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ShipSage is an AI-powered DevOps readiness analyzer and pipeline generator that transforms how teams prepare repositories for production deployment. The core problem: every new project requires manual setup of Docker, CI/CD, monitoring, Kubernetes, and infrastructure configurations. Existing generators create files blindly without telling teams what is actually missing or what still needs review. ShipSage fills this gap. How it works: 1. Repository Intelligence — Analyzes any public GitHub repository to detect language, framework, project type, and critical files automatically. 2. Readiness Scoring — Scores production readiness using weighted DevOps signals including tests, CI/CD, Docker, documentation, monitoring, security, and infrastructure-as-code. 3. Starter Asset Generation — Generates ready-to-use Dockerfile, Docker Compose, Kubernetes manifests, CI/CD pipelines, AWS Terraform, ELK monitoring stack, and environment configurations. 4. AI Codebase Analysis — Provides detailed architecture summaries and module breakdowns describing every file and directory in the repository. 5. AWS Cost Estimation — Estimates monthly cloud deployment costs with per-service breakdowns. 6. Interactive Q&A — Users can ask natural-language questions about the repository and receive context-aware answers grounded in actual file contents. ShipSage runs entirely in a free rule-based mode for demos, with optional IBM Watsonx Granite integration for deeper AI-powered analysis. Built with Python, FastAPI, and a modern dark-themed dashboard UI. Developed using IBM Bob IDE across three structured sessions covering architecture, feature building, and submission preparation. Live Demo: https://shipsage.onrender.com GitHub: https://github.com/AbhishekKharat04/repo-sage
17 May 2026