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NatwarUpadhyay/agentic-ai-project-delivery-risk-engine

Multi-agent AI system for pre-execution project delivery risk assessment with executive reporting.

MIT GitHub ↗
★ 0
stars
75
AI relevance
50
solo dev
0
tool sigs

SUMMARY AI summary by gpt-5-mini

Agentic AI Project Delivery Risk Assessment Engine is a multi-agent, dependency-aware risk assessment app built in AWS PartyRock to evaluate IT project delivery risk before execution. Intended users: IT services firms, consultancies, PMOs, delivery managers, AI teams and project managers. It takes three inputs (project description, team size, timeline) and produces boardroom-ready outputs: project summary, risk register with probability/impact scoring, risk heat map, project health score, success probability, mitigation plan, and executive report. Architecture: an orchestrator plus six specialized agents (project understanding, risk identification, probability & impact, mitigation planning, resource/timeline assessment, executive reporting) supporting parallel workstreams and dependency joins. Demonstrates traceability, auditability, and structured governance-ready reporting; sample results include a 30-item risk register and health score. Future extensions cover simulations, tool integrations, exports, and role-based dashboards.

DETECTED Detected AI stack

AI-related keywords found in this repo's description, topics, or README summary — grouped by category. Each badge links to the corresponding ranking detail page.

☁️ Cloud platforms (1)
AWS

Why this is classified AI-related

The AI relevance score checks four places for AI keywords and adds the weight of each one that matches. Full methodology

Repository name no match
Description +25 matched: ai
GitHub topics no match
README head +20 (derived from the score — README text is not stored)

Total AI relevance score: 75 / 100

Owner

Account
NatwarUpadhyay
Type
User
Followers
2

👋 Hi! I'm Natwar Upadhyay, an aspiring AI Consultant dedicated to leveraging cutting-edge technology to drive impactful projects in the field of AI.

Dates

Created on GitHub 2026-05-30
Last push 2026-05-30
First seen here 2026-05-30
Last fetched 2026-08-19 16:21