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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

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.

Enterprise SoftwareApr 16

Top 12 RMM Software Tested: Features and Pricing

RMM software components keep business devices secure and efficient, thanks to features like patch management. We benchmarked the top 3 RMM platforms (NinjaOne, ManageEngine, and Acronis) by deploying them to seven servers across six AWS regions. We analyzed how they handle agent deployment and monitoring from scratch.

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

Tabular Models Benchmark: Performance Across 19 Datasets 2026

We benchmarked 7 widely used tabular learning models across 19 real-world datasets, covering ~260,000 samples and over 250 total features, with dataset sizes ranging from 435 to nearly 49,000 rows. Our goal was to understand top-performing model families for datasets of different sizes and structure (e.g. numeric vs.

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.

DataApr 15

Best Rotating Proxies in 2026: Residential, Mobile & 4G Ranked

We benchmarked major rotating proxies (residential, datacenter, and mobile) using over 200,000 requests, including 100,000 parallel requests, for major e-commerce and social media sites.

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.

AIApr 15

LLM Inference Engines: vLLM vs LMDeploy vs SGLang

We benchmarked 3 leading LLM inference engines on NVIDIA H100: vLLM, LMDeploy, and SGLang. Each engine processed identical workloads: 1,000 ShareGPT prompts using Llama 3.1 8B-Instruct to isolate the true performance impact of their architectural choices and optimization strategies.

AIApr 15

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. Cloud GPU price per throughput Two common pricing models for GPUs are “on-demand” and “spot” instances.

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