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Şevval Alper

Şevval Alper

AI Researcher
19 Articles
Stay up-to-date on B2B Tech
Şevval is an AI researcher at AIMultiple. She has previous research experience in pseudorandom number generation using chaotic systems.

Research interests

Şevval focuses on AI coding tools, AI agents, and quantum technologies.

She is part of the AIMultiple benchmark team, conducting assessments and providing insights to help readers understand various emerging technologies and their applications.

Professional experience

She contributed to organizing and guiding participants in three “CERN International Masterclasses - hands-on particle physics” events in Türkiye, working alongside faculty to facilitate learning.

Education

Şevval holds a Bachelor's degree in Physics from Middle East Technical University.

Latest Articles from Şevval

Agentic AI
Benchmark
Aug 21

AI Agent Platforms Benchmark: Claude Managed Agents vs Google Vertex Agent Engine

We benchmarked 4 AI agent platforms across 3 dimensions: task completion (10 coding tasks × 3 runs), harness-specific capabilities (steering, reconnection, long-conversation recall, large-file handling), and cost. Claude Managed Agents and Vertex AI Agent Engine both achieve 100% pass rates on the task suite, with Vertex winning on cost ($1.45 vs $2.50). For harness-specific features…

Agentic AI
Benchmark
Aug 21

MCP Benchmark: Top MCP Servers for Web Access

We benchmarked 8 MCP servers across web search and extraction, as well as browser automation tasks, by running 4 different tasks 5 times on all suitable MCPs. We also performed a load test involving 250 concurrent AI agents. *Web search & extraction tasks are run with Bright Data’s default MCP server, browser automation tasks are…

AI
Insight
Aug 21

LLM Parameters: GPT-5 High, Medium, Low and Minimal

Some LLMs, such as OpenAI’s GPT-5 family, come in different versions (e.g., GPT-5, GPT-5-mini, and GPT-5-nano) and with various parameter settings, including high, medium, low, and minimal. Below, we explore the differences between these model versions by gathering their benchmark performance and the costs to run the benchmarks. We used the GPT-5 family in our…

AI
Benchmark
Aug 21

Best AI Code Editor: Cursor vs Windsurf vs Replit

Making an app without coding skills is highly trending right now. But can these tools successfully build and deploy an app? We benchmarked 6 AI code editors across 10 real-world web development challenges. Each task required implementations such as backend, frontend, authentication, state management. We evaluated backend correctness, frontend behavior, and combined performance, and analyzed…

AI
Benchmark
Aug 21

Speech-to-Text Benchmark: Deepgram vs. Whisper

We benchmarked the leading speech-to-text (STT) providers, focusing specifically on healthcare applications. Our benchmark used real-world examples to assess transcription accuracy in medical contexts, where precision is crucial. Based on both word error rate (WER) and character error rate (CER) results, GPT-4o-transcribe demonstrates the highest transcription accuracy among all evaluated speech-to-text systems. Deepgram Nova-v3 and…

AI
Benchmark
Aug 21

OCR Benchmark: Text Extraction / Capture Accuracy

OCR accuracy is critical for many document processing tasks, and SOTA multi-modal LLMs are now offering an alternative to OCR. We benchmarked leading OCR services in DeltOCR Bench to identify their accuracy levels in different document types: The full names of the above products and their versions in use as of November 2025 are listed…

Enterprise Software
Insight
Aug 21

Quantum Annealing: Practical Quantum Computing

Quantum annealing is a promising quantum technology for companies with urgent optimization problems that traditional computers cannot solve quickly. It can be used to solve optimization problems more effectively than traditional computers. However, it is still mostly used in academia, and more R&D is required to build commercial quantum annealers. There are different approaches to…

Agentic AI
Benchmark
Aug 11

Top Agent Harnesses: Claude Code vs Codex

Agent harnesses serve as the production runtime for AI agents, with design choices that create performance variation across identical underlying models. We benchmarked 17 agent harnesses across 10 coding tasks. To isolate the harness rather than the model, we ran every agentic CLI on a single foundation model, Claude Sonnet 4.6 (non-reasoning), and AI code…

AI
Open World Evaluation
Jul 29

Top 8 Open Source AI Coding Agents

In prior evaluations, we benchmarked both open-source and proprietary Agentic CLIs, focusing on their performance in web development tasks, and some open-source agents performed as successfully as the paid options. Therefore, we also listed the top open-source coding agents for users with privacy concerns. For methodology, see the AI coding benchmark. For more details about…