I design and build AI and data systems that turn complex information into actionable intelligence.

My work sits at the intersection of AI engineering, data, research, and real-world applications. I have worked across research organizations, government/statistics, industry, startups, and international collaborative projects, often bringing together technical teams and domain experts to develop practical AI solutions.

My current interests include Generative AI, LLMs, RAG systems, AI architecture, AI strategy, data platforms, multilingual NLP, and AI for complex societal and industrial challenges.

• Retrieval-Augmented Generation (RAG)
• Hybrid retrieval and semantic search
• Embeddings and vector search
• LLM application architecture
• Information extraction and summarization
• LLM evaluation
• Multilingual NLP
• AI-assisted decision support

I have designed and deployed multiple RAG systems using modern LLM and cloud technologies.

I am particularly interested in designing AI systems end-to-end:

Data Sources
     ↓
Data Ingestion
     ↓
Processing & Enrichment
     ↓
Search / Retrieval
     ↓
AI / ML / LLM
     ↓
Evaluation
     ↓
API / Application
     ↓
Monitoring & Improvement

My focus is on how data, models, infrastructure, people, and domain knowledge come together to create useful AI systems.

I have worked on AI and data applications involving:

• Social sciences
• Food safety
• Food security
• Climate and environmental risks
• Biodiversity
• Consumer behaviour
• Government and public-sector applications
• Scientific research
• Multilingual information analysis

I particularly enjoy working with domain experts who understand a problem deeply but are not necessarily AI specialists, and translating their needs into technically feasible solutions.

Led the development of the ECO-Ready Observatory, bringing together data, analytics, and AI approaches to support analysis of food-system resilience and emerging risks.

Led work packages in the Horizon Europe EFRA project, focusing on data and AI approaches for identifying, analysing, and communicating emerging food risks.

Designed and deployed several retrieval-augmented generation systems involving:

• Document processing
• Embeddings
• Hybrid retrieval
• Vector search
• LLM orchestration
• Retrieval evaluation
• Cloud-based deployment

CTO & Co-founder

Building AI and data solutions for understanding consumers, food systems, emerging trends, and risks.

My work involves translating emerging AI capabilities into practical products and collaborating with technical and domain teams.

My research background is in Computational Linguistics and multilingual Natural Language Processing, including information extraction, text classification, language resources, and large-scale text analysis.

I hold:

• PhD in Computational Linguistics — Radboud University
• MSc in Cognitive Science
• BSc in Computer Engineering

My research has involved NLP, machine learning, information extraction, multilingual text processing, evaluation, and large-scale language datasets.

I have also organized and contributed to international NLP workshops, shared tasks, benchmarks, and evaluation activities.

LLMs · RAG · NLP · Machine Learning · Embeddings · Information Retrieval · Information Extraction

Python · Git · Docker · APIs · Data Engineering

AWS · Amazon Bedrock · Cloud-based AI Systems

Vector Search · Hybrid Retrieval · Semantic Search · LLM Evaluation · AI Architecture

I enjoy working at the intersection of technology and domain expertise.

My experience across different disciplines has taught me that successful AI projects are rarely only about choosing the right model. They require understanding:

• What problem actually needs to be solved
• What data is available
• How domain knowledge can be incorporated
• Which AI approach is appropriate
• How the system should be evaluated
• How it can be integrated into existing workflows
• How people will use and trust the result

I therefore tend to approach AI projects from both technical and strategic perspectives.

• Generative AI
• AI Agents & AI Applications
• Retrieval-Augmented Generation
• AI Architecture
• AI Strategy & Innovation
• Responsible AI
• AI Evaluation
• Data Platforms
• Multilingual AI
• AI for Science
• AI for Government
• Food Systems Intelligence
• Climate & Environmental Intelligence

• LinkedIn: Ali Hürriyetoğlu
• Website: hurrial.com
• ORCID: 0000-0003-3003-1783
• Google Scholar: Research

Building AI systems that connect data, intelligence, and domain expertise to solve real-world problems.