Ahikam Kaufman of Safebooks AI, co-founder and CEO, discusses how their company injects agentic artificial intelligence into corporate finance to automate close processes and ensure auditable accuracy. Kaufman outlines a systems approach that emphasizes platform strategies over point solutions and centers on data integrity and guardrails, ontology and graph-based data layers and SOC 1 certification. They describe commercial traction and deployment models. theCUBE Research frames the conversation while hosts John Furrier and Gabe Elabe probe product-market fit and operational impact. Key takeaways include finance becoming a bounding function for enterprise AI and the centrality of auditable accuracy supported by a human-in-the-loop reviewer. Kaufman directly attributes Safebooks AI's agent layer with automating close processes, generating proof-of-work documentation and shifting teams from preparation to exception management. The discussion highlights real-world traction including 15 paying customers, a $50 million seed round and plans to pursue a Series A.