Personal AI

Personal AI, the operating name of Human AI Labs, is a San Francisco company founded in 2020 by Suman Kanuganti, Sharon Zhang, and Kristie Kaiser. Kanuganti, a Forbes 40 Under 40 honoree, previously founded the accessibility company Aira, and chief technology officer Sharon Zhang came from machine learning roles at LinkedIn and research at MIT. Originally a consumer product for building a personal digital memory, the company pivoted to the enterprise, and has raised around sixteen million dollars from investors and partners that include Microsoft, NVIDIA, and Verizon. Its enduring thesis, formed years before the ChatGPT moment, is that the most valuable AI is grounded in your own memory and identity rather than the generic internet.

The core of Personal AI is memory infrastructure. An identity based, multi layered, persistent memory architecture replaces context window personalization and powers custom small language models, built on the company's Generative Grounded Transformer, that are trained on a customer's proprietary knowledge rather than public data. On top of that memory layer, enterprises rapidly train and deploy their own AI personas, or teammates, each a specialized persona with agentic capabilities that draws on an evolving institutional memory. Because the models are small and grounded, Personal AI emphasizes precision, low latency, and cost efficiency, and it is purpose built for distributed, privacy first deployment, including on network delivery across telecommunications infrastructure integrated with voice, text, and data services. Data is user owned and controlled, and the platform is SOC 2 compliant.

Personal AI sits at the intersection of memory infrastructure and an agent building platform, letting organizations stand up an evergreen AI workforce grounded in their own knowledge across business functions. It works with Fortune 500 companies and large telcos. It is a strong fit for enterprises that want AI teammates grounded in proprietary knowledge and persistent memory, with privacy first or distributed deployment. It is a weaker fit for teams that simply want to route a general purpose chatbot, or that need broad prebuilt agent libraries and heavy workflow orchestration out of the box, which are not its focus.