Untrap Information

Untrap builds applied AI that reads the operational data traditional systems struggle to interpret. Organizations generate enormous amounts of valuable information across documents, contracts, emails, notes, service records, logs, and other forms of unstructured data. Much of it contains important signals about risk, performance, customer commitments, operational issues, and changing business conditions—but those signals are difficult to identify at scale. Untrap analyzes structured and unstructured data together to surface specific, traceable findings that people can verify and act on. Our technology was first proven in IT service operations, where it analyzed tens of thousands of records and uncovered issues including revenue leakage, delivery failures, recurring operational problems, and customer risk that conventional dashboards and manual review had missed. That work demonstrated a broader capability: using AI to understand what is happening across complex operational records, identify where reality differs from expectations or commitments, and determine where action may be required. We are now researching broader applications for this technology, with a particular focus on regulated financial markets and the companies that serve them. We are actively speaking with industry leaders to better understand where operational complexity, AI adoption, changing technology, customer obligations, and regulatory expectations create problems that existing tools do not solve well. Our approach remains the same: read what traditional systems cannot, connect the evidence, and turn it into actionable intelligence.