Finance software is starting to deploy itself.

In this episode of Terminal Value, Nik Singh sits down with Ahikam Kaufman, Co-Founder and CEO of SafeBooks, to discuss how AI agents are changing finance operations, revenue integrity, and the modern CFO stack.

SafeBooks is building an agentic revenue integrity platform that connects systems like CPQ, CRM, contracts, billing, ERP, and revenue recognition — then gives finance teams a way to validate transactions, catch errors, automate workpapers, and ask questions across their financial data.

We discuss why finance teams still spend so much time manually checking data, how AI can create a financial data graph across systems, why forward-deployed engineering may become less important over time, and why many finance AI workflows may not require frontier models.

We also cover the future of accounting work, the difference between SafeBooks and legacy close-management platforms, and what happens when finance operations become real-time, agent-driven, and self-serve.

Chapters:
00:00 Cold open: AI agents for finance operations
00:45 Introduction: SafeBooks and the revenue integrity problem
01:44 What revenue integrity means in practice
03:20 The finance stack behind revenue integrity
04:31 What an agentic revenue integrity workflow does
06:09 The financial data graph behind SafeBooks
08:54 Deploying across CRM, billing, ERP, and accounting systems
10:27 Are forward-deployed engineers going away?
11:16 SafeBooks’ target customer and mid-market use case
13:03 Pricing AI software with SaaS + usage models
16:20 Why finance AI may not need frontier models
18:39 SafeBooks vs. BlackLine, FloQast, and close-management tools
21:09 Why deployment, context, and real-time controls matter
23:40 How AI changes finance employment
25:16 The future of automated finance operations
27:51 Closing and final takeaways

Subscribe for more conversations on AI, software, markets, and where value accrues.