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Citrusˣ Raises $4.5 million Seed for AI Explainability Collaboration Platform

Updated: Dec 17, 2023

The Israeli startup’s platform provides model validation, governance, and monitoring so all stakeholders can make better decisions about machine learning


Israeli startup Citrusˣ has announced $4.5 million in Seed funding for its end-to-end AI validation and explainability platform. The round was led by Canadian VC Awz with the participation of several angel investors.


As more industries adopt AI, the journey from model development to deployment in production is increasingly becoming a critical bottleneck for businesses. Machine learning (ML) models are often not understood outside of the data science team that developed them, posing challenges for validation, explainability, risk assessment, and legal approval.


Citrusx management group photo
Photo by: Omer Hacohen

Citrusˣ, founded by Noa Srebrnik (CEO) and Gilad Manor (CTO), has built a platform for all stakeholders in an organization’s AI pipeline to ensure ML models are robust, explainable, and fair. It enables verification and risk mitigation by data scientists and risk officers, ensuring AI is being used responsibly and fairly according to regulatory requirements.


“In most organizations, the data scientists who built the models also test and validate them, and the rest of the business is blind to what’s happening with their machine learning”

“In most organizations, the data scientists who built the models also test and validate them, and the rest of the business is blind to what’s happening with their machine learning,” said CEO Noa Srebnik. “By providing one unified platform for a whole company to use, Citrusˣ acts as the bridge that connects those mysterious ML models to the rest of the company through validation, monitoring, and reporting. Deployment and maintenance of ML models become smoother and faster, meeting regulatory demands, and helping to explain model decisions to end customers.”


The company’s patent-pending technology shows all elements and weak spots in a data space, identifies errors and vulnerabilities in an ML model, and highlights potential feature bias which leads to unexpected errors in the model. CitrusX is part of the first cohort of the Awz X-Seed Hub, a deep-tech, early-stage technology acceleration initiative.


To read the article on CTech click here.

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