We deploy CV systems on edge devices (NVIDIA Jetson, Coral TPU, Intel Movidius, Raspberry Pi), cloud infrastructure (AWS, Azure, GCP), or hybrid architectures depending on your latency, privacy, and connectivity requirements. Edge deployment is ideal for real-time monitoring with minimal latency, offline operation, and data privacy. Cloud deployment works well for batch processing, centralized analytics, and systems that don’t need sub-second response times.

Development timeline depends on problem complexity, data availability, integration requirements, and your internal review processes. Our technical assessment provides a detailed project roadmap with realistic milestones specific to your requirements.

Off-the-shelf tools (cloud APIs, SaaS platforms) work well for common use cases with standard datasets—think facial recognition, general object detection, or basic OCR. Custom development is necessary when: your use case is specialized (detecting specific defects, rare objects, industry-specific scenarios), you need to operate in challenging conditions (poor lighting, extreme angles, unusual environments), you have strict latency or privacy requirements, or existing tools don’t achieve the accuracy your business demands. We assess both options during our technical evaluation and recommend the most cost-effective path.

We implement active monitoring to track model performance, detect accuracy drift, and flag when retraining is needed. Every deployed system includes performance dashboards, automated alerts for degraded accuracy, data collection pipelines to capture edge cases, and regular model health reviews. When conditions change—new products, lighting upgrades, camera repositioning—we provide model updates and retraining services to maintain accuracy.

Project cost depends on scope, technical complexity, data requirements, integration needs, and deployment infrastructure. Our technical assessment provides a fixed-price proposal tailored to your specific use case. We work with organizations of all sizes, from targeted pilot projects to enterprise-scale deployments.

Yes. We offer managed support agreements that include: system monitoring and alerts, regular model performance reviews, retraining and updates as needed, integration support for new cameras or data sources, security patches and infrastructure updates, and technical support with guaranteed response times. Support packages are tailored to your uptime and accuracy requirements.

Absolutely. We specialize in integrating CV systems into existing infrastructure. We work with standard protocols (RTSP, MQTT, WebRTC, REST APIs), connect to most IP cameras and video management systems, integrate with databases (SQL, NoSQL, data warehouses), push results to your business systems (ERP, CRM, SCADA), and deploy on your preferred infrastructure (cloud, on-premise, edge). Integration planning is part of every technical assessment.

We implement security at every layer: data encryption in transit (TLS) and at rest (AES-256), role-based access controls and audit logging, compliance with GDPR, HIPAA, or industry-specific regulations as needed, option to deploy entirely on-premise or in your private cloud (no data leaves your infrastructure), and regular security audits and penetration testing. For sensitive applications, we can train models using federated learning or differential privacy techniques.

We establish clear accuracy benchmarks during the assessment phase and validate them with POC testing before full development. Our contracts include performance guarantees tied to agreed accuracy metrics. If deployed systems don’t meet targets, we provide additional model tuning, data collection, and retraining at no extra cost until benchmarks are achieved. This is why we emphasize rigorous POC validation—we don’t move to production until accuracy is proven.