Transforming Video Data into Actionable Business Intelligence
We provide AI-powered people counting and behavioral analytics using advanced computer vision. Our solution converts video streams into measurable insights that help organizations optimize operations, improve customer experience, and drive data-driven decisions—without compromising privacy.
Our Computer Vision Analytics service provides businesses with actionable insights into visitor flow and on-site behavior using advanced video analysis and pattern recognition technology. By transforming visual data into meaningful metrics, organizations can optimize operations, improve customer experience, and make informed, data-driven decisions.
The solution automatically detects and analyzes people movement across physical spaces, capturing accurate traffic data while respecting operational efficiency and scalability requirements.
Accurately measures the number of individuals entering, exiting, and passing by monitored areas.
Tracks movement patterns to understand peak hours, congestion points, and overall traffic trends.
Analyzes dwell time, movement paths, and zone engagement to assess how people interact with spaces.
Optimized deployment at entrances and key areas to ensure reliable data capture and coverage.
Access live dashboards and historical data for performance monitoring and trend analysis.
Suitable for single locations or multi-site environments, adaptable to various industries.
Develop a highly reliable pedestrian traffic counting system
Detect movement direction (entering vs. exiting the store)
Count people who pass near the entrance without entering
Generate heat maps to visualize customer behavior patterns inside the store
Produce detailed reports to support executive decision-making
Improve operational efficiency and sales performance
The client will be advised on physical camera adjustments to ensure accurate counting results.
Compare leading GPU options to choose the right hardware for your analytics workload.
| Feature | NVIDIA Tesla V100 | NVIDIA Tesla T4 |
|---|---|---|
| GPU Type | Data-center / training-grade | Inference-optimized |
| VRAM | 16 GB HBM2 | 16 GB GDDR6 |
| Tensor Cores | 640 | 320 |
| FP32 Performance | ~14 TFLOPS | ~8.1 TFLOPS |
| FP16 Performance | ~112 TFLOPS | ~65 TFLOPS |
| Memory Bandwidth | 900 GB/s | 320 GB/s |
| Power Consumption | 250 W | 70 W |
| Best For | Model training, high-density video inference | Video inference, batch processing |
| Key Strengths | High-speed training, large batch processing | Efficient, cost-effective, low/medium traffic |
Our proven 9-phase development process ensures high-quality, client-ready analytics solutions.
Gather high-quality video data for model training and validation.
Prepare data for model training and ensure quality.
Train a base model to detect and count people.
Validate model performance on client data.
Adapt model to client's real-world conditions.
Maximize processing speed.
Produce actionable insights and reports.
Ensure seamless data flow for business operations.
Ensure long-term reliability and accuracy.
Choose the deployment model that best fits your organization's needs and technical capabilities.
Clients send video files to the service provider, who performs all processing and delivers results without requiring client-side infrastructure.
Clients upload, process, and download results through a web-based interface with real-time progress visibility.
Transform raw video data into intuitive visual representations for data-driven decisions.
Real-time detection overlays showing model understanding.
Display real-time numeric data on video frames.
Understand visitor navigation patterns.
Visualize high-traffic areas.
Analyze trends for operational decisions.
Objective: Ensure continued accuracy of analytics.
Measure success with clearly defined, actionable metrics.
We prioritize data protection and regulatory compliance in all our solutions.
Proactive risk management ensures project success.
| Risk | Mitigation Strategy |
|---|---|
| Poor camera angles or blind spots | Follow installation guidelines; regular audits |
| Lighting variations or glare | Periodic retraining; adjust camera settings |
| High computational load | GPU optimization, batching, scaling |
| Model drift over time | Continuous retraining with new data |
Ready to transform your video data into actionable insights? Here's how to get started.
Contact us today to discuss your computer vision analytics needs and discover how we can help transform your business.
Transform your video data into actionable business intelligence. Our AI-powered analytics help you optimize operations, improve customer experience, and drive data-driven decisions.