RIO Co‑lab built the RIO Co‑lab, a multi‑agent risk‑register analysis and visualisation solution that applies specialist AI agents to identify themes, assess data quality, summarise change, and surface actionable insights across project and portfolio risk registers.

FutureFlo delivered FutureFlo, a data‑quality‑led schedule forecasting solution that combines structured data cleansing, feature analysis and Power BI visualisation to highlight drivers of project slippage and forecast future delivery risk.

Local RAG Assurance Engine delivered a fully local, offline-capable assurance analysis engine using retrieval‑augmented generation (RAG) to identify and surface evidence from project documentation and return structured, machine‑readable outputs.

ProCost built ProCost, a Power Apps and Power BI prototype for intelligent cost management that integrates actuals, forecasts and requisition data to provide scalable, modular cost visibility across the project lifecycle.

Risky presented a concept prototype focused on applying agentic AI to proactively interrogate risk registers and surface actionable insights for regulators and delivery teams, emphasising clarity of narrative and decision support.

WBS Cost Estimation Tool developed a desktop‑based Work Breakdown Structure (WBS) and Cost Breakdown Structure (CBS) estimation tool that supports structured cost entry, versioned change tracking, and comparison of estimates against actuals across the project lifecycle.

MoD Assurance Assessment Build delivered a data-driven assurance assessment build that automates evaluation of project documents against GovS 002 criteria, producing structured ratings, scores, and commentary at scale.

Forecast Input Cost App delivered a Power Apps and Power BI based cost‑forecasting solution that enables controlled forecast entry, integrates actual spend data, and provides clear visibility of cost performance against estimates across projects.

PEAT Document Assessment System developed an interactive assurance evidence assessment solution that applies large language models to analyse project documentation, score maturity, and surface assurance evidence and gaps aligned to recognised governance frameworks.

Project Overrun Predictor built a machine‑learning driven schedule‑forecasting prototype that predicts the likelihood of project overruns by analysing feature trends across completed and in‑progress energy projects, supported by an interactive Streamlit application.

TerraCast developed TerraCast, a machine‑learning based forecasting approach that combines data quality checks, classification, and regression models to predict schedule delay risk and likely lateness across energy projects, supported by dashboard‑ready outputs.

Evidence Query Assistant demonstrated a lightweight AI-assisted evidence query approach using ChatGPT to interrogate assurance documents against defined criteria and return clear, traceable answers identifying where evidence exists or is missing.

Hack25 is a collaborative hackathon-style event focused on rapid experimentation, problem-solving and practical innovation across data, AI and modern digital tooling. Teams explore defined challenges, prototype solutions and share learnings within a short, delivery‑driven format.

Team 1B applied structured prompt engineering with Microsoft Copilot to automate assurance evidence identification and scoring across multiple personas, aligned to PEAT success criteria.

Risk Review Regulator designed a set of agentic AI personas to automatically review risk registers, analyse data quality and exposure, and drive action through targeted, human‑centred email nudges. The solution demonstrates a closed‑loop risk‑management cycle spanning project, portfolio, and enterprise views.

CutVac Risk Cleaner implemented a Python‑based risk‑register processing and feedback pipeline that cleans, validates and analyses risk and mitigation data, then generates automated, insight‑driven email prompts to drive corrective action.

AI PEAT Evidence Tool developed an AI-assisted PEAT-style evidence assessment tool that uses structured prompts to extract assurance evidence from project documents, apply RAG ratings, and generate auditable JSON outputs for reporting and dashboards.

Integrated Cost Data Platform delivered an end‑to‑end cost management architecture that migrates fragmented Excel‑based cost data into a structured PostgreSQL database and exposes a single, trusted cost model to Power BI for analysis across estimation and execution.