Mert Palazoğlu
Mert Palazoglu has been an industry analyst at AIMultiple since 2023.
Research interests
His work focuses on the latest trends, companies, and innovations in:- Artificial intelligence (AI)
- Cyber security with a focus on network security
- Customer service software
- Proxies for data collection
Education
He graduated with a BS in Management from Bilkent University in 2021.
Latest Articles from Mert
Low/No-Code AI Agent Builders: n8n, AgentKit, make, Zapier
We spent three days setting up and configuring AI agent workflows using the free tiers of popular low/no-code tools, including n8n (self-hosted), make, and Zapier, and evaluated OpenAI’s AgentKit based on its official documentation.
Best 7 AI Testing Platforms for QA
We evaluated AI testing platforms embedded with AI agents; most were overhyped Selenium/Playwright with marketing. A few were capable of writing/maintaining test cases or visual testing, though even these tools still have notable limitations. From these, we selected 7 platforms and categorized them by their primary focus areas.
LCMs: From LLM Tokenization to Concept-level Representation
Large concept models (LCMs), as introduced by Meta in their work on “Large Concept Models,” represent a fundamental shift away from token-based prediction toward concept-level representation.
Authorization for AI Agents: Permit.io, Descope & more
I have been exploring agent identity and the authentication/authorization platforms that could support it, while also examining how standards like OAuth 2.0 and frameworks such as Keycloak might apply. Below, I listed the best AI agent–specific platforms and features, categorized by their primary focus.
How we Moved from LLM Scorers to Agentic Evals?
Evaluating LLM applications primarily focuses on testing an application end-to-end to ensure it performs consistently and reliably. We previously covered traditional text-based LLM evaluation methods like BLEU or ROUGE. Those classical reference-based NLP metrics are useful for tasks such as translation or summarization, where the goal is simply to match a reference output.
Top 40+ AI Developer Tools for Software Development
We have been experimenting with AI development tools in our code generation and code editing benchmarks for months. We have seen that AI agents like Claude Code are highly capable of software development, achieving ~%90 success rate.
Top 11 Open Source AI Platforms & Libraries
Deploying your own AI model or, in some cases, fine-tuning pre-existing models comes with several challenges: Open-source platforms that offer unified APIs help address these challenges by enabling multi-cloud deployment, optimizing GPU resource management.
The Industrial AI Agent Landscape: 30+ Platforms to Watch
Industrial AI agents address the limitations of siloed data by autonomously integrating and deriving actionable insights from IoT, controls systems (e.g. SCADA), and connected assets.
Agentic AI Architecture for Industrial Systems
Agentic AI allows natural language interaction with industrial systems, enabling users to query data and receive actionable insights. We will outline a reference architecture designed for industrial environments, describe how task-specific agents and tools can be orchestrated. We will also explore current state of natural language interfaces (NLIs) in industrial systems.
12 Reasons AI Agents Still Aren't Ready
For all the bold promises from tech CEOs about AI agents “joining the workforce” and driving “multi-trillion-dollar opportunities,” the reality is far less inspiring. What we currently have are not autonomous agents, but glorified chatbots dressed in fancy packaging; mostly mimicking scripts. Give them the same task twice, and you’ll often get wildly different results.
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