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.

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.

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.

The team designed a context-aware Lessons SME Agent that builds on an existing Lessons Library to deliver targeted, actionable insights from historic MOD Gateway Reviews. Their work shows how semantic retrieval and persona-driven prompts can surface the most relevant lessons and recommended actions for different roles and project phases.

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.

The team built an automated Lessons Learned Library that extracts recommendations and insights from historic MOD Gateway Review reports and turns them into a structured, searchable knowledge base. The solution combines document parsing, NLP categorisation, AI summarisation, and Power BI reporting to surface relevant lessons at project start-up a...

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.