Sena Sezer
Research interests
Sena’s research focuses on emerging AI architectures and enterprise AI infrastructure, particularly in the following areas:
Agentic web architectures
AI memory systems
MCP
Chatbots and ChatGPT
Multi-factor authentication (MFA)
Her work explores how autonomous AI agents interact with web environments, how memory layers enhance contextual reasoning, and how AI systems can be securely deployed and governed within enterprise environments. She is particularly interested in the intersection of AI orchestration, system control, and security frameworks.
Sena is part of the AIMultiple benchmark team. She is working with the AIMultiple tech team to formulate an MFT, IGA benchmark that includes top MFT software providers.
Professional experience
Sena has over 3 years of experience as a technical marketer in e-commerce, where she focused on SEO strategy, product positioning, and data-driven content optimization. She has hands-on experience improving search rankings, enhancing site performance, and aligning technical product specifications with customer expectations.
In addition to her marketing background, she has experience in software development and website design, combining technical execution with user-centered thinking. Her cross-functional background enables her to bridge technical analysis with business impact effectively.
Education
Latest Articles from Sena
Best Appen Alternatives in 2026 for Workers & Customers
We analyzed the top Appen alternatives by comparing worker review ratings from Trustpilot, crowd size, payment schedules, and publicly available company data. The alternatives differ significantly depending on what you need from Appen. Browse by role: Workers or contributors. Customers or buyers who rely on data from Appen. Appen alternatives for workers AlternativesWorker ratings*Payment schedule**Pricing…
Generative AI in Retail: 7 Use Cases & Examples
Retail businesses strive to enhance customer experiences and loyalty. This requires producing attractive content in various formats, effective marketing efforts, and exceptional customer service. With generative AI, retailers can address most of these issues through automation, particularly by enhancing their ability to analyze customer data to deliver more personalized experiences. See the examples and benefits…
The Future of Large Language Models
See the future of large language models by delving into promising approaches, such as self-training, fact-checking, and sparse expertise that could address LLM limitations. Success rate comparison of LLM’s Claude Sonnet 4.6 led the benchmark with an overall score of 0.748, with base and thinking variants tied to three decimal places. Claude Opus 4.8 (0.702),…
10 SOAR Use Cases with Real-World Workflow Examples
Generic SOAR use cases rarely hold up in practice; the right automation depends entirely on your environment, alert volumes, and how your SOC is structured. The use cases below are tailored to specific scenarios and include step-by-step workflow breakdowns. The workflows below reflect the traditional SOAR model; agentic platforms run many of these same cases…
Top 6 Open Source Sensitive Data Discovery Tools
The following tools are selected based on GitHub activity and sorted by GitHub star count in descending order. They cover the main use cases for sensitive data discovery: metadata cataloging with lineage, agentless scanning, and API-based detection of PII, PCI data, and credentials at rest. One thing worth being upfront about before the list: these…
Top 50 Deep Learning Use Case & Case Studies
Deep learning uses artificial neural networks to learn from data. When trained on large, high-quality datasets, it achieves high accuracy, making it valuable wherever you have abundant data and need accurate predictions. Below are real deep learning applications across industries and business functions, with concrete examples. What are the capabilities & technologies enabled by deep…
20+ AI Agent Builders: Microsoft, CrewAI, LangGraph and More
After reviewing the documentation and spending several hours testing these AI agent builders, we compiled a list of the best open-source frameworks and low-code/no-code platforms. To demonstrate AI agent builder use cases, we provided a tutorial on building a product-expert agent with CrewAI. Low-code/no-code platforms Low-code/no-code platforms with prebuilt tools are best for enterprise workflow…
Top Cloud Object Storage Tools: Results & Comparison
We tested five cloud object storage providers IONOS, Amazon S3, Backblaze B2, Cloudflare R2, and DigitalOcean Space across performance, features, and pricing. All tests ran from Europe against each provider’s EU-region endpoint. Cloud Object Storage Benchmark Results Upload Throughput (MB/s): higher is better Provider100 KB1 MB10 MB1 GB IONOS1.819.1619.3370.64 AWS S3326.52 65.7777.92 Backblaze B20.7217.515.8923.54 Cloudflare…
Top 13 Use Cases of Generative AI in Education
According to the OECD Digital Education Outlook, 57% of lower secondary teachers state that AI helps them create or improve lesson plans.68Used with a clear teaching purpose, generative AI technologies can improve learning and support skills such as critical thinking, creativity, and collaboration. Explore the top 13 use cases to learn how generative AI can…
Synthetic Users Explained: Top 7 AI User Research Tools
Traditional user research takes weeks: recruiting participants, scheduling sessions, and manually coding transcripts. Synthetic user platforms compress that timeline to hours by generating AI-driven personas you can interview, survey, and test against without the logistics. After evaluating 10+ AI research platforms and reviewing independent validation studies, we found that the most practical use case is…
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