Akheros offers a critical shift in anticipating machine behavior technologies. Post-hoc profiling is prone to mistakes and self-deception. The industry is currently paying for offers with weak anticipation capabilities. Anticipating behavior is becoming vital for cybersecurity as threats escalate in costs and damages, but the current technological development paradigm is focused on ad-hoc and post-hoc, and spends most of its energy fixing the flaws of old architectures not fit for the current threats.

Akheros is a constant anticipated forensic watchdog, including online forensic and cloud-forensic. It allows a precise identification of the network of components displaying interrelated incongruous behaviors. Our long-term objective is to integrate self-awareness and anticipation within the design of IT architectures.

Being outpaced is the harsh reality of the industry today. Malware detection software producers cannot keep up with the rhythm of production of new threats. They are overloaded with an exponential growth of the malware analysis tasks, which destroys their profitability and creates a systematic delay in signatures production and malicious codes identification.

Akheros is designed by leading cybersecurity experts, who have in mind the data they need to conduct red team interventions. The Akheros learning engine cumulates critical knowledge on variables that accelerate such interventions, and allows for avoiding time and resource losses in initial interventions. This means being faster in interventions, protecting business continuity, and avoiding further spread of damages in the compromised system.