Deployment & Architecture

On-premises, the analytics server sits on the camera network and pulls each stream directly. In the cloud, the server usually can't reach into the private camera network, so an on-site agent pushes the streams up instead, often at a lower frame rate and resolution to fit the available bandwidth.

SaaS data stays in the selected Azure region, and on-premises/BYOC deployments give customers full control over data location.

• United States
• Canada
• UK South
• Customer-chosen regions

Yes, many VAM systems integrate seamlessly with other business tools like CMS (Content Management Systems), LMS (Learning Management Systems), and marketing platforms. This integration helps ensure smooth workflows across departments, enhancing collaboration and content distribution.

Logical tenant isolation at the application, database, and storage levels. Shared SaaS keeps each tenant's data separate despite shared infrastructure. Dedicated SaaS provides single-tenant environments with exclusively allocated infrastructure.

VAM systems provide robust security features like access control, user authentication, and encrypted storage. These features ensure that sensitive video content remains secure while being accessible to the right teams or individuals, reducing the risk of unauthorized access or data breaches.

Up to 8 portals per deployment (EnterpriseTube Premium) with independent branding, users, content, and security policies per portal. This enables separate branded experiences from a single deployment for different departments or audiences.

A VAM system simplifies video distribution by allowing businesses to share video assets easily across teams or externally. Whether you need to distribute training materials, marketing videos, or internal communications, a VAM system ensures efficient sharing with proper security measures in place.

Bring Your Own Cloud lets organizations deploy VIDIZMO on their own cloud environment (Azure, AWS) while VIDIZMO manages the application layer. Customers retain full infrastructure and data control with managed application support.

When choosing a VAM system, consider factors such as ease of use, scalability, integration capabilities with other tools, and security features. Look for a solution that offers centralized storage, metadata tagging, and customizable access control to meet your specific business needs.

On-premises deployment includes multiple specialized server roles for full platform functionality.

• Application server
• Content processing server
• Up to 9 AI server types (transcription, object detection, OCR, PII, vision description, AI search, agentic, embedding, live video analytics)
• Database server
• Message broker
• Streaming server

Windows Server with IIS 10/11, Python 3.9.12 for AI/ML runtime, and SQL Server 2019 or 2022 for database. AI servers require NVIDIA GPUs with high-speed NVMe storage for optimal performance.

Hybrid deployments combine on-premises with cloud services. Keep sensitive data on-premises while leveraging cloud for scalability, collaboration, and global access. Workloads allocate based on data sensitivity requirements.

Hot, cold, and archive storage tiers enable cost-optimized data lifecycle management. Frequently accessed content stays on hot storage while older content moves to cold or archive tiers with automated lifecycle policies.

Shared is multi-tenant, lower cost, provisions in 30 seconds. Dedicated is single-tenant with exclusive infrastructure, custom security tuning, and approximately 4-hour provisioning. Choose dedicated for compliance-heavy or performance-critical deployments.

Azure Site Recovery with geo-redundant storage (3+3 copies across regions) and Azure Traffic Manager for automatic failover. RTO is 2 hours for database, 48 hours for infrastructure. RPO is 24 hours. DR testing is semi-annual. Security.

AI Live Server handles 32 camera streams per instance, live streaming supports 20,000 simultaneous participants, bulk processing is tested with 1.1M+ recordings, and multi-portal supports 8 portals per deployment with auto-scaling.

AWS GovCloud is fully supported for government workloads requiring U.S.-jurisdiction data processing and storage. VIDIZMO supports both AWS and Azure Government Cloud deployment paths for federal customers.

Multiple IaC tools are supported, combined with CI/CD pipelines for automated, repeatable deployment across environments.

• Terraform
• Azure Bicep
• ARM Templates
• AWS CloudFormation
• Azure DevOps and GitHub Actions CI/CD pipelines

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VIDIZMO is built on a modern enterprise stack optimized for high-throughput AI processing.

• .NET 9 -- backend application
• Python 3.9.12 -- AI/ML runtime
• SQL Server 2019/2022 -- database
• IIS 10/11 -- web server
• Wowza -- streaming
• NVIDIA NVENC -- GPU acceleration
• ElasticSearch -- search engine
• Kafka/RabbitMQ/Azure Service Bus -- messaging
• Docker/Kubernetes -- containerization

VIDIZMO supports multiple streaming protocols with CDN delivery via Azure CDN for live and Akamai/EdgeCast for VOD.

• HLS -- primary protocol
• RTMP -- ingest and legacy
• MPEG-DASH -- adaptive standard
• Microsoft Smooth Streaming -- legacy via fallback