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Cem Dilmegani

Cem Dilmegani

Principal Analyst
723 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

CybersecurityDec 4

Top 10 USB Blocking Software

Based on our DLP review benchmark, user reviews & feature comparisons, here are the top 10 USB Blocking Software alternatives. See why we selected them by following the links below: Unmanaged devices increase data breach risk. Control over devices, including USBs, is key to effective cybersecurity.

AIDec 4

Agentic Document Extraction: LandingAI & more

Agentic Document Extraction (ADE) is a specialized form of Optical Character Recognition (OCR) that extracts data from various file types. It combines document processing, data retrieval, structured output generation, and automation to streamline knowledge work. ADE stands out from traditional OCR by its ability to recognize complex document structures, such as tables, flowcharts, and images.

AIDec 4

Receipt OCR Benchmark with LLMs

Extracting data from receipts is essential for businesses, as millions of employees submit their work-related expenses via receipts. With the latest developments in generative AI and large language models, data extraction accuracy has reached a level comparable to that of humans.

CybersecurityDec 4

Top Open Source UEBA Tools & Commercial Alternatives

At their core, UEBA solutions aim to identify patterns in data, whether from real-time streams or historical datasets. Open source UEBA tools After reviewing the documentation of each open-source UEBA framework/tool, I listed leading open-source behavior analytics technologies that provide standard SIEM-like capabilities (e.g., alerting, MITRE ATT&CK threat intelligence framework, API-based ingestion from data sources).

CybersecurityDec 3

Compare 10+ Open Source Security Audit Tools

Previously, I explained 30+ security audit tools based on their specializations. To compare vulnerability scanning, web application scanning, and security automation & simulation capabilities of the best free open-source auditing tools, I spent several hours going through the documentation and watching demos of these tools.

CybersecurityDec 3

AI IPS: 6 Real-life Use Cases & Leading Tools

AI intrusion prevention systems (IPS) use machine learning algorithms and behavioral analytics to detect and prevent several cyber threats. These systems integrate AI with traditional IPS technologies, improving their ability to detect and mitigate attacks in real time. AI IPS can: 1.

CybersecurityDec 3

Top 6 Open-Source Data Governance Tools 

Open source data governance tools with data cataloging capabilities help collect, process, and maintain metadata, serving as a central repository for tracking data operations. Organizations use these tools in data security posture management (DSPM), data discovery, data lineage, and data quality initiatives.

DataDec 3

Audio Data Collection for AI: Challenges & Best Practices

As the demand for voice recognition and virtual assistants grows , so does the need for audio data collection services. You can also work with an audio or speech data collection service to acquire relevant training data for your speech processing projects.

Enterprise SoftwareDec 3

7 Ways SAP Job Scheduling Optimizes IT Operations

Enterprise automation plays a key role in business digitalization. Enterprise Resource Planning (ERP) systems, including SAP, the largest ERP by sales, are at the center of most enterprises’ businesses and are involved in numerous processes.

DataDec 3

5 Steps to OCR Training Data

The interest in optical character recognition (OCR) and intelligent character recognition (ICR) technology is falling as companies switch to more automated solutions, such as machine learning-enabled data extraction. However, due to its various benefits, many companies still use or plan to use tools powered by OCR technology in their paper-based operations.