Connecting The Dots In Complex Data
We're not just another AI startup! We're your ticket to explainable AI that cleans, connects, and understands your data, helping organizations make decisions grounded in truth, not noise.
See our Work
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A chatbot that doesn’t guess, it reasons. Built on Bayesian Networks, it supports decision-making under uncertainty by updating beliefs step by step as new information is provided. The result is transparent, adaptive reasoning that users can understand and trust.
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RootSquare built a multimodal AI system for the Sophia Foundation for Children to automatically match children’s photos and records. The solution reduced manual work from days to minutes while keeping humans in the loop for verification and trust.
Rootsquare.io’s solution demonstrates unparalleled accuracy in identifying duplicates across diverse datasets. This analysis highlights the potential of our tools to streamline database management and improve data integrity.
Meet the team
- 10+ years in AI for Healthcare
- Deployed AI systems across UCLA Health and UC-wide clinics
- Published work in Bayesian Networks, ML, and LLMs for clinical use
- Data deduplication
- NLP and LLM systems
Frequently Asked Questions
We are often asked...
RootSquare builds AI systems that clean, connect, and explain complex data. Our work focuses on data deduplication, multimodal intelligence, and explainable healthcare AI.
Our systems combine machine learning, multimodal reasoning, and causal models. This allows us to handle missing data, reduce bias, and provide explanations instead of black-box predictions.
Still have questions?
What our clients say
Don't just take our word for it, see what the awesome people we work with have to say.
Demetris D.
Management/Operations Sophia Foundation for Children
Stephanos C.
Data Lead Sophia Foundation for Children
Sophia T.
Event Coordinator