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hack26

overview

hack26 is a collaborative hackathon-style event focused on rapidly exploring and prototyping practical data and AI solutions against a defined set of challenges. Teams work within clear challenge boundaries to test ideas, build proof‑of‑concepts and share learning in a short, intensive format.

Please be aware that this content was generated follwing an automated review so may not be perfectly accurate; refer to the original challenge brief and team files for authoritative information

topics

solution-centre, hack26, python, azure, power-bi, github, hackathon, innovation, data, artificial-intelligence, prototyping, collaboration, challenge1, large-language-models, machine-learning, natural-language-processing, risk-management, tacit-knowledge, heuristics, project-risk

technologies used

python, azure, power-bi, github, large-language-models, machine-learning, natural-language-processing, streamlit, reportlab, pandas, microsoft-excel, dataverse, power-apps, power-automate, copilot-studio, jupyter, google-gemini, openpyxl, fuzzywuzzy, json, microsoft-copilot, office-365, project-scheduling-tools, microsoft-office, primavera-p6, document-analysis, knowledge-bases, search, pdfplumber, sentence-transformers

challenges

challenge brief topics technologies
Risk Insight Ignition: Making Tacit Knowledge Tangible This challenge, presented by Thales, focuses on improving project risk management by capturing and applying subject matter expert (SME) heuristics that are typically tacit and inconsistently recorded. Teams explore how large language models and related AI techniques can codify SME insight, apply it to existing risk registers, and enhance the quality, consistency and usefulness of risk identification and mitigation data, with an emphasis on learning and refinement through expert feedback. solution-centre, hack26, challenge1, large-language-models, machine-learning, natural-language-processing, risk-management, tacit-knowledge, heuristics, project-risk, data-quality, artificial-intelligence, python, streamlit, reportlab, pandas, human-in-the-loop, microsoft-excel, dataverse, power-apps large-language-models, machine-learning, natural-language-processing, python, streamlit, reportlab, pandas, microsoft-excel, dataverse, power-apps, power-automate, copilot-studio, power-bi, jupyter, google-gemini, openpyxl, fuzzywuzzy, json
Automated WBS AutoPlan: From Narrative to Project Schedule This challenge, presented by EDF, focuses on automating the creation of project schedules from unstructured scope documents and narratives. Teams explore how large language models and related AI techniques can read narrative project descriptions and generate consistent, structured Work Breakdown Structures (WBS) with activities, milestones, durations, and logical dependencies, reducing manual effort, improving consistency, and enabling earlier visibility of delivery risks within secure enterprise environments. solution-centre, hack26, challenge2, large-language-models, natural-language-processing, microsoft-copilot, office-365, project-scheduling-tools, project-scheduling, work-breakdown-structure, automation, project-controls, data-quality, artificial-intelligence, microsoft-office, primavera-p6 large-language-models, natural-language-processing, microsoft-copilot, office-365, project-scheduling-tools, microsoft-office, primavera-p6
Ghosts of Projects Past This challenge, presented by the MOD, focuses on preventing repeated delivery failures by unlocking lessons hidden in historic project assurance artefacts, particularly Gateway reviews. Teams explore how large language models and related AI techniques can automatically extract both explicit and implicit lessons, organise them into a structured and searchable Lessons Library, and make them reusable at project start‑up and review stages to strengthen learning and assurance across portfolios. solution-centre, hack26, challenge4, large-language-models, natural-language-processing, document-analysis, knowledge-bases, search, lessons-learned, project-assurance, knowledge-management, governance, data-quality, artificial-intelligence, python, pdfplumber, sentence-transformers, hugging-face, power-bi, openpyxl large-language-models, natural-language-processing, document-analysis, knowledge-bases, search, python, pdfplumber, sentence-transformers, hugging-face, power-bi, openpyxl, watchdog, pymupdf, textblob, pandas, openai, vector-databases, retrieval-augmented-generation, microsoft-copilot, power-automate, microsoft-forms, csv, excel
Risky Resource Routines: Pinpointing Patterns for Preventing Poor Practices This challenge, presented by Thales, focuses on improving project delivery by exposing and addressing poor resource planning and scheduling behaviours. Teams are invited to design behavioural analytics dashboards or tools that reveal hidden patterns in forecasting accuracy, resource over‑ and under‑utilisation, and reliance on generic placeholders, turning planning data into insight that drives better decisions and sustainable behaviour change. solution-centre, hack26, challenge5, analytics-dashboards, data-visualisation, large-language-models, machine-learning, enterprise-data-platforms, resource-management, schedule-forecasting, behavioural-analytics, project-controls, data-quality, artificial-intelligence, power-bi, analytics, microsoft-copilot, python, pandas, jupyter analytics-dashboards, data-visualisation, large-language-models, machine-learning, enterprise-data-platforms, power-bi, analytics, microsoft-copilot, python, pandas, jupyter, data-analysis, data-profiling, visualisation, streamlit

