MENLO PARK, Calif., Nov. 23, 2021 — Hakimo, a venture-backed company dedicated to modernizing physical security, has announced the release of its smart monitoring software powered by artificial intelligence (AI) to holistically manage enterprise physical security operations.
Hakimo’s software significantly streamlines the workflow of a global security operations center (GSOC) by freeing up time for operators and by surfacing security threats which would have gone unnoticed previously.
“Hakimo leverages state-of-the-art deep learning technology developed over the last few years,” said Sam Joseph, co-founder and chief executive officer of Hakimo. “What Hakimo is doing today was literally impossible to achieve just a decade ago. Hakimo-like tools have been the norm in the cybersecurity industry, and Hakimo is pioneering the convergence between cybersecurity and physical security by bringing them to physical security.”
Tailgating is a serious concern for every security organization because the damage that a malicious person can do within a secure facility has no bounds. Hakimo’s software detects tailgating using existing cameras without needing any additional hardware to be deployed.
Not only that, Hakimo has an industry-leading performance rate that even beats out other tailgating solutions that rely on specialized hardware, such as sensors. Tests show that corporate security systems infused with Hakimo’s software reported a 99 percent precision rate on hundreds of thousands of events analyzed by the system, making it the best-performing tailgating detection system in the industry.
Hakimo actually goes a step further and follows a holistic approach in solving tailgating. In addition to just detecting tailgating, Hakimo provides gamification tools and automated email alerts to bring about behavior change in employees.
All GSOCs suffer from false alarms and the ensuing alarm fatigue because of the sheer impractical volume of alarms that must be managed. What’s even worse is the fact that GSOCs routinely miss real security breaches which destroys the entire purpose of having a 24x7 security operations center and puts the security team in a bad light.
Hakimo uses video analytics to auto-resolve false alarms and consistently reduces nuisance alarms by 75 to 85 percent. This gives time back to the GSOC operators to focus on real issues that require true human attention, such as real security incidents, emergency response, and travel risk management. Alternatively, the same GSOC can now handle five times the volume of alarms with the same amount of resources.
Hakimo’s data analytics algorithms also analyze alarms across time and diagnose faulty hardware such as door sensors and sensors. Pointing out anomalies in cardholder behavior is another useful tool in Hakimo’s toolkit. It can point out impossible travel (the same card being used at multiple locations within a short duration which is physically impossible), unusual time or location of usage, and so on.
Hakimo was founded by AI researchers at Stanford University and raised a $4 million seed round from several top Silicon Valley investors. The round was led by Neotribe Ventures and saw participation from defy.vc, Firebolt Ventures, and prominent angels such as Ameet Patel, Prasanna Srikhanta, and Stanford professor Sachin Katti. Hakimo’s solution is currently deployed at several leading enterprises across the country.
The collaboration further expands the capabilities of unified LenelS2 security systems and helps address false alarm and tailgating challenges.
Opportunities abound for making sense of access control data to enhance security and efficiencies. Co-Founder and CEO Sam Joseph highlights how.
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