“Can you detect this specific object or condition?”
GSTREAM
Custom detection, classification or segmentation models for customer-specific visual requirements.
VIDEO AI // INTEGRATOR PARTNERS
Custom Video AI for Security Integrators.
When your customer's requirement goes beyond standard camera or VMS analytics, Gstream builds the custom AI layer.
Custom detection, event logic, video understanding and edge/GPU inference - engineered around your existing camera, VMS and security infrastructure.
You keep the customer relationship. Gstream provides the AI engineering.
- CUSTOM DETECTION
- TEMPORAL EVENTS
- VIDEO AI
- EDGE INFERENCE
- VLM
- RTSP
- ON-PREMISE
01 // THE GAP
When Standard Video Analytics Isn't Enough
Modern cameras and VMS platforms handle many common analytics well. The problem starts when a customer asks for something specific to their operation, environment or workflow.
Standard analyticsCustom requirementGstream
“Can you alert only when this sequence of events happens?”
GSTREAM
Tracking, state and temporal event logic that goes beyond simple line-crossing or zone rules.
“Can the system understand what happened in this video?”
GSTREAM
Computer vision plus multimodal/VLM reasoning for richer event validation and video understanding.
“Can this run across 10, 20 or 50 existing cameras?”
GSTREAM
RTSP ingestion, hardware-accelerated decoding, GPU/edge inference and production-grade multi-camera pipelines.
02 // AI LAYER
Built Around Your Existing Security Stack
We do not require customers to replace their complete camera infrastructure. Gstream engineering is designed to integrate into existing systems wherever technically practical.
EXISTING IP CAMERASInstalled base, unchanged
RTSP / ONVIF / EXISTING VMSTransport and stream access
GSTREAM AI LAYER
DETECTION
TRACKING
EVENT LOGIC
VLM / VALIDATIONSecondary reasoning on candidate events
ALERTS / REST API / WEBHOOKS / VMS INTEGRATIONDelivered into the systems your operators already use
DEPLOYMENT TARGETS
EDGE DEVICE
NVIDIA GPU
ON-PREMISE SERVER
CLOUD
RTSPONVIFRESTWEBHOOKSPYTORCHTENSORRTCUDADEEPSTREAMDOCKERJETSONNVIDIA GPUFASTAPI
03 // CUSTOM ANALYTICS
The Requirements That Usually Need Custom Engineering
Feasibility is always subject to image quality, camera position and data availability. We assess each requirement before committing to a build.
Custom object detection
Detect customer-specific objects that are not part of generic pretrained classes.
Complex intrusion logic
Combine zones, direction, duration, tracking and context.
Left / removed object events
Track object state over time rather than relying on a single frame.
PPE and process compliance
Detect operational states, interactions or process violations where technically appropriate.
Vehicle and yard intelligence
Vehicles, trailers, loading zones, dwell times and movement events.
Multi-camera tracking
Associate activity across multiple camera streams where camera geometry allows.
Visual anomaly detection
Identify conditions that differ from expected appearance or process state.
Video event validation
Use secondary AI/VLM reasoning to reduce unnecessary alerts.
Thermal + RGB analytics
Fuse thermal measurements and visible imagery for specialist monitoring applications.
OCR / ALPR workflows
Recognition and downstream business logic where standard systems are insufficient.
04 // PARTNER MODEL
Your Customer. Your Project. Our AI Engineering.
Gstream can work behind the integrator rather than competing for the end customer.
White-label available- 01
YOU OWN THE CUSTOMER
You remain the commercial and operational relationship.
- 02
SEND THE REQUIREMENT
Share the use case and representative footage or data.
- 03
GSTREAM VALIDATES IT
We assess feasibility, architecture, data requirements and likely constraints.
- 04
WE BUILD THE AI LAYER
Models, inference, tracking, business logic, APIs and deployment.
- 05
YOU DELIVER THE SOLUTION
White-label or engineering-partner engagement depending on the project.
05 // HOW WE ENGAGE
Start Small. Prove It. Then Deploy.
Partner projects typically include customer-specific validation, integration and deployment requirements.
01CUSTOMER FEASIBILITY SPRINT
Determine whether the customer's requirement is technically viable before committing to a full build.
INPUTS
- Customer requirement
- Sample video / images
- Camera and environment information
- Expected trigger and output
OUTPUTS
- Feasibility assessment
- Prototype where appropriate
- Architecture proposal
- Constraints and risks
- Production estimate
Typical scope: EUR 2,000–5,000.
02CUSTOM VIDEO AI IMPLEMENTATION
Build the production AI capability.
INCLUDES WHERE REQUIRED
- Model development or adaptation
- Inference service
- Tracking and event logic
- APIs
- Deployment packaging
- Monitoring hooks
- Integration support
SCOPE
- Scoped per requirement
- Camera count and site conditions drive effort
Typical production engagements: EUR 10,000+.
03ONGOING ENGINEERING
Maintain and improve deployed systems.
EXAMPLES
- Model updates
- Additional camera sites
- Performance optimisation
- Alert tuning
- Infrastructure support
- New analytics
COMMERCIAL MODEL
- Retainer
- Project
- Engineering support
Agreed per deployment and support level.
06 // ENGINEERING
Not Another Camera Analytics Product
Custom rather than fixed analytics
Built around the customer's actual requirement.
Production-first engineering
Inference, observability, deployment and maintainability are part of the system.
Edge and GPU expertise
Optimise workloads for constrained devices and multi-stream GPU systems.
Full pipeline capability
Video ingestion, inference, tracking, event engine, API and operational output.
Vendor-neutral approach
Build around the appropriate camera, compute and software environment.
Clear handover
Readable architecture, Dockerised services, APIs and documentation where required.
07 // EXPERIENCE
Production Computer Vision, Not Demo-Only AI
Challenge
Visual QA and human review inside a production workflow.
Engineering
Computer vision, production pipeline and human-in-the-loop confidence logic.
Challenge
Continuous camera and video processing across multiple streams.
Engineering
RTSP ingestion, GPU inference, tracking and event logic, alert and API integration.
Challenge
Vision workloads on constrained or on-premise hardware.
Engineering
Model optimisation and TensorRT / CUDA / Jetson / NVIDIA GPU deployment where appropriate.
Challenge
Visual tasks that require richer semantic understanding.
Engineering
Conventional computer vision combined with multimodal/VLM components where appropriate.
08 // PARTNERS
Designed for Companies That Already Own the Customer Relationship
If you already provide cameras, security infrastructure or monitoring systems and occasionally encounter a requirement your standard analytics cannot satisfy, that is where Gstream fits.
- Security Integrators
- CCTV / Video Integrators
- VMS Integrators
- Access-Control Integrators
- Smart-Camera Vendors
- Industrial / Infrastructure Monitoring Companies
09 // START HERE
Have a Customer Requirement Your Current Stack Can't Handle?
Send a short description and, where possible, representative footage. We can quickly establish whether the requirement is worth pursuing technically.
Discuss the requirement