What is Agentic AI? How does it differ from other AI types? What’s in it for video analytics? Here’s everything you need to know.
We have entered a whole new era, the era of Agentic AI. It’s a breakthrough class of AI that’s not just faster or smarter, but fundamentally more capable than anything we’ve seen before, and it’s having an unprecedented impact on almost every industry and every area of our lives.
What is Agentic AI?
Agentic AI is an artificial intelligence technology designed to act autonomously and solve complex, multi-step problems through sophisticated reasoning and iterative planning. It can perceive, evaluate, act, and learn from its interactions. Agentic AI understands your goals, makes decisions in real time, and carries out tasks, often entire projects, with minimal human input.
With this rich technical backbone, these AI agents are adaptable to real-world complexity where environments shift, exceptions arise, and rigid systems fall short. They thrive in dynamic, unstructured, multifaceted situations where human intuition and judgment were once indispensable (such as video; more on that below).
Agentic AI vs. Generative AI: What’s the Difference?
Though both are foundational to modern AI progress, agentic AI and generative AI serve distinct purposes.
- Generative AI is about creating text, images, videos, code, and more. It’s ideal for brainstorming, storytelling, and content production.
- Agentic AI is about doing, planning, reasoning, decision-making, and execution. It’s focused on goals, action, and adaptability.
As President and CEO of NVIDIA, Jensen Huang, noted during his GTC Keynote: “Generative AI fundamentally changed how computing is done; from a retrieving computing model, we now have a generative computing model. Rather than retrieving data, it now generates answers. Every single layer of computing has been transformed.
“Agentic AI basically means that you have an AI that has agency. It can perceive and understand the context of the circumstance. It can reason. Very importantly, it can reason about how to answer or how to solve a problem and it can plan an action.”
(You can watch the full keynote address here).
Generative AI and Agentic AI complement each other beautifully. For example, Agentic AI can analyze hours of video input to identify the how’s and why’s of a situation while Generative AI can create a comprehensive report on it.
Why Agentic AI is Revolutionary
Agentic AI represents a whole new mode of operation that fundamentally changes how organizations work. Here’s what makes it so transformative:
- Doing things faster:
Forget manually combing through hundreds of analytics. Agentic AI handles the heavy lifting, executing tasks and surfacing insights at a speed far beyond human capacity. - Doing the previously impossible:
Correlations, patterns, and anomalies that were once buried in the noise are now discoverable. Agentic AI connects the dots in ways that are often not feasible for human operators working alone. - Smarter automation:
These systems don’t just follow rules; they reason. They adapt to change, navigate uncertainty, and manage complex, multi-step workflows. - Better human-AI collaboration:
Agentic AI empowers people by taking on repetitive and intricate tasks, freeing up teams’ time. With natural language interaction, it’s also intuitive to use. - Increased scale:
Beyond speed, agentic systems expand what can be handled at once, enabling parallel execution across large numbers of workflows that previously couldn’t be managed simultaneously.
Video Intelligence: The Breakthrough Use Case for Agentic AI
Nowhere is agentic AI’s potential more profound than in video intelligence (well, we might be slightly biased on this one.)
The world is awash in video. Surveillance cameras data centers, ports, highways, power utilities, and other critical infrastructures generate petabytes of footage. Yet 99% of this video goes unreviewed. It’s like sitting on an oil field without the machinery to extract it. So much value, completely untapped.
Within this vast reservoir are critical insights: safety risks, operational inefficiencies, behavioral patterns, anomalies, and emerging opportunities. But they stay buried simply because human teams don’t have the time or the bandwidth to watch, analyze, and act on such enormous volumes of unstructured content. Humans need hyper-doer tools, and current video analytics software doesn’t cut it.
In the world of video, we’re used to hearing about better cameras, new technologies, etc. that replace the existing hardware. We are also used to hearing about ‘improved’ analytics capabilities. But this latest shift, driven by AI agents, is something else entirely. It’s a leap from a different tech domain and when applied to video analytics, its implications are seismic.
Here’s why. AI agents are intelligent collaborators that understand context and take action. They are the hyper-doers video professionals need: they analyze thousands of hours of footage in real-time and offline, undertake detailed analyses, find correlations, summarize them, generate reports on them and more. In short, they are turning video into an active operational assistant.
The Proprietary cyNeuron and Its Army of AI Agents
cyNeuron is cynapse.ai’s proprietary technology that enables a fundamentally new approach to understanding video. Even prior to the integration of AI agents, the cynapse platform offered significant technological capability, rooted in its underlying architecture: domain-specific large language models (LLMs), computer vision, vision-language models (VLMs), vision AI, graph databases, and retrieval-augmented generation (RAG), each contributing to a deeper and more structured interpretation of video content.
Now, with the addition of AI agents called to action through the cynapse copilot, the platform extends beyond understanding into action. Users are now able to operationalize insights directly, translating video intelligence into execution. This enables advanced automation, highly enhanced search capabilities, and substantially improved efficiency. In effect, it delivers greater video intelligence across the organization, at significantly increased speed.
With Agentic AI, operators can search for nuanced, multi-step scenarios in their own words. For example, an operator might ask:
“I’m looking for a delivery truck reversing into a loading zone during restricted hours while workers are present and no safety cones are deployed.”
Or,
The ability to ask such complex, context-rich questions and receive immediate, precise responses is where cyNeuron’s Discovery AI Agent delivers significant value. It eliminates the need for prolonged search processes and reduces inefficiencies in time and resource allocation. Depending on operational requirements, it can correlate temporal data, behavioral patterns, identity, and historical incidents.
That’s not just AI video surveillance. That’s situational awareness.
CyNeuron’s AI agents:
- Allow teams to come up with their own user-defined ad-hoc events, on the fly, using natural language, with no need to rely on preset rules or wait for the vendor to update configurations.
- Generate reports, summaries, and other business deliverables instantly.
- Undertake automated non-deterministic workflows such as investigations, analysis of trends, etc.
- Deliver insights that go beyond the security use case: safety, compliance, operational efficiency and more.
With the cynapse Agentic AI video intelligence solution, it’s a new era of seeing and analyzing. It’s a whole new level of video understanding.
