MarchlandLabs
Contact R&D
Advanced AI & Neural Topologies R&D

Pioneering Next-Gen
AI Memory & Graph Architecture

Marchland Labs builds core foundational systems spanning self-organising spatial graph databases, secure Graph RAG frameworks, and high-efficiency small language models (SLMs) tailored for specialized edge execution.

Lead Researcher: Matthew Beddoes
Direct Contact: matthew@business-analytica.com
Partner: UK Cybersecurity Testing

Current Research Initiatives

Self-Organising Graph (SOG)

Developing dynamic spatial graph databases combining Euclidean geometry and cosine similarity for adaptive AI memory across 2D and 3D network architectures.

Graph RAG AI

Enhancing retrieval-augmented generation using structured graph topologies instead of flat vector indexes to eliminate context hallucination in enterprise setups.

Topology Optimisation

Small Language Models (SLMs)

Optimizing compact, specialized language models engineered for high-efficiency local execution, ensuring absolute enterprise privacy and zero cloud token leakage.

Edge Execution Focus

Secure AI & Data Engines

Building hardened multi-agent architectures capable of multi-step reasoning, backed by defensive validation checks against prompt injection and data poisoning.

Defensive AI Frameworks

Computer Vision & Object Recognition

Researching advanced visual processing pipelines and structural recognition paradigms to map complex visual parameters into machine-readable vector states.

Visual Intelligence

Adaptive State Chatbots

Designing conversational systems driven by real-time state tracking and reinforcement feedback mechanisms for highly contextual dialogue systems.

Dynamic Dialogues

Ecosystem Collaboration

Marchland Labs operates as an independent R&D node collaborating with specialized advisory and security testing entities across the UK network.