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.
Reducing false alarms and operator fatigue
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.
Detecting faulty hardware and anomalous cardholder behavior
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.
