In this episode of The CTO Show with Mehmet, I’m joined by Ahikam Kaufman, Co-Founder and CEO of Safebooks.ai, a seasoned finance executive turned entrepreneur with deep experience across startups, public companies, and large-scale acquisitions.

We explore why finance has lagged behind other functions in digital transformation, how AI is fundamentally reshaping financial governance, and why the modern CFO is becoming a transformation leader, not just a financial steward.

This conversation goes beyond buzzwords and dives into real-world problems: broken audit trails, fragmented systems, compliance risk, and how AI agents can finally deliver real-time financial truth.

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👤 About the Guest

Ahikam Kaufman is the Co-Founder and CEO of Safebooks.ai.

He began his career in accounting, served as a CFO in Silicon Valley startups, experienced multiple acquisitions including by Hewlett-Packard and Intuit, and spent over a decade as an entrepreneur.

Today, Ahikam is focused on modernizing the Office of the CFO by applying AI to financial data governance, auditability, and compliance at scale.

https://www.linkedin.com/in/ahikam-kaufman-688310/

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🎯 Key Topics Covered

• Why finance was never designed for today’s data complexity

• The two biggest blind spots in modern financial organizations

• What “audit trail” really means and why it’s so hard to achieve

• How AI agents bridge structured system data and unstructured documents

• From quote to cash: tracing transactions across fragmented systems

• Why compliance failures are often data problems, not intent problems

• The evolving role of the CFO in the AI era

• Where humans still matter and where machines outperform

• Why AI makes regulation easier to meet, not harder

• Practical advice for founders building in finance and compliance

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🧠 Key Takeaways

• Finance teams deal with massive data but are not trained as data teams

• Fragmented systems create hidden compliance and cash-flow risks

• AI can monitor 100% of financial transactions, not just samples

• Real-time governance is now technically possible for the first time

• CFOs are becoming transformation leaders, not just scorekeepers

• The future of finance is continuous, automated, and exception-driven

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🎓 What You’ll Learn

• How AI changes financial accuracy from “material” to near-perfect

• Why most financial errors happen even when teams do “everything right”

• How AI reduces headcount pressure without removing human oversight

• What founders must understand before building in fintech or compliance

• How finance can finally get its own “single pane of glass”

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⏱️ Episode Highlights (Timestamps)

• 00:00 – Ahikam’s journey from CFO to AI founder

• 05:00 – The two unsolved problems in corporate finance

• 09:30 – Why audit trails break across modern systems

• 14:00 – What really goes wrong when financial data is wrong

• 18:30 – How AI understands contracts and financial documents

• 24:00 – Humans vs machines in financial decision-making

• 30:00 – The CFO’s evolving role in AI transformation

• 36:00 – Regulation, compliance, and AI realities

• 43:00 – Advice for founders building in finance

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🔗 Resources Mentioned

• Safebooks.ai

• Topics: AI agents, financial audit trails, CFO transformation, data governance

In this episode of The CTO Show with Mehmet, I sit down with Khaled Nazif, COO of DSquares, one of the most influential yet quietly powerful enterprise loyalty platforms in the MENA region.

Khaled shares his journey from Stanford and Silicon Valley back to the region, where he helped scale DSquares into a 150M+ end-user platform serving banks, telcos, governments, and large enterprises across 16 countries.

We go deep into what loyalty really means today, why most companies still misunderstand it, how culture breaks at scale if you are not intentional, and what founders in emerging markets can learn from Silicon Valley without copying it blindly.

This is a conversation about scale, systems, leadership, and long-term thinking.

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👤 About the Guest

Khaled Nazif is the Chief Operating Officer at DSquares, a leading white-labeled loyalty and engagement platform powering some of the largest enterprises and government programs across MENA and Africa.

Before returning to the region, Khaled spent nearly a decade in Silicon Valley, earning his MBA from Stanford, founding a B2B SaaS startup, and later working at Zendesk. He brings a rare blend of operator discipline, startup grit, and enterprise execution to scaling regional platforms.

https://www.linkedin.com/in/khalednazif/

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🧠 Key Takeaways

• Why loyalty is misunderstood and often wrongly treated as a cost center

• How DSquares scaled without VC hype and stayed bootstrapped for 13 years

• What it really means to move from a “pirate” startup culture to a “navy” scale-up

• Why government loyalty programs are not an oxymoron

• The importance of productization when scaling enterprise platforms

• How culture breaks after ~150 people and what leaders must do proactively

• What MENA founders can learn from Silicon Valley and what they should ignore

• Why failure must be normalized for ecosystems to truly mature

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🎯 What You Will Learn

• How to scale enterprise platforms across multiple countries and cultures

• How loyalty, data, and behavior change intersect at scale

• Why leadership transitions matter more than founder heroics

• How to think long-term when building in emerging markets

• Why execution discipline beats hype cycles every time

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⏱ Episode Highlights & Timestamps

00:00 – Welcome and introduction

02:00 – Khaled’s journey from Stanford to Silicon Valley

05:30 – What DSquares really does and why most people don’t know it

09:00 – Scaling loyalty across banks, telcos, and governments

13:30 – Loyalty vs transactions: what most companies get wrong

18:00 – Using data and gamification to influence behavior

23:00 – Loyalty as a revenue driver, not a cost center

27:30 – Bootstrapping DSquares and resisting VC pressure

33:00 – Replacing a founder and scaling leadership responsibly

38:30 – The 150-employee culture breaking point

45:00 – Pirate vs Navy mindset and operational maturity

51:00 – Silicon Valley lessons that actually work in MENA

57:00 – Failure, risk-taking, and ecosystem maturity

01:03:00 – Advice for founders building in emerging markets

01:08:00 – Closing thoughts and where to connect with Khaled

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🔗 Resources & Mentions

• DSquares – Enterprise Loyalty & Engagement Platform : https://dsquares.com/

• Book referenced: Blitzscaling by Reid Hoffman

In this episode of The CTO Show with Mehmet, I’m joined by Alex Schlager, Founder and CEO of AIceberg, a company operating at the intersection of AI, cybersecurity, and explainability.

We dive deep into why AI agents fundamentally change enterprise risk, how shadow AI is spreading across organizations, and why monitoring black-box models with other black boxes is a dangerous mistake.

Alex explains how explainable machine learning can provide the observability, safety, and security enterprises desperately need as they adopt agentic AI at scale.

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👤 About the Guest

Alex Schlager is the Founder and CEO of AIceberg, a company focused on detection and response for AI-powered workflows, from LLM-based chatbots to complex multi-agent systems.

AIceberg’s mission is to secure enterprise AI adoption using fully explainable machine learning models, avoiding black-box-on-black-box monitoring approaches. Alex has deep expertise in AI explainability, agentic systems, and enterprise AI risk management.

https://www.linkedin.com/in/alexschlager/

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🧠 Key Topics We Cover

• Why AI agents create a new and expanding attack surface

• The rise of shadow AI across business functions

• Safety vs security in AI systems and why CISOs must now care about both

• How agentic AI amplifies risk through autonomy and tool access

• Explainable AI vs LLM-based guardrails

• Observability challenges in agent-based workflows

• Why traditional cybersecurity tools fall short in the AI era

• Governance, risk, and compliance for AI driven systems

• The future role of AI agents inside security teams

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📌 Episode Highlights & Timestamps

00:00 – Introduction and welcome

01:05 – Alex Schlager’s background and the founding of AIceberg

02:20 – Why AI-powered workflows need new security models

03:45 – The danger of monitoring black boxes with black boxes

05:10 – Shadow AI and the loss of enterprise visibility

07:30 – Safety vs security in AI systems

09:15 – Real-world AI risks: hallucinations, data leaks, toxic outputs

12:40 – Why agentic AI massively expands the attack surface

15:05 – Privilege, identity, and agents acting on behalf of users

18:00 – How AIceberg provides observability and control

21:30 – Securing APIs, tools, and agent execution paths

24:10 – Data leakage, DLP, and public LLM usage

27:20 – Governance challenges for CISOs and enterprises

30:15 – AI adoption vs security trade-offs inside organizations

33:40 – Why observability is the first step to AI security

36:10 – The future of AI agents in cybersecurity teams

40:30 – Final thoughts and where to learn more

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🎯 What You’ll Learn

• How AI agents differ from traditional software from a security perspective

• Why explainability is becoming critical for AI governance

• How enterprises can regain visibility over AI usage

• What CISOs should prioritize as agentic AI adoption accelerates

• Where AI security is heading in 2026 and beyond

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🔗 Resources Mentioned

• AIceberg: https://aiceberg.ai

• AIceberg Podcast – How Hard Can It Be? https://howhardcanitbe.ai/