
*ArchSentinel* is an AI-powered multi-agent code review and architectural analysis platform designed to address the growing challenges of slow, inconsistent, and shallow software code reviews. In modern development teams, Pull Requests and large codebases often require significant senior-engineer effort, while important security vulnerabilities, performance bottlenecks, logical errors, edge cases, and architectural inconsistencies can still be overlooked. ArchSentinel addresses this problem by introducing an intelligent review pipeline in which a *Master Agent* orchestrