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Cem Dilmegani

Cem Dilmegani

Principal Analyst
583 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

AIFeb 6

Deep Learning in Healthcare: 12 Real-World Applications 

The computing capabilities of deep learning models enable fast, accurate, and efficient operations in patient care, R&D, and insurance. Key deep learning in healthcare includes: IDC claims that: Patient Care 1.

CybersecurityFeb 6

Top 5 ZTNA Open Source Components

ZTNA is replacing VPNs in many organizations as part of a broader move toward zero-trust security. ZTNA open-source tools offer a cost-effective way to authorize access at each layer, securing remote access to resources.

CybersecurityFeb 6

Top 13 Open Source SIEM Tools in 2026

Unlike commercial SIEMs such as ManageEngine Log360, open-source SIEM tools commonly lack core SIEM capabilities, including event correlation, log analytics, alerting, or require combining with other tools. However, several network defensive tools (e.g., intrusion detection and prevention systems and network monitoring tools) can be used as SIEM tools with fine-tuning.

Enterprise SoftwareFeb 6

Top 6 Log Analysis Software Including Solarwinds in 2026

When servers crash at 3 AM or applications start throwing errors, teams need to quickly understand what went wrong. Log analysis platforms help by collecting scattered log files from different systems and making them searchable in a single location.

AIFeb 6

Top 30+ NLP Use Cases in 2026 with Real-life Examples

The NLP market reached $34.83 billion in 2026, with projections to hit $93.76 billion by 2032. Healthcare is adopting AI at twice the rate of the broader economy, while the voice recognition market has grown to $22.49 billion in 2026, projected to reach $61.71 billion by 2031. We analyzed 250+ deployments across industries.

Agentic AIFeb 6

Moltbook: Agent Driven Social Media [2026]

The rapid growth of OpenClaw has triggered an unusual social experiment: Moltbook, a Reddit-like social platform where agents interact with each other. Launched on the 28th of January, 2026, and started to get attention in a short time span. It reached 1.5m+ agents in its first week.

AIFeb 5

Large Language Models in Cybersecurity in 2026

We evaluated 7 large language models across 9 cybersecurity domains using SecBench, a large-scale and multi-format benchmark for security tasks. We tested each model on 44,823 multiple-choice questions (MCQs) and 3,087 short-answer questions (SAQs), covering areas such as data security, identity & access management, network security, vulnerability management, and cloud security.

DataFeb 5

Best Database Performance Monitoring Tools: Top 5 Platforms Compared

Database issues cause application failures: A memory spike crashes your server, and a slow query times out user requests. We analyzed six database monitoring platforms and benchmarked three of them extensively on MySQL and MongoDB by installing them from scratch, running identical workloads, and documenting every step of the setup and monitoring experience.

Agentic AIFeb 5

Top 8 Agentic CRM Platforms in 2026

Customer relationship management tools are getting smarter. Instead of just storing data, agentic CRM platforms can plan tasks, execute workflows, and adjust strategies autonomously. Think of them as CRM systems with built-in intelligence that actually do the work instead of waiting for you to click buttons.

AIFeb 5

Embedding Models: OpenAI vs Gemini vs Cohere in 2026

The effectiveness of any Retrieval-Augmented Generation (RAG) system depends on the precision of its retriever. We benchmarked 11 leading text embedding models, including those from OpenAI, Gemini, Cohere, Snowflake, AWS, Mistral, and Voyage AI, using ~500,000 Amazon reviews.