team repos

challenge team path repo topics technologies
Risk Insight Ignition: Making Tacit Knowledge Tangible Jim-E submissions/hack26-challenge1-a hack26-jim-e solution-centre, hack26, challenge1, python, streamlit, reportlab, pandas, large-language-models, risk-management, heuristics, tacit-knowledge, data-quality, project-risk, human-in-the-loop python, streamlit, reportlab, pandas, large-language-models
Risk Insight Ignition: Making Tacit Knowledge Tangible AI Risk Evaluator submissions/hack26-challenge1-b hack26-ai-risk-evaluator solution-centre, hack26, challenge1, microsoft-excel, dataverse, power-apps, power-automate, copilot-studio, power-bi, large-language-models, risk-management, heuristics, tacit-knowledge, data-quality, project-risk, decision-support, analytics microsoft-excel, dataverse, power-apps, power-automate, copilot-studio, power-bi, large-language-models
Risk Insight Ignition: Making Tacit Knowledge Tangible Risk Hacktory submissions/hack26-challenge1-c hack26-risk-hacktory solution-centre, hack26, challenge1, python, pandas, jupyter, google-gemini, openpyxl, power-bi, risk-management, heuristics, data-analysis, large-language-models, data-quality, project-risk, analytics, automation python, pandas, jupyter, google-gemini, openpyxl, power-bi
Risk Insight Ignition: Making Tacit Knowledge Tangible Risk Assessment Rule Management System submissions/hack26-challenge1-d hack26-risk-REDACTED solution-centre, hack26, challenge1, python, jupyter, fuzzywuzzy, json, large-language-models, risk-management, heuristics, rule-engine, data-quality, governance, human-in-the-loop python, jupyter, fuzzywuzzy, json, large-language-models
Automated WBS AutoPlan: From Narrative to Project Schedule AutoPlan WBS Generator submissions/hack26-challenge2-a hack26-autoplan-wbs-generator solution-centre, hack26, challenge2, natural-language-processing, project-scheduling-tools, microsoft-office, primavera-p6, project-scheduling, work-breakdown-structure, automation, project-controls, data-quality natural-language-processing, project-scheduling-tools, microsoft-office, primavera-p6
Ghosts of Projects Past Ghost Busters submissions/hack26-challenge4-a hack26-ghost-busters solution-centre, hack26, challenge4, python, pdfplumber, sentence-transformers, hugging-face, power-bi, openpyxl, watchdog, lessons-learned, project-assurance, knowledge-management, document-analysis, search, governance, data-quality python, pdfplumber, sentence-transformers, hugging-face, power-bi, openpyxl, watchdog
Ghosts of Projects Past Lessons Library Builder submissions/hack26-challenge4-b hack26-lessons-library-builder solution-centre, hack26, challenge4, python, pymupdf, sentence-transformers, textblob, pandas, openai, openpyxl, lessons-learned, project-assurance, knowledge-management, document-analysis, sentiment-analysis, data-quality python, pymupdf, sentence-transformers, textblob, pandas, openai, openpyxl
Ghosts of Projects Past Lessons SME Agent submissions/hack26-challenge4-d hack26-lessons-sme-agent solution-centre, hack26, challenge4, python, sentence-transformers, vector-databases, retrieval-augmented-generation, large-language-models, microsoft-copilot, lessons-learned, project-assurance, knowledge-management, semantic-search, decision-support, governance python, sentence-transformers, vector-databases, retrieval-augmented-generation, large-language-models, microsoft-copilot
Ghosts of Projects Past Lessons Intake & Power BI Flow submissions/hack26-challenge4-e hack26-lessons-intake-power-bi-flow solution-centre, hack26, challenge4, power-bi, power-automate, microsoft-forms, csv, excel, lessons-learned, project-assurance, knowledge-management, data-standardisation, reporting, governance power-bi, power-automate, microsoft-forms, csv, excel
Risky Resource Routines: Pinpointing Patterns for Preventing Poor Practices Resource Behaviour Monitor submissions/hack26-challenge5-a hack26-resource-behaviour-monitor solution-centre, hack26, challenge5, power-bi, data-visualisation, analytics, enterprise-data-platforms, resource-management, schedule-forecasting, behavioural-analytics, project-controls, data-quality, analytics-dashboards power-bi, data-visualisation, analytics, enterprise-data-platforms
Risky Resource Routines: Pinpointing Patterns for Preventing Poor Practices Resource Behaviour Insights submissions/hack26-challenge5-b hack26-resource-behaviour-insights solution-centre, hack26, challenge5, power-bi, microsoft-copilot, data-visualisation, analytics, enterprise-data-platforms, resource-management, schedule-forecasting, behavioural-analytics, project-controls, data-quality power-bi, microsoft-copilot, data-visualisation, analytics, enterprise-data-platforms
Risky Resource Routines: Pinpointing Patterns for Preventing Poor Practices Project Health and Behaviour Monitor submissions/hack26-challenge5-c hack26-project-health-and-behaviour-monitor solution-centre, hack26, challenge5, python, pandas, jupyter, data-analysis, analytics, resource-management, schedule-forecasting, behavioural-analytics, data-quality, project-controls python, pandas, jupyter, data-analysis, analytics
Risky Resource Routines: Pinpointing Patterns for Preventing Poor Practices Behavioural Planning Insights submissions/hack26-challenge5-e hack26-behavioural-planning-insights solution-centre, hack26, challenge5, python, pandas, analytics, data-profiling, visualisation, resource-management, schedule-forecasting, behavioural-analytics, data-visualisation, project-controls, data-quality python, pandas, analytics, data-profiling, visualisation
Risky Resource Routines: Pinpointing Patterns for Preventing Poor Practices Forecast Force submissions/hack26-challenge5-f hack26-forecast-force solution-centre, hack26, challenge5, python, pandas, jupyter, analytics, data-visualisation, resource-management, schedule-forecasting, behavioural-analytics, project-controls, data-quality python, pandas, jupyter, analytics, data-visualisation
Risky Resource Routines: Pinpointing Patterns for Preventing Poor Practices PRISM submissions/hack26-challenge5-g hack26-prism solution-centre, hack26, challenge5, python, streamlit, pandas, analytics, machine-learning, data-visualisation, resource-management, schedule-forecasting, behavioural-analytics, project-controls, data-quality python, streamlit, pandas, analytics, machine-learning, data-visualisation

About

hack26 is a collaborative hackathon-style event focused on rapidly exploring and prototyping practical data and AI solutions against a defined set of challenges. Teams work within clear challenge boundaries to test ideas, build proof‑of‑concepts and share learning in a short, intensive format.

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