Projects

MHIL

Concept & Early Prototyping (TRL-5)
Semi-Stealth • Non‑Profit
  • Non-profit research institute developing rigorous benchmarks and evaluation methodologies for real machine intelligence beyond narrow LLM tasks.
  • Designs human-aligned test batteries assessing critical agent capabilities including memory, adaptive planning, robustness, and autonomous problem-solving under uncertainty.
  • Produces open evaluation matrices facilitating standardized comparisons across diverse AI models, vendors, and system architectures.
  • Focuses on future-ready intelligence standards featuring reproducible scorecards, capability tiering, and safety-critical thresholds for responsible real-world deployment.

MazeByte

SOTA Proof of Concept (PoC)
Semi-Stealth
  • Research project pioneering fully autonomous AI agents that self-manage end-to-end ETL pipelines without human intervention.
  • Employs infant-inspired feedback mechanisms based on reward and pain signals, alongside resource-seeking and self-preservation behaviour to enable adaptive learning.
  • Generates modular pseudo-code implementing memory, search, optimisation, and orchestration functionalities essential for continuous data pipeline automation.
  • Built around the proprietary MBI internal model aiming to replace manual data engineering with resilient agent-driven automation.

SightBit

SaaS (TRL-9)
Public
  • Production-grade computer vision platform delivering real-time detection for drowning prediction, human and vessel identification, and flood-risk monitoring.
  • Operates exclusively on standard CCTV video streams, eliminating the need for specialised sensors, edge computing devices, or per-site calibration.
  • Incorporates a panoptic segmentation deep learning model enhanced with a proprietary augmentation pipeline, significantly improving small-object recall rates by 18 percentage points.

AdaptiveBridge

Production-ready (TRL-8)
Public • Open-Source
  • Open-source Python library designed to ensure machine learning model robustness against missing features during inference in real-world production.
  • Predicts and imputes absent features dynamically, preserving model accuracy and stability.
  • Supports configurable thresholds for feature importance, correlation, and accuracy metrics, alongside custom accuracy logic and automated feature distribution handling.
  • Provides a drop-in estimator interface enabling seamless integration with existing ML pipelines via fit-transform workflows.
  • Manages complex feature dependencies including mandatory, deviation-aware, and leveled feature types to optimise predictive performance.

Jhive

Production (TRL-7)
Public • AIforGood
  • Django-based web application leveraging OpenAI's API for real-time detection and analysis of antisemitic content.
  • Implements robust content classification workflows paired with a detailed reporting interface for thorough review and operational transparency.
  • Exposes RESTful API endpoints with integrated rate limiting to support scalable integration.
  • Enforces strict input validation and sanitisation protocols to mitigate injection and security risks, ensuring safe, reliable deployment for sensitive content moderation scenarios.