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Cem Dilmegani

Cem Dilmegani

Principal Analyst
724 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

AIDec 10

Text-to-Speech Software: Hume, ElevenLabs & Resemble

As AI capabilities evolve, text-to-speech (TTS) software is becoming more adept at producing natural, human-like speech. We evaluated and compared the performance of five different TTS and sentiment analysis tools (Resemble, ElevenLabs, Hume, Azure, and Cartasia) across seven core emotion categories to determine which could most accurately, consistently, and comprehensively recognize emotional tones.

AIDec 9

RAG Frameworks: LangChain vs LangGraph vs LlamaIndex vs Haystack vs DSPy

We benchmarked 5 RAG frameworks: LangChain, LangGraph, LlamaIndex, Haystack, and DSPy, by building the same agentic RAG workflow with standardized components: identical models (GPT-4.1-mini), embeddings (BGE-small), retriever (Qdrant), and tools (Tavily web search). This isolates each framework’s true overhead and token efficiency.

DataDec 9

Roadmap to Web Scraping: Benchmark Results from 30M Requests

We crawled more than 30 million web pages using more than 50 products from 6 leading web data infrastructure companies. This massive undertaking enabled us to assess critical performance metrics, including success rates, latency, and stability at scale. Our goal was to determine which solutions truly handle the complexities of enterprise-level scraping.

Agentic AIDec 9

Best 30+ Open Source Web Agents

We tested proprietary web agents, remote browsers, and benchmarked 8 MCP servers across web search and browser automation tasks. Below are 30+ open-source web agents that enable AI to navigate, interact with, and extract data from the web, including browsing, authentication, and crawling. Open-source web agents: Accuracy benchmark See benchmark sources.

CybersecurityDec 9

Best Database Performance Monitoring Tools: Top 6 Platforms Compared

Database issues cause application failures. A memory spike crashes your server. A slow query times out user requests. We analyzed six database monitoring platforms and benchmarked three of them extensively on MySQL and MongoDB. The results show significant differences in setup complexity, query analysis capabilities, and metric accuracy.

AIDec 9

AI Hallucination: Compare Popular LLMs

AI models sometimes generate data that seems plausible but is incorrect or misleading, known as AI hallucinations. 77% of businesses concerned about AI hallucinations. We benchmarked 37 different LLMs with 60 questions to measure their hallucination rates: AI hallucination benchmark results Our benchmark revealed that xAI Grok 4 has the lowest hallucination rate (i.e.

AIDec 9

LLM Pricing: Top 15+ Providers Compared

LLM API pricing can be complex and depends on your preferred usage. We analyzed 15+ LLMs and their pricing and performance: Hover over model names to view their benchmark results, real-world latency, and pricing, to assess each model’s efficiency and cost-effectiveness. Ranking: Models are ranked by their average position across all benchmarks.

AIDec 9

No-Code AI: Benefits, Industries & Key Differences

No-code AI tools allow users to build, train, or deploy AI applications without writing code. These platforms typically rely on drag-and-drop interfaces, natural language prompts, guided setup wizards, or visual workflow builders. This approach lowers the barrier to entry and makes AI development accessible to users without a programming background.

Agentic AIDec 9

AI Agents: Operator vs Browser Use vs Project Mariner

AI agents are increasingly marketed as end-to-end digital workers, but real-world performance can vary widely depending on the task, tools, and execution environment. To understand what these systems can genuinely deliver today, we conducted hands-on benchmarking across practical business scenarios.

AIDec 9

RAG Evaluation Tools: Weights & Biases vs Ragas vs DeepEval vs TruLens

Failures in Retrieval Augmented Generation systems occur not only because of hallucinations but more critically because of retrieval poisoning. In such cases, the retriever returns documents that share substantial lexical overlap with the query but do not contain the necessary information.

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