Services
Contact Us
No results found.
Cem Dilmegani

Cem Dilmegani

Principal Analyst
346 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 enterprise AI and software.

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

Enterprise SoftwareApr 17

Best 12+ Android Emulators in 2026

Android emulators let you run Android apps and games on PC, Mac, and browsers. Different emulators excel in different use cases. Below is a list of the top Android emulators categorized by their strengths from gaming to app development, security testing, and everyday Android app usage.

CybersecurityApr 17

Top 5 Vulnerability Scanning Tools

Vulnerability scanning tools identify security weaknesses in networks, applications, and systems. Organizations evaluate these tools based on scanning methods (DAST/IAST/SCA), SIEM integration, deployment options, and pricing. Our analysis covers five vulnerability scanning solutions based on technical capabilities and market presence.

Enterprise SoftwareApr 17

Axway MFT: A Comprehensive Guide in 2026

Managed File Transfer (MFT) solutions handle secure data movement between systems. Traditional protocols such as FTP and HTTP lack the security and compliance features that modern enterprises require. Axway is part of 74Software, formed through the combination of Axway and Sopra Banking Software, serving over 11,000 companies globally, including 1,500+ financial service customers.

Enterprise SoftwareApr 16

Top Alternatives to Dollar Universe Workload Automation

We selected the top alternatives to Dollar Universe based on their popularity, ratings on B2B review platforms, features, scalability, ease of use, and ability to integrate with diverse IT environments.

Agentic AIApr 16

Best 30+ Open Source Web Agents in 2026

We tested 30+ open-source web agents across four categories: autonomous agents, computer-use controllers, web scrapers, and developer frameworks. We ran identical benchmarks using the WebVoyager test suite, which covers 643 tasks across 15 real websites, to measure which tools actually complete multi-step web tasks and which fail when sites use dynamic dropdowns or JavaScript-heavy layouts.

AIApr 16

Best 10 Serverless GPU Clouds & 14 Cost-Effective GPUs

Serverless GPU can provide easy-to-scale computing services for AI workloads. However, their costs can be substantial for large-scale projects. Navigate to sections based on your needs: Serverless GPU price per throughput Serverless GPU providers offer different performance levels and pricing for AI workloads.

AIApr 16

100+ AI Use Cases with Real Life Examples in 2026

Learning AI use cases have measurable benefits. During my ~2 decades of experience of implementing advanced analytics & AI solutions at enterprises, I have seen the importance of use case selection. I analyzed 100+ AI use cases, their real-life examples and categorized them by business function and industry.

Agentic AIApr 16

OpenClaw (Moltbot/Clawdbot) Use Cases and Security 2026

OpenClaw (formerly Moltbot and Clawdbot) is an open-source, self-hosted AI assistant designed to execute local computing tasks and interface with users through standard messaging platforms. Unlike traditional chatbots that function as advisors generating text, OpenClaw operates as an autonomous agent that can execute shell commands, manage files, and automate browser operations on the host machine.

AIApr 16

Hybrid RAG: Boosting RAG Accuracy

Dense vector search is excellent at capturing semantic intent, but it often struggles with queries that demand high keyword accuracy. To quantify this gap, we benchmarked a standard dense-only retriever against a hybrid RAG system that incorporates SPLADE sparse vectors.

AIApr 15

Multimodal Embedding Models: Apple vs Meta vs OpenAI

Multimodal embedding models excel at identifying objects but struggle with relationships. Current models struggle to distinguish “phone on a map” from “map on a phone.” We benchmarked 7 leading models across MS-COCO and Winoground to measure this specific limitation. To ensure a fair comparison, we evaluated every model under identical conditions using NVIDIA A40 hardware and bfloat16 precision.

...89101112...