Reken’s platform, which it calls the Reken Private Core, is a system of small, proprietary AI models that run directly on a user’s device rather than routing communications to the cloud. While some competitors, such as cybersecurity startups Abnormal and Doppel, use AI to analyze communications, most do that by transmitting data to cloud-based services.
Sending data to the cloud introduces further risks of data breaches as well as possible time lags that can frustrate users, Ghosemajumder said. Some of these cybersecurity companies are also using AI models from providers such as OpenAI, Anthropic, and Google DeepMind, which also introduces additional costs. Google and Apple are both reported to be working on AI-powered phishing detection software that would function on device, but neither has rolled out a product yet.
Ghosemajumder said the central R&D challenge was proving that Reken’s AI models could produce high-quality results on ordinary hardware—standard corporate laptops without GPUs—fast enough to block threats in real time.
“You could take an LLM and figure out a way to quantize it so that you could run it with fewer resources and run it on a machine that didn’t have GPUs, but if it still runs at the speed of a full LLM, then it’s not going to be able to produce a result in a timeframe that matters,” Ghosemajumder told Fortune. “But what we’re able to do is both.”
