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Hazal Şimşek

Hazal Şimşek

Industry Analyst
78 Articles
Stay up-to-date on B2B Tech

Hazal is an industry analyst at AIMultiple.

Research interests

Hazal focuses on

  • process intelligence including process mining
  • enterprise automation including IT automation and low-code no-code (LCNC) automation

Professional interests

She has experience as a quantitative market researcher and data analyst in the fintech industry.

Education

Hazal received her master's degree from the University of Carlos III of Madrid and her bachelor's degree from Bilkent University.

Latest Articles from Hazal

Agentic AIJan 27

Top 10+ Agentic Orchestration Frameworks & Tools in 2026

We benchmarked four major agentic frameworks using an identical five-agent travel-planning workflow and consistent LLM settings. Each framework was executed 100 times, and we measured pipeline latency, token usage, agent-to-agent transitions, and the agent-to-tool execution gap to isolate true orchestration overhead. Agentic orchestration benchmark All frameworks successfully completed the task across 100 run each.

AIJan 27

LLM Orchestration in 2026: Top 12 frameworks and 10 gateways

Running multiple LLMs at the same time can be costly and slow if not managed efficiently. Optimizing LLM orchestration is key to improving performance while keeping resource use under control.

Enterprise SoftwareJan 27

Top 44 Process Mining Use Cases & Applications in 2026

Latest process mining trends and stats show that 93% of business leaders aim to leverage a process intelligence software like process mining since these tools enabled process improvement by 23%, digital transformation by 25% and automation by 25%.Process mining offers a variety of use cases beyond these broad application.

Enterprise SoftwareJan 26

Compare Top 15+ Production Planning Tools by Features in 2026

While examining the production planning tools market, we found that much of the available information is outdated, failing to reflect the latest advancements and deployment options. To provide a clearer view, the market can be categorized into key segments: Note that the rating data is gathered from top B2B user review websites.

AIJan 23

AI Compliance in 2026: Top 6 Challenges & Real-Life Failures

The rise in artificial intelligence (AI) usage is prompting new laws and ethical standards. South Korea recently became the first nation to fully enforce a comprehensive, standalone AI law. Because of these rapid shifts, 77% of companies view AI compliance as a top priority.

AIJan 23

Top 20 AI GRC Software & Technologies in 2026

As AI systems integrate into business processes, organizations face growing AI governance, risk, and compliance needs. In our prior research, we tested AI risks in practice with an AI bias benchmark, finding persistent bias around race, gender, and socioeconomic assumptions in several models.

AIJan 22

Benchmark of 30 Finance LLMs in 2026: GPT-5, Gemini 2.5 Pro & more

Large language models (LLMs) are transforming finance by automating complex tasks such as risk assessment, fraud detection, customer support, and financial analysis. Benchmarking finance LLM can help identify the most reliable and effective solutions.

Enterprise SoftwareJan 22

3 Types of EBS Migration: Best practices & Key Benefits in 2026

Oracle EBS is a well-known suite of business applications that was released by Oracle Corporation in 2001 to manage and automate various business processes. The term “Oracle EBS migration” describes the Oracle EBS migration procedure. This migration could consist of the following types:  Oracle EBS migration refers to the migration process for Oracle EBS.

AIJan 14

Compare Top 20 LLM Security Tools & Free Frameworks in 2026

Chevrolet of Watsonville, a car dealership, introduced a ChatGPT-based chatbot on their website. However, the chatbot falsely advertised a car for $1, potentially leading to legal consequences and resulting in a substantial bill for Chevrolet. Incidents like these highlight the importance of implementing security measures to LLM applications.

AIJan 12

Benchmark of 16 Best Open Source Embedding Models for RAG

Most embedding benchmarks measure semantic similarity. We measured correctness. We tested 16 open-source models, from 23M-parameter to 8B-parameter embeddings, on 490,000 Amazon product reviews, scoring each by whether it retrieved the right product review through exact ASIN matching, not just topically similar documents.