Physical security has traditionally been a people-intensive function. Surveillance cameras, access control systems, alarm networks, and security personnel have operated together for decades, but the workflow has remained largely unchanged. Cameras capture footage, alerts are generated, and human operators decide whether an event requires action. The infrastructure has evolved over time, but the decision-making layer has remained predominantly manual.
The latest $12 million growth funding secured by Hakimo is notable because it reflects investor confidence in a different layer of the security ecosystem. Rather than building new surveillance hardware, the company is developing software that operates on top of existing infrastructure using artificial intelligence. The round, led by Zigg Capital, brings Hakimo’s total funding to $32 million. Over the past year, the company has also reported tripled revenue, expanded to more than 300 customers, and doubled its workforce.
What stands out is not the funding announcement itself, but the category in which the company operates.
Physical AI is emerging as a segment where artificial intelligence is applied to real-world environments rather than digital workflows. Instead of generating text, images, or code, these systems interpret camera feeds, detect anomalies, identify security incidents, and assist operators in responding more quickly. The objective is not to replace surveillance infrastructure. It is to increase the operational value of infrastructure that already exists.
This represents a broader pattern visible across enterprise AI adoption. Much of the current AI investment is not directed towards replacing complete systems. It is being directed towards reducing repetitive operational work. Security monitoring is one such example. Large facilities generate thousands of hours of video every day, while only a small fraction requires human attention. Artificial intelligence is increasingly being introduced to identify those exceptions before they reach an operator.
The economics of this shift are also changing. Labour shortages, increasing security costs, and the growing volume of surveillance footage are creating operational pressure across commercial real estate, manufacturing facilities, logistics parks, healthcare institutions, and retail environments. AI is increasingly being positioned as a way to manage this growing volume without proportionally increasing human monitoring capacity.
Another observation is where companies like Hakimo are positioning themselves. Rather than asking enterprises to replace cameras or install entirely new systems, the technology integrates with existing hardware. This reduces the operational barrier to adoption. Organisations can modernise their monitoring capabilities without redesigning their physical security infrastructure. The innovation lies in the intelligence layer, not necessarily in the devices themselves.
The company’s recent expansion into capabilities such as AI-powered forensic search also reflects a broader industry direction. Security operations are gradually moving beyond live monitoring towards faster investigation and incident analysis. Video archives, which previously required manual review, are becoming searchable through natural language and AI-assisted analysis. This changes how organisations interact with recorded security data after an event occurs.
At the same time, this transition introduces new operational considerations. Physical security differs from many enterprise software categories because decisions can have immediate real-world consequences. False positives, missed incidents, and delayed responses directly affect people, assets, and business continuity. As a result, AI systems in this category are likely to evolve alongside human oversight rather than replacing it completely. The role of operators shifts from continuous observation to verification and intervention.
From a market perspective, the funding also reflects growing investor interest in vertical AI companies. Instead of building general-purpose AI platforms, many startups are focusing on industries with repetitive, high-volume workflows where artificial intelligence can improve speed and consistency. Security monitoring is becoming one of those categories.
Hypetrics Intelligence Note
- Physical AI is expanding from digital automation into real-world operational environments.
- Enterprise AI adoption is increasingly focused on improving existing workflows rather than replacing infrastructure.
- Security monitoring is shifting from continuous human observation to AI-assisted exception management.
- Existing surveillance infrastructure is becoming more valuable through software rather than new hardware investments.
- Vertical AI companies continue to attract investment by solving operational bottlenecks within specific industries.
- Human oversight is likely to remain a core component of physical AI deployment, particularly in security-critical environments.
The significance of Hakimo’s funding extends beyond one company’s growth. It points to a broader shift in enterprise technology, where artificial intelligence is increasingly being embedded into operational systems that organisations already use, rather than asking them to rebuild those systems from the ground up.