Over the past decade, the role of video-based security systems has fundamentally changed. Cameras are no longer mere tools for recording incidents; they have become a primary data source for operations, safety, and decision-making across a wide range of industries.
This shift comes with significant consequences. As the number of cameras grows and video resolutions increase, organizations are now required to manage volumes of video data far greater than ever before.
In many cases, the analytics systems in use have not evolved at the same pace as real-world operational demands. The result is a growing number of alarms, slower investigations, and increasing workloads for operators. Against this backdrop, Hikvision introduced Guanlan AI, positioned not as an additional feature, but as the new intelligence core of its AIoT portfolio.
New Challenges in a Data-Driven Operational Era
The explosion of video data is no longer just a storage issue. In industrial zones, public facilities, and critical infrastructure, security teams are required to filter through thousands of notifications every day, many of which turn out to be irrelevant.
Conventional analytics systems often struggle to distinguish real threats from environmental noise such as lighting changes, weather conditions, or non-critical movement. At the same time, when a real incident does occur, video retrieval is still largely manual and time-consuming.
Why Conventional AI Approaches Are No Longer Sufficient
Most legacy AI systems were designed for specific tasks and operated in isolation. This approach was effective when system scale was limited. However, in modern AIoT environments, where video, text, and other data types are interconnected—such models are increasingly showing their limitations.
Common challenges observed across industries include:
- A surge in false alarms that burden operators
- Video investigations that take hours to complete
- Inability to recognize new objects or behaviors
- Increasing network and cloud resource consumption
At scale, these challenges go beyond technical inconvenience. They directly affect operational costs, security response times, and overall trust in AI surveillance systems.
What Is Guanlan AI and How Does It Address Video Analytics Challenges?
Source: hikvision.com
Guanlan AI is a suite of large-scale AI models developed by Hikvision to serve as a unified intelligence foundation across AIoT, AI surveillance, and video analytics ecosystems. Rather than focusing on a single function or device, Guanlan acts as a consistent intelligence layer, powering cameras, NVRs, and video management systems within a shared understanding framework.
This approach represents a fundamental shift away from fragmented traditional video analytics. In conventional systems, each camera or application often relies on separate AI models that must be retrained for different scenarios. As a result, accuracy becomes difficult to maintain, integration grows complex, and operational costs rise as systems scale.
Guanlan AI addresses these limitations through a three-tier architecture designed for scalability, adaptability, and real-world operational context.
How Guanlan AI Works: A Three-Layer Architecture
The core strength of Guanlan AI lies in its three-layer architecture, built to deliver both flexibility and high accuracy:
1. Foundation Model
A large-scale base model that understands complex visual patterns, object relationships, and environmental context at a holistic level.
2. Industry Model
Models optimized for specific industry needs, such as security, traffic, or manufacturing, ensuring analytics remain relevant to real-world operational scenarios.
3. Task Model
An execution layer designed for specific tasks such as perimeter protection, intrusion detection, or behavioral analysis.
Guanlan AI: From Architecture to Real-World Implementation
Source: hikvision.com
This layered approach shows that Guanlan AI goes beyond a conceptual framework. A consistent architecture allows the same intelligence to operate seamlessly across devices—from edge AI cameras to NVRs and video management systems—without losing context or accuracy.
Built on this foundation, Guanlan AI moves from concept to real-world deployment, embedded directly into products to address everyday operational challenges. Its implementation can be seen through the following solutions:
DeepinViewX Cameras Powered by Guanlan AI
As a direct implementation of Guanlan AI’s large vision models at the edge, DeepinViewX cameras deliver a significant leap in AI surveillance and video analytics performance.
With contextual intelligence rather than object-only detection, these cameras offer:
- Up to 90 percent reduction in false alarms, even in complex environments
- Twice the VCA detection range compared to previous generations
- Stable human and vehicle detection in low-light and high-density areas
Because reliability is critical, DeepinViewX cameras are widely deployed for perimeter protection, industrial zones, campuses, and critical infrastructure, environments where detection failure is not an option.
AcuSeek NVR: Natural Language Search for Faster Investigations
If DeepinViewX enhances how systems see, AcuSeek NVR transforms how security teams search and analyze video.
Powered by Guanlan’s multimodal AI, AcuSeek enables natural-language video search. Operators no longer need to manually scrub timelines; instead, they can type queries such as:
“a man wearing a red jacket in the parking area in the afternoon”
The system retrieves relevant footage within minutes—reducing investigations that took hours. For SOCs, security teams, and large-scale operations, this capability represents a fundamental shift in how decisions are made.
Operational and Business Implications of Guanlan AI
The impact of Guanlan AI goes beyond technical improvements. With more accurate alarms and faster investigations, organizations can:
- Reduce operator fatigue
- Accelerate incident response
- Lower long-term operational costs
- Improve overall system efficiency
From an investment perspective, this approach helps organizations balance security requirements with cost control and scalability.
Use Cases Across Industries
Source: hikvision.com
Unified AI approaches like Guanlan AI are relevant across industries facing similar challenges: high data volumes and the need for rapid response, without increasing system complexity.
- Factories & industrial parks: high-precision perimeter protection
- Smart cities: enhanced situational awareness
- Retail & logistics: rapid video retrieval for loss prevention
- Critical infrastructure: stable performance in complex environments
- Campuses & education: visitor and vehicle monitoring
Looking Ahead: Guanlan AI and the Future of AIoT
By positioning AI as a core layer rather than a feature, Hikvision places Guanlan AI at the center of its long-term AIoT strategy. This aligns with global industry trends, where AI increasingly serves as the connective tissue between devices, data, and decisions.
Rather than adding complexity, Guanlan AI aims to simplify how organizations understand and act on video data.
Check Other Hikvision’s Products
Build a Strong AIoT Foundation with Virtus Technology Indonesia
As part of CTI Group, Virtus Technology Indonesia (VTI) delivers Hikvision Guanlan AI through a consultative approach, covering planning, system integration, and optimization tailored to business needs.
For organizations preparing to enter the AI camera and AIoT era with a solid foundation, Guanlan AI offers more than video analytics. It delivers intelligence designed to reduce false alarms, accelerate investigations, and improve operational efficiency in measurable ways.
Discuss your security and AIoT requirements with the Virtus team today and discover how Guanlan AI can be effectively deployed in your business environment. Contact us now.