Tolu Andre Olatunbosun is the co-founder of Limitus, an AI startup focused on privacy-first, locally executed automation agents. His work involves developing intelligent systems that integrate Web2 and Web3 functionalities with an emphasis on data privacy.

Overview

Tolu Andre Olatunbosun is a professional with a background in data science and artificial intelligence. He is associated with Los Alamos National Laboratory as a Staff Data Scientist. Concurrently, Olatunbosun is involved with Limitus Intel, an initiative focused on developing AI agents that prioritize user data privacy through local execution. His work in this area includes co-authoring a white paper on privacy-layered Web3 agents, exploring the architecture for locally executed, speech-cognitive automation systems. This work aims to provide users with advanced automation capabilities without requiring them to transfer sensitive data to centralized cloud services. His academic background includes a Master's degree in Data Science from Rochester Institute of Technology (RIT).

Education

Olatunbosun is a graduate of Rochester Institute of Technology (RIT), where he completed a Master's degree in Data Science. ^[3]

Career

Tolu Andre Olatunbosun is a co-founder of Limitus Intel and serves as a Staff Data Scientist at Los Alamos National Laboratory (LANL) in the United States. His professional background includes roles in data science, blockchain, artificial intelligence, and cybersecurity, spanning academic institutions, public organizations, and private companies.

At Los Alamos National Laboratory, Olatunbosun initially joined in 2023 as a Data Scientist under the Post-Master's program. His work focused on developing machine learning models for image processing of transuranic waste drums, performing statistical data analysis, and implementing data mining techniques for the evaluation of nuclear waste materials. Since 2024, he has held the position of Staff Data Scientist and AI Operations Developer, where his responsibilities include maintaining vector databases, developing AI workflows, and supporting Large Language Model (LLM) operations in high-performance computing environments.

Olatunbosun is also a co-founder of Limitus, an AI startup focused on developing privacy-centric, locally executed automation agents. The project is designed to enable the integration of Web2 and Web3 workflows through voice-controlled AI systems that operate entirely on local devices. Its architecture emphasizes on-device data processing without reliance on centralized servers. The technical framework behind Limitus is outlined in the whitepaper “Privacy-Layered Web3 Agents: Architecting Locally Executed, Speech Cognitive Automation for Multi-Domain Intelligent Systems”, co-authored by Olatunbosun and Sai Tarun Sathyan.

His previous experience includes working as a Data Scientist at Bayer Crop Science, where he contributed to demand forecasting models and developed data visualizations for agricultural logistics operations in North America. He also served as a Data Science Analyst at the New York State Senate, focusing on political data analysis and micro-targeting strategies.

Additionally, Olatunbosun has held research assistant roles at the RIT ESL Global Cybersecurity Institute, conducting assessments of denial-of-service (DoS) attack patterns, and at NYU Langone Health, where he worked on financial dashboards and data process optimization. His career further includes data analysis positions at organizations such as The Nightingale-Bamford School and Equinox Technology Partners, as well as research projects at the University of Rochester focused on emotion recognition using deep learning, and at SUNY Geneseo, where he contributed to research on genetic markers associated with Alzheimer’s disease.

His areas of expertise encompass machine learning, cybersecurity, LLM operations, data engineering, and AI systems integration in both secure and high-compliance environments. ^{[1] [2] [3]}