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Cem Dilmegani

Cem Dilmegani

Principal Analyst
688 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

Agentic AIJan 16

Building AI Agents with Anthropic's 6 Composable Patterns

We spent 3 days experimenting workflows and agent pipelines in n8n according to Anthropic’s and OpenAI’s guides on building effective AI agents. We are going to distill down everything we have learned to give you a guide to build functional AI agents in your LLM projects.

Enterprise SoftwareJan 16

Compare Remote Control Software: NinjaOne & Acronis

We tested the top 3 remote control software (also known as remote access software) to evaluate the general UI and remote control experience, their remote control quality, protocols, and unique capabilities: ​​Strengths and weaknesses based on our observations An agent needs to be installed for each tool we tested in this benchmark.

AIJan 16

Top 10 Healthcare Analytics Use Cases with Examples ['26]

The $28 billion healthcare analytics marketis transforming how providers, payers, and life sciences organizations compete, and companies that move now can seize the advantage. By delivering solutions that drive predictive care, reduce costs, and optimize operations, analytics unlocks new revenue streams and strengthens customer loyalty in a healthcare industry racing toward data-driven performance.

Agentic AIJan 16

Building a No-Code AI Lead Generation Workflow with n8n

I have been reviewing popular AI sales agents, including  AiSDR and Outreach.io. While these platforms support lead management, they are typically focused on broader sales engagement and delivered as commercial packages with costs ranging from $2K to $5K per user per month.

Agentic AIJan 16

Low/No-Code AI Agent Builders: n8n,make, Zapier in 2026

Low- and no-code AI agent builders let users create automated, AI-driven workflows without writing complex code, making agent development faster and accessible to non-technical teams.

Enterprise SoftwareJan 16

Top 8 Observability Software with Pricing Including Solarwinds

Observability platforms promise complete visibility across distributed systems, but selecting the right one is hard when every vendor claims they do everything. We analyzed the top 8 observability software products by reviewing their documented capabilities, public pricing, verified customer reviews, and enterprise reference cases.

Enterprise SoftwareJan 16

CRM in Retail: Top 4 Tools, 7 Key Features & Benefits ['26]

As the retail industry continues to grow, so does the need for automation due to the increased quantity and magnitude of operations.

Agentic AIJan 16

Top 8 Agentic CRM Platforms in 2026

Customer relationship management tools are getting smarter. Instead of just storing data, agentic CRM platforms can plan tasks, execute workflows, and adjust strategies autonomously. Think of them as CRM systems with built-in intelligence that actually do the work instead of waiting for you to click buttons.

Enterprise SoftwareJan 16

CRM AI Systems: Top 5 Vendors and Key Features in 2026

AI-powered CRM systems leverage machine learning, natural language processing (NLP), and data analytics to enhance the capabilities of traditional CRM. The adoption of AI in CRM is driven by the need for more personalized customer experiences and efficient data management.

CybersecurityJan 16

Top 10+ Data Governance Tools in 2026

Organizations struggle when customer data exists in three different formats across sales, finance, and marketing databases. Your reports don’t match because “John Smith” appears as “J. Smith” in one system and “Smith, John” in another. Data governance tools solve this by establishing standards and policies for who can access data and how it gets used.