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...

• Updated Apr 28, 2026
• TypeScript

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.

• Updated Apr 28, 2026

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.

• Updated Apr 17, 2026
• Python

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.

• Updated Apr 17, 2026

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.

• Updated Apr 28, 2026
• Jupyter Notebook

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.

• Updated Apr 28, 2026

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...

• Updated Apr 28, 2026
• Python

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.

• Updated Apr 14, 2026
• Jupyter Notebook

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...

• Updated Apr 28, 2026
• Jupyter Notebook

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.

• Updated Apr 28, 2026

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...

• Updated Apr 14, 2026
• Jupyter Notebook

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.

• Updated Apr 28, 2026
• Jupyter Notebook

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.

• Updated Apr 17, 2026

The team developed an automated Work Breakdown Structure generator that converts narrative project scope documents into structured, standardised schedules. Using defined activity standards and sample enterprise schedule data, the solution demonstrates how unstructured text can be transformed into consistent WBS elements with activities, duration...

• Updated Apr 14, 2026

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.

• Updated Apr 28, 2026

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.

• Updated Apr 17, 2026

Delivery Confidence Radar built an early‐warning Delivery Confidence Radar that integrates activity and capacity data to surface instability, pressure and likely slippage before dates move. The solution emphasises explainable signals and a clear ‘what’s at risk, why, and where to intervene’ structure suitable for planners and senior lead...

• Updated Apr 28, 2026
• HTML

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.

• Updated Apr 17, 2026

The team explored persona‐driven behavioural analytics to address risky resource planning practices. By combining detailed persona definitions, behavioural metrics, and deep analysis of forecasting and utilisation data, they designed a dashboard concept that highlights over‐optimistic planning, generic resource use, and weak feedback loops,...

• Updated Apr 14, 2026
• HTML

The team built Jim‐E, an interactive AI‐assisted risk review tool that applies SME heuristics to project risk entries. Using a lightweight Streamlit interface and encoded heuristic rules, the solution helps users identify weak risks and mitigations, capture structured feedback, and generate clear audit‐ready reports.

• Updated Apr 14, 2026
• Python