Built by Engineers Focused on Production
RetrieveIQ was created to help teams move retrieval-based AI systems from fragile pilots to production-ready deployments.
RetrieveIQ was founded on a simple belief: most AI systems fail in production not because of the model, but because retrieval, data pipelines, and evaluation aren’t engineered properly.
[ Our mission ]
Help teams build retrieval-augmented AI systems that are
[ Our Vision ]
The future we’re building
We believe the next generation of AI systems will be judged not by demos, but by reliability, governance, and real-world performance. Our goal is to help teams meet those standards.
Years of AI and automation experience
From Experiments to Production-Ready AI
Arsalan is an Edinburgh-based AI Engineer focused on building and fixing production RAG and ETL pipelines. He holds an MEng in Electronics and Computer Science from the University of Edinburgh, with a background spanning machine learning, data systems, and applied AI engineering.
He has worked extensively on document-heavy AI systems in LegalTech environments, where retrieval quality, latency, and correctness are critical. His experience includes diagnosing chunking and indexing issues, improving retrieval relevance, and reducing hallucinations caused by missing or poorly surfaced context.
RetrieveIQ was founded to help teams move from fragile proofs-of-concept to AI systems that are observable, testable, and safe to deploy at scale.
Ready to Start Your AI Project?
Book a quick call or message us with an enquiry, either way you will be a step closer to bringing your product closer to deployment.
