Abraheem Rashid

Founder · London

Neura-X

Digitalisation with AI

A research-grounded AI venture I founded to build practical frameworks at the intersection of applied AI and enterprise digitalisation.

New

Neura-X is now operating in London

We have officially started operations in the United Kingdom. Working from London puts us close to some of the strongest AI research ecosystems in Europe and to the enterprises we most want to work with. New plans, new frameworks, and new partnerships are on the way, more details coming soon.

The story

Alongside my research, I founded Neura-X, a venture focused on building practical AI frameworks at the intersection of applied AI and enterprise digitalisation. Drawing on hands-on experience from Curium and INK AI, Neura-X develops scalable solutions using frontier AI technologies such as retrieval-augmented generation, agentic pipelines, efficient transformers, and trustworthy ML systems. Our work is deliberately research-grounded: every framework and deployment is shaped by the same rigour that drives my academic publications.

How we work

Research-First Engineering

Every engagement starts from a hypothesis, not a template. We build production systems the same way we build publishable research: reproducible, benchmarked, and honest about failure modes.

Frameworks, Not One-Off Builds

The proprietary frameworks we develop across projects, on RAG orchestration, federated pipelines, and cost-aware LLM routing, compound over time. Every client benefits from what came before.

Enterprise-Ready From Day One

Trustworthy ML, privacy-preserving architectures, and observability are not afterthoughts. They are baked in from the first sprint so the system you ship is the system you can defend.

Where we go deep

Agentic & LLM Systems

Production-grade RAG, multi-agent orchestration, fine-tuning (LoRA/QLoRA), and quantised inference.

Computer Vision & Perception

Industrial monitoring, multi-sensor calibration, and real-time CV pipelines built for edge deployment.

Trustworthy ML

Federated learning, privacy-preserving pipelines, and explainability evaluation under real-world drift.

Work with us

We are selective about the engagements we take on. If you are building something at the frontier of applied AI, agentic systems, or trustworthy ML, and you want a team that treats every project like a research contribution, get in touch.