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Cem Dilmegani

Cem Dilmegani

Principal Analyst
360 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

DataNov 2

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.

AIOct 31

Cloud GPUs for Deep Learning: Availability& Price / Performance

If you are flexible about the GPU model, identify the most cost-effective cloud GPU based on our benchmark of 10 GPU models in image and text generation & finetuning scenarios. If you prefer a specific model (e.g. A100), identify the lowest-cost GPU cloud provider offering it.

DataOct 31

Top 5+ Geonode Alternatives: Pricing & Features

Proxy services are essential for companies to use technologies such as web scraping, ad verification, and market research. We reviewed Geonode and its top competitors including Bright Data, Webshare, Oxylabs, Decodo, SOAX, and IPRoyal.

Enterprise SoftwareOct 27

Control-M for Enterprise Workload Automation

Control-M by BMC Software helps teams coordinate and automate data and application workflows across environments, including mainframes, the cloud, and hybrid systems. It gives users a single place to schedule jobs, track progress, and handle dependencies.

Agentic AIOct 24

Building Personal AI Agents + 18 Agent Platforms and Tools

We spent the two days experimenting with real-world demos and tools to build personal AI assistants that can handle your tasks, such as scheduling meetings, managing notes, or sorting through emails. We will dive into three main approaches to building and using personal AI assistants, with real-world examples for each: 1.

Enterprise SoftwareOct 21

Top 4 WAN Monitoring Software

We selected WAN monitoring software that offers bandwidth monitoring and traffic analysis, along with real-time tracking of network devices, servers, applications, and infrastructure across wide-area networks. See a comparison of popular WAN monitoring software: Selection criteria We selected WAN monitoring tools meeting these criteria: Top 5 WAN Monitoring Software 1.

Agentic AIOct 18

Top 4 AI Search Engines Compared

Searching with LLMs has become a major alternative to Google search. We benchmarked the following AI search engines to see which one provides the most correct results: Benchmark results Deepseek is the leader of this benchmark, by correctly providing 57% of the data in our ground truth dataset.

AIOct 15

AI Text Generation: Top 16 Use Cases & 4 Case Studies

Generative AI, a subset of artificial intelligence, allows for creating new content, such as text, code, images, designs, and videos, by learning from and building on existing data. Explore how generative AI can be used to generate content in the form of text via 4 use cases and 2 case studies of AI text generation..

Enterprise SoftwareOct 9

RPA Pricing Compared Across Leading Vendors

We reviewed leading RPA pricing in detail to identify the lowest RPA vendor license fees: Calculating the total cost of ownership (TCO) for RPA software is complex because there are various factors that affect RPA pricing, such as: See license costs of market-leading solutions for different scenarios with different numbers and types of licenses: RPA pricing

Agentic AIOct 1

Best 17 AgentOps Tools: AgentNeo, Langfuse & more ['26]

We will introduce leading AgentOps tools, outline the challenges of operating agents and explain how an AgentOps automation pipeline can address them through observability, metrics, issue detection. How to think about AgentOps One of the hard parts of operating reliable agentic systems is making sure system behavior is observable and traceable at every step.