hack25-risk-review-regulator/repo-manifest.json at main · Projecting-Success-Solutions-Portal/hack25-risk-review-regulator · GitHub

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{
  "event": {
    "name": "hack25",
    "slug": "hack25",
    "repo": "hack25",
    "topics": [
      "solution-centre",
      "hack25",
      "github",
      "microsoft-azure",
      "power-platform",
      "python",
      "hackathon",
      "innovation",
      "data",
      "artificial-intelligence",
      "collaboration",
      "prototyping",
      "challenge1",
      "large-language-models",
      "natural-language-processing",
      "project-assurance",
      "automation",
      "evidence-management",
      "assurance",
      "llm"
    ],
    "technologies": [
      "GitHub",
      "Microsoft Azure",
      "Power Platform",
      "Python",
      "Large Language Models",
      "Natural Language Processing",
      "HTML",
      "JavaScript",
      "D3.js",
      "Microsoft Copilot",
      "Microsoft Excel",
      "Power Query",
      "CSV",
      "Data Analysis",
      "Prompt Engineering",
      "JSON",
      "Power BI",
      "ChatGPT",
      "Word Documents",
      "Ollama",
      "DeepSeek-R1",
      "LangChain",
      "Streamlit",
      "Tesseract OCR",
      "Agentic AI",
      "Email Automation",
      "Data Visualisation",
      "Data Analytics",
      "Presentation",
      "Video"
    ]
  },
  "visibility": {
    "event_repo": "public",
    "team_repos": "public"
  },
  "repos": [
    {
      "type": "team",
      "challenge_name": "Risk Register Regulator: Agentic Review",
      "challenge_description": "This challenge focuses on improving the effectiveness of project risk management by using agentic AI to automatically review risk registers, identify quality issues and opportunities, and prompt action. Teams are invited to design a prototype that applies AI personas to assess risk data, generate tailored and actionable feedback, and issue automated email nudges to relevant stakeholders. The approach aims to create a closed\u2011loop system that improves risk data quality, drives timely mitigation activity, and visualises change over time, enabling organisations to demonstrate tangible return on investment from automated risk assurance.",
      "challenge_slug": "challenge3",
      "team_name": "Risk Review Regulator",
      "team_slug": "a",
      "name": "hack25-risk-review-regulator",
      "child_repo_path": "submissions/hack25-challenge3-a",
      "url": "https://github.com/Projecting-Success-Solutions-Portal/hack25-risk-review-regulator.git",
      "description": "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\u2011centred email nudges. The solution demonstrates a closed\u2011loop risk\u2011management cycle spanning project, portfolio, and enterprise views.",
      "key_outcomes": "Expected to improve risk\u2011register data completeness, reduce overdue mitigation actions, and increase engagement with risk owners through targeted nudges, leading to measurable reductions in residual risk exposure and time\u2011to\u2011action.",
      "important_files": [
        {
          "path": "Prompt Persona Responses/AgenticAI Role Profile - Cruise Control.docx",
          "purpose": "Defines the Risk Review Regulator persona responsible for converting AI findings into targeted, actionable email nudges."
        },
        {
          "path": "Prompt Persona Responses/Portfolio Owner - Enterprise Level Risk Review.docx",
          "purpose": "Example portfolio\u2011level agentic review summarising exposure, data quality, trends, and priority actions."
        },
        {
          "path": "Prompt Persona Responses/Project Manager - Project 066 \u2013 Risk Management Report (full Lifecycle).docx",
          "purpose": "Project\u2011level agentic risk review illustrating tailored insights and prioritised actions for a Project Manager."
        }
      ],
      "required_fields": {
        "summary": "An agentic AI risk\u2011register regulator that reviews data, generates insights, and nudges stakeholders to act.",
        "problem": "Risk registers often degrade in quality and fail to trigger timely action, reducing their value as a management tool.",
        "approach": "Apply multiple AI personas to analyse risk registers, tailor insights by role, and issue targeted email nudges while tracking response and impact.",
        "deliverables": "Defined agentic personas, role\u2011specific risk review reports, draft nudge emails, and supporting analytics for ROI and maturity tracking."
      },
      "thumbnail_path": "",
      "topics": [
        "solution-centre",
        "hack25",
        "challenge3",
        "large-language-models",
        "agentic-ai",
        "email-automation",
        "data-analytics",
        "power-bi",
        "risk-management",
        "risk-register",
        "assurance",
        "automation",
        "behavioural-nudges"
      ],
      "technologies": [
        "Large Language Models",
        "Agentic AI",
        "Email Automation",
        "Data Analytics",
        "Power BI"
      ],
      "members": []
    }
  ]
}