Cem Dilmegani
Cem's work at AIMultiple has been cited by leading global publications including Business Insider, Forbes, Morning Brew, Washington Post, global firms like HPE, NGOs like World Economic Forum and supranational organizations like European Commission. [1], [2], [3], [4], [5]
Professional experience & achievements
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider. [6], [7]
Research interests
Cem's work focuses on how enterprises can leverage new technologies in AI, agentic AI, cybersecurity (including network security, application security) and data including web data.Cem's hands-on enterprise software experience contributes to his work. Other AIMultiple industry analysts and the tech team support Cem in designing, running and evaluating benchmarks.
Education
He graduated as a computer engineer from Bogazici University in 2007. During his engineering degree, he studied machine learning at a time when it was commonly called "data mining" and most neural networks had a few hidden layers.He holds an MBA degree from Columbia Business School in 2012.
Cem is fluent in English and Turkish. He is at an advanced level in German and beginner level in French.
External publications
- Cem Dilmegani, Post-AI Banking: Millions of jobs at risk as banks automate their core functions. International Banker.
- Cem Dilmegani, Bengi Korkmaz, and Martin Lundqvist (December 1, 2014).Public-sector digitization: The trillion-dollar challenge, McKinsey & Company.
Media, conference & other event presentations
- Answers to Korea24's questions on job loss due to AI, Korea24
- Real Estate and Technology, presented by Hofstra University’s Wilbur F. Breslin Center for Real Estate Studies and the Frank G. Zarb School of Business in 2023 and 2024.
- Radar AI session (June 22, 2023): "Increasing Data Science Impact with ChatGPT".
- Generative AI Atlanta meetup: Generative AI for Enterprise Technology.
Sources
- Why Microsoft, IBM, and Google Are Ramping up Efforts on AI Ethics, Business Insider.
- Microsoft invests $1 billion in OpenAI to pursue artificial intelligence that’s smarter than we are, Washington Post.
- Empowering AI Leadership: AI C-Suite Toolkit, World Economic Forum.
- Science, Research and Innovation Performance of the EU, European Commission.
- EU’s €200 billion AI investment pushes cash into data centers, but chip market remains a challenge, IT Brew.
- Hypatos gets $11.8M for a deep learning approach to document processing, TechCrunch.
- We got an exclusive look at the pitch deck AI startup Hypatos used to raise $11 million, Business Insider.
Latest Articles from Cem
Building Local AI Agents: Goose, Observer AI, AnythingLLM
We spent three days mapping the ecosystem of local AI agents that run autonomously on personal hardware without depending on external APIs or cloud services. We organized the tools we evaluated into five categories: Local AI agent stack See category descriptions.
Top 10 Edge AI Chip Makers with Use Cases
The demand for low-latency processing has driven innovation in edge AI chips. These processors are designed to perform AI computations locally on devices rather than relying on cloud-based solutions. Based on our experience analyzing AI chip makers, we identified the leading solutions for robotics, industrial IoT, computer vision, and embedded systems.
GPU Software for AI: CUDA vs. ROCm
Raw hardware specifications tell only half the story in GPU computing. To measure real-world AI performance, we ran 52 distinct tests comparing AMD’s MI300X with NVIDIA’s H100, H200, and B200 across multi-GPU and high-concurrency scenarios.
AI Browser Security Risks: ChatGPT Atlas and Comet
Agentic AI browsers now handle your banking, emails, and private documents. A single malicious link can turn these assistants against you. Recent discoveries in Perplexity’s Comet browser reveal how attackers exploit prompt injection to steal credentials, exfiltrate data, and hijack authenticated sessions.
15 Security Threats to LLM Agents (with Real-World Examples)
Even a few years ago, the unpredictability of large language models (LLMs) would have posed serious challenges. One notable early case involved ChatGPT’s search tool: researchers found that webpages designed with hidden instructions (e.g., embedded prompt-injection text) could reliably cause the tool to produce biased, misleading outputs, despite the presence of contrary information.
Top PAM Solutions: 8 Commercial Vendors + Free Alternatives
We spent three days testing and reviewing popular Privileged Access Management (PAM) solutions. We used the free trials and admin consoles of BeyondTrust, Keeper PAM, and ManageEngine PAM360. For solutions that required registration, we relied on official product documentation and user experiences to assess their capabilities.
Top 5 SaaS Backup Solutions for MSPs
Many businesses operate under the misconception that their SaaS providers (like Microsoft 365 or Google Workspace) fully protect their data from all threats. While these platforms offer robust infrastructure and some level of data redundancy, they do not protect against accidental deletion, ransomware, or insider threats.
The LLM Evaluation Landscape: 16 Frameworks by Functionality
We spent 2 days reviewing popular LLM evaluation frameworks that provide structured metrics, logs, and traces to identify how and when a model deviates from expected behavior.
RAG Frameworks: LangChain vs LangGraph vs LlamaIndex vs Haystack vs DSPy
We benchmarked 5 RAG frameworks: LangChain, LangGraph, LlamaIndex, Haystack, and DSPy, by building the same agentic RAG workflow with standardized components: identical models (GPT-4.1-mini), embeddings (BGE-small), retriever (Qdrant), and tools (Tavily web search). This isolates each framework’s true overhead and token efficiency.
Top 5 Open Source Database Monitoring Tools
Commercial database monitoring tools often promise polished user interfaces and dedicated enterprise support. Open-source solutions are increasingly chosen for their transparency, cost-effectiveness, community-driven innovation, and flexibility. We’ve analyzed both approaches to understand the current landscape.
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