key benefits
- Reuse existing cameras and reduce new hardware investments
- Scale analytics across large camera environments more efficiently
- Add new analytics capabilities without replacing camera hardware
- Simplify software updates and lifecycle management
- Reduce vendor lock-in through open, interoperable architecture
- Combine video-derived events with wider operational data in IoT-TICKET or other systems
Key benefits of building AI capabilities with a partner:
- Move faster from AI opportunity to concrete action.
- Focus on the use cases that are worth prioritising.
- Avoid disconnected pilots and costly false starts.
- Build AI solutions that are ready for real use, not just proof of concept.
- Strengthen internal capability through training, collaboration and shared ways of working.
- Create a stronger foundation for long-term AI development and governance.
How we work
We begin every project with a collaborative phase to understand your data, processes, and objectives. From there, we move rapidly to proof of concept and after validation, to scalable implementation.
1) From the challenge to use case
We begin by understanding your goals, data, processes and current readiness. This can start with a focused workshop, maturity assessment or use-case discovery session.
2) Validate what is worth building
Together, we prioritise use cases, assess feasibility and define a practical roadmap. When needed, we build a proof of concept to validate the idea with real data.
3) Build for real use
Once the direction is clear, we design and implement the solution for production use — including integrations, deployment, governance and continuous development.
These are examples of ways how we usually start working with clients.
Feel free to tell how you would like to start!
Feel free to tell how you would like to start!
Let’s look at your system together
Whether you need architecture support, embedded and industrial software expertise, better integration between systems, more scalable use of data, or a practical path from platform work to applied AI, Wapice can help.
Tell us where the friction is: platform architecture, software quality, integration, data, AI, or lifecycle continuity.
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