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.

NDA Harm Evidence Explorer built a policy-facing web application that turns anonymised survey data and survivor testimonies into clear, judge-ready evidence of NDA-linked harm. The solution surfaces patterns across sectors, regions and reporting paths, and generates concise narratives that policymakers can reuse in consultation and briefing mate...

SpeakOutIQ built SpeakOutIQ, a policy decision‑support platform that combines statistical analysis with an interactive dashboard and optional locally hosted AI to translate NDA misuse evidence into clear, policy‑ready insights. The solution is designed to help campaigners and legislators explore harm, reporting behaviour and sector patterns...

The team developed a scalable Lessons Library pipeline that ingests historic MOD Gateway Review documents and converts them into a large, structured lessons dataset. Their solution focuses on high‑volume extraction, semantic classification, and sentiment analysis to rapidly surface reusable lessons for assurance and organisational learning.

Evidence Engine built Evidence Engine, a web‑based Assumption Assurance platform that captures project assumptions, links them to evidence, and highlights drift through confidence scoring and visual alerts. The solution focuses on making assumptions explicit, traceable and continuously reviewed rather than static entries in documentation.

Early Slip Predictor focused on identifying early indicators of delivery slippage by analysing capacity pressure and task behaviour across work centres. Using simple machine‑learning techniques and clear capacity metrics, the team demonstrated how likely future slip can be predicted early and translated into understandable risk signals.

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.

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.

Assumption Drift Canvas focused on collaboratively mapping how critical assumptions emerge, drift and impact delivery confidence across projects. Using a shared visual workspace, the team structured the logic linking assumptions, confidence, external signals and portfolio‑level assurance to support earlier, clearer decision‑making.

The team built a rule‑driven risk assessment system that converts SME survey responses into structured, validated heuristics. Using LLMs, fuzzy matching, and human‑in‑the‑loop review, they generate, deduplicate, and govern high‑quality risk and mitigation rules that can be applied consistently across risk registers.

The team focused on standardising the capture and reporting of lessons learned from MOD Gateway Reviews by creating a structured lessons dataset and Power BI ingestion flow. Their work demonstrates how consistent data schemas, Microsoft Forms, and Power BI automation can turn assurance outputs into a repeatable, analysable Lessons Library.

Project:Hack27 is a community hackathon bringing teams together to design, pitch and judge practical solutions across six defined challenges, with a focus on innovation, clear value and real‑world impact.

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.

The team focused on establishing strong data quality and analytical foundations for a Project Health and Behaviour Monitor. Using a structured synthetic dataset, they demonstrated how task-level schedule, cost, and resource attributes can be cleaned, validated, and analysed to identify volatility, critical path risk, forecasting accuracy issues,...

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.

HCD Action Console built a full Human‑Centric Data Action Console combining secure data capture, analytics APIs and role‑based dashboards to monitor team wellbeing and performance during the Hackathon. The solution supports both a portfolio view for organisers and a team‑level view for participants, with optional AI‑assisted insight gene...

Forecast Insight Canvas focused on collaboratively mapping the drivers of forecast fade and reframing them into a clear, executive‑ready decision journey. Using a shared visual workspace, the team structured how Programme Directors can move from raw supply chain data to confidence, explanation and action when committing spend.

The team produced a data‑driven risk heuristics analysis pipeline that combines Python analytics with large language model feedback to assess and enrich existing risk registers. Using Jupyter notebooks, they analyse risk and mitigation data, apply SME heuristics via an LLM, and output annotated spreadsheets and summary datasets designed for do...

Sector Risk Lens developed a sector‑level risk analysis that translates NDA misuse and reporting failures into clear, policy‑relevant signals. Using survey data and interpretable modelling, the team highlights where harmful behaviours concentrate and frames results in plain language suitable for non‑technical decision‑makers.

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.