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Nazlı Şipi

Nazlı Şipi

AI Researcher
4 Articles
Nazlı is a data analyst at AIMultiple. She has prior experience in data analysis across various industries, where she worked on transforming complex datasets into actionable insights.

She is also part of the benchmark team, focusing on large language models (LLMs), AI agents, and agentic frameworks.

Nazlı holds a Master’s degree in Business Analytics from the University of Denver.

Latest Articles from Nazlı

Agentic AIOct 16

Benchmarking Agentic AI Frameworks in Analytics Workflows

Frameworks for building agentic workflows differ substantially in how they handle decisions and errors, yet their performance on imperfect real-world data remains largely untested.

Agentic AISep 24

Vision Language Models Compared to Image Recognition

Can advanced Vision Language Models (VLMs) replace traditional image recognition models? To find out, we benchmarked 16 leading models across three paradigms: traditional CNNs (ResNet, EfficientNet), VLMs ( such as GPT-4.1, Gemini 2.5), and Cloud APIs (AWS, Google, Azure).

AISep 24

LLM Latency Benchmark by Use Cases

The effectiveness of large language models (LLMs) is determined not only by their accuracy and capabilities but also by the speed at which they engage with users. We benchmarked the performance of leading language models across various use cases, measuring their responsiveness to user input.

Agentic AIOct 11

Top 5 Open-Source Agentic Frameworks

We evaluated practical performance of popular open-source AI agent frameworks with 4 data analysis tasks (e.g. clustering) on each framework. Each task was executed 100 times per framework to measure consistency, performance, and usability under realistic workloads. We also examine their agent and function definitions, memory management, and human-in-the-loop features.