‘If you build it, they will come’- Ray Kinsella, Field of Dreams, 1989
An open video system is a standards-based platform that connects any IP camera or sensor, centralizes video management, and makes footage available to the applications and people who need it. Unlike closed, proprietary tools, an open video systemturns video into a shareable data asset—fueling real-time security, AI video analysis, and day-to-day decision-making.
This article unpacks the business case for open video systems, the core benefits they deliver, the technical checkpoints to consider, and practical steps for evaluating and implementing an open platform.
The business case for open video systems
The promise of “seeing everything everywhere” pushed many organizations to buy the highest-resolution cameras they could afford. Years later, most teams are trapped in a patchwork of incompatible video management systems and face two expensive problems:
- Managing dozens, sometimes hundreds, of proprietary devices that each stream video to their own silo.
- Finding new opportunities hidden inside all that video data—without manually downloading clips or paying add-on licensing fees.
An open video system eliminates those walls by welcoming any ONVIF-compliant camera, access-control reader, or environmental sensor into one dashboard. The result is unified video intelligence that serves security, operations, and customer-experience initiatives at the same time.
Why open video systems matter now
More than one billion security cameras operate worldwide today, generating petabytes of footage every day. As resolutions rise from HD to 4K and 8K, data volumes—and the need for interoperability—skyrocket.
Standards like ONVIF and RTSP make basic connections possible, but only an open video system fully capitalizes on them by:
- Extending the life of existing hardware—no rip-and-replace upgrade cycles.
- Integrating video with point-of-sale, ERP, and analytics tools through secure APIs.
- Scaling from one site to hundreds without changing core architecture.
Consider a car wash. Traditional surveillance records each lane for incident review, but an open system fuses video with PoS data to reveal how long customers wait, which memberships are most active, and where equipment causes delays. As Glide Xpress discovered, “ We reduced idle time at the pay station from minutes to seconds once we could finally see where the bottleneck was. ” — Maxwell Dwigans, Director of Operations, Glide Xpress.
Key features and technical considerations
When you evaluate an open video system, confirm that it delivers the following capabilities out of the box:
- Camera-agnostic integration: Works with any ONVIF-compliant or RTSP-streaming camera—dome, fisheye, panoramic, or body-worn.
- Flexible data consumption: Exposes secure APIs and webhooks so video can flow into third-party dashboards, CRM tools, and analytics platforms.
- Scalable architecture: Supports unlimited cameras, locations, and users without performance trade-offs—whether deployed on-premises, in the cloud, or at the edge.
- AI-enhanced analytics: Offers built-in or pluggable AI models for real-time alerts, object detection, and searchable video archives.
- Rapid deployment: Allows most organizations to connect cameras and start streaming in under a week, often without specialty IT resources.
Not sure if your current camera systems are compatible? Check device specifications for ONVIF support or run a free utility such as ONVIF Device Manager. If the camera exposes an RTSP stream, it can almost always join an open platform. Legacy analog units may require encoders, and some older IP cameras might need a firmware update before they can authenticate with modern video management software.
Finally, remember the people side. Look for vendors that provide hands-on training, detailed documentation, and ongoing education so your team can master new AI video analysis features and workflows.
Benefits and ROI of open video systems
Organizations that move to an open video system report measurable improvements across security, operations, and the bottom line:
- Lower total cost of ownership: Eliminates per-camera licensing fees and reduces maintenance hours tied to proprietary software.
- Hardware longevity: Extends the useful life of existing cameras by decoupling software innovation from physical devices.
- Organizational agility: Quickly integrates new AI models, access-control panels, or business applications without forklift upgrades.
- Productivity gains: Gives every department—from loss prevention to marketing—immediate, self-service access to relevant video data.
Gartner predicts that by 2026 more than 60 percent of enterprise video surveillance deployments will rely on open or hybrid cloud platforms, up from fewer than 25 percent today.
Limitations and considerations
Before committing to an open video system, weigh these factors:
- Legacy integration: Very old or proprietary cameras without ONVIF/RTSP may need encoders or be replaced.
- Infrastructure investment: High-resolution recording and AI analytics can require additional storage or compute resources.
- Vendor support: Evaluate the provider’s documentation, customer success program, and roadmap to ensure long-term partnership.
- Security posture: Open does not mean insecure—verify that the platform supports encryption, role-based access control, and regular third-party audits.
Building for the future with an open video system
From eliminating vendor lock-in to unlocking new revenue streams, an open video system is a foundational building block for modern video intelligence. By aligning camera systems, AI video analysis, and business workflows under one flexible platform, organizations position themselves for faster decisions, safer environments, and stronger customer experiences.
Ready to see the difference an open approach can make? book a demo with our team and explore how Spot AI can transform your video intelligence strategy.
Frequently asked questions
What is an open video system?
An open video system is a video management platform built on non-proprietary standards—such as ONVIF and RTSP—that allows any compatible camera or sensor to connect, stream, and share data with other business applications.
What are the costs associated with implementing an open video system?
Costs typically include initial setup (edge servers or cloud resources), potential middleware for legacy cameras, storage for higher-resolution video, and staff training. Over time, organizations often offset these expenses through lower licensing fees and extended hardware lifespan.
How do I know if my current video systems can integrate with an open system?
Check the camera’s specification sheet for ONVIF or RTSP support, verify firmware versions, and test connectivity with tools like ONVIF Device Manager. Cameras lacking these standards may require an encoder or replacement.
What are the future trends in video management systems?
Key trends include AI-driven analytics, hybrid edge-to-cloud architectures, higher-resolution imaging, and deeper integration with business applications through open APIs.
How can I train my staff to use a new open video management system?
Combine vendor-led onboarding sessions with role-specific workshops and micro-learning videos. Continuous, hands-on practice helps teams adopt new workflows and extract maximum value from the system.
How does an open video system support AI video analysis?
The platform either embeds machine-learning models or allows you to plug in third-party AI tools, enabling real-time object detection, anomaly alerts, and searchable video archives.
What is the difference between open and proprietary video management systems?
Opensystems use industry standards to integrate with any compliant camera or application, while proprietary systems restrict you to a single vendor’s hardware, software, and upgrade cycles.
What are the primary benefits for businesses adopting open video systems?
Primary benefits include reduced total cost of ownership, hardware longevity, greater flexibility to add new technologies, and the ability to turn video data into actionable insights across the organization.
About the author: Rish Gupta is CEO and Co-founder of Spot AI, leading the charge in business strategy and the future of video intelligence. With extensive experience in AI-powered security and digital transformation, Rish helps organizations unlock the full potential of their video data.
