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Cem Dilmegani

Cem Dilmegani

Principal Analyst
359 Articles
Stay up-to-date on B2B Tech
Cem has been the principal analyst at AIMultiple for almost a decade.

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

Media, conference & other event presentations

Sources

  1. Why Microsoft, IBM, and Google Are Ramping up Efforts on AI Ethics, Business Insider.
  2. Microsoft invests $1 billion in OpenAI to pursue artificial intelligence that’s smarter than we are, Washington Post.
  3. Empowering AI Leadership: AI C-Suite Toolkit, World Economic Forum.
  4. Science, Research and Innovation Performance of the EU, European Commission.
  5. EU’s €200 billion AI investment pushes cash into data centers, but chip market remains a challenge, IT Brew.
  6. Hypatos gets $11.8M for a deep learning approach to document processing, TechCrunch.
  7. We got an exclusive look at the pitch deck AI startup Hypatos used to raise $11 million, Business Insider.

Latest Articles from Cem

DataMar 2

Compare 45+ MLOps Tools in 2026

Machine Learning Operations (MLOps) brings DevOps principles into machine learning from model deployment to maintenance to automate transitions between training and deployment pipelines Explore 45+ MLOps tools for different components of the ML lifecycle, such as: What are the types of MLOps solution providers? Open source MLOps 63% of organizations from different sectors and 72%

Enterprise SoftwareMar 2

Top 20 Email Server Software: Features & Pricing

There are two main use cases for email servers. If you are looking for: Top 15 transactional email providers Sorting: The list ranks providers, with sponsored entries shown first along with their respective links. All non-sponsored providers are listed in order of the total number of B2B user reviews collected from G2 and Capterra.

CybersecurityMar 2

Top 13 Open Source SIEM Tools

There is no single open-source tool that delivers a complete, production-ready SIEM out of the box. Every option involves a trade-off: you either get a purpose-built SIEM with gaps in analytics, or a powerful logging and analytics stack that requires you to wire in security detection yourself.

CybersecurityMar 2

Top 6 SaaS Backup Solutions

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 some level of data redundancy, they do not protect against accidental deletion, ransomware, or insider threats.

AIMar 2

10 Risks of Generative AI & How to Mitigate Them

With industries prioritizing generative AI for innovation and automation, its potential grows. However, risks of generative AI like accuracy and ethical concerns remain. Addressing these challenges is key to ensuring AI benefits humanity. Explore the top 10 risks of generative AI and steps to mitigate them: Model reliability & output integrity risks 1.

CybersecurityMar 2

Top 8 SIEM Use Cases and Real-life Examples 

SIEM addresses this by correlating data across the entire environment, endpoints, networks, cloud applications, and authentication systems to surface connections that no single tool would catch. A login at 2 am isn’t suspicious on its own. That same login, combined with a spike in outbound transfers and a new USB device, is a different story.

CybersecurityMar 2

Top 10+ SIEM Systems & How to Choose the Best Solution

SIEM systems have evolved to become more than log aggregation tools. Some vendors developed unified product suites with UEBA, SOAR, and EDR capabilities, claiming they are “next-gen” SIEMs. Others offer products focused on traditional event and log management.

Enterprise SoftwareFeb 27

Top 7 Open Source RMM Software: Pros, Cons & Benefits in 2026

IT teams and managed service providers (MSPs) need remote monitoring and management (RMM) tools to maintain infrastructure health, patch endpoints, respond to alerts, and manage devices at scale.

AIFeb 27

Best AI Code Editor: Cursor vs Windsurf vs Replit

Making an app without coding skills is highly trending right now. But can these tools successfully build and deploy an app? We benchmarked 6 AI code editors across 10 real-world web development challenges. Each task required implementations such as backend, frontend, authentication, state management.

AIFeb 27

Vision Language Models Compared to Image Recognition

Can advanced Vision Language Models (VLMs) replace traditional image recognition models? To find out, we benchmarked 16 leading models across three paradigms: traditional CNNs (ResNet, EfficientNet), VLMs ( such as GPT-4.1, Gemini 2.5), and Cloud APIs (AWS, Google, Azure).