Basil Systems unveils AI-powered Safety Signaling Platform to boost post-market device surveillance

Basil Systems unveils AI-powered safety system for devices: ©Lalaka - stock.adobe.com

Basil Systems has launched a new artificial intelligence solution designed to transform post-market surveillance for medical devices from a reactive process into a proactive safety system. The company’s new MedTech Safety Signaling platform leverages AI to detect early signs of risk and prevent patient harm before it occurs.

Medical device makers operate in a landscape crowded with millions of data points—from adverse event reports and product recalls to regulatory filings and internal quality documentation. Traditionally, teams have manually reviewed this information to identify safety issues, a slow and resource-intensive process that often uncovers risks only after a problem has escalated.

Basil’s Safety Signaling tool automates and enhances that process. It uses large language models trained on what the company describes as the industry’s most comprehensive indexed dataset, scanning regulatory documents, inspection reports, and adverse event narratives to uncover subtle, predictive correlations invisible to manual review. The AI interprets the meaning of text data, grouping related events by confidence level and linking each finding to original source documents.

The system enables manufacturers to identify emerging safety trends, improve corrective and preventive actions, and even anticipate future areas of regulatory scrutiny. According to Basil, the platform is already in use by several top global device makers to predict recall risks, connect safety issues to specific supply chain or design factors, and inform product development.

“Medical device companies are drowning in post-market data but starving for predictive analytics and intelligence,” said Anthony Cirurgiao, CEO and founder of Basil Systems. “Our AI-powered Safety Signaling delivers those insights. This isn’t about finding more data; it’s about finding the critical connections in the data that already exist.”

AI’s expanding role in device safety and regulatory oversight

Artificial intelligence is rapidly reshaping how medical device manufacturers manage compliance, safety, and risk. As post-market surveillance becomes more data-driven, regulators are emphasizing continuous monitoring and early detection of potential safety concerns.

The U.S. Food and Drug Administration has repeatedly highlighted the importance of robust post-market systems in recent years, particularly as device complexity grows and connected technologies introduce new types of risk. AI platforms like Basil’s could play a central role in meeting those expectations by automating pattern recognition across vast data ecosystems that would overwhelm human analysts.

Industry experts say such tools could also help companies reduce costly recalls. According to FDA data, hundreds of device recalls occur each year—many linked to issues such as software errors, manufacturing defects, or component failures that might have been flagged earlier through smarter data analysis.

Beyond compliance, AI-driven surveillance is becoming a key competitive advantage. Companies that can rapidly detect and resolve emerging risks are better positioned to protect their reputations and maintain physician and patient trust. As more device makers adopt advanced analytics for safety monitoring, post-market intelligence is likely to evolve from a regulatory obligation into a strategic asset for innovation and quality improvement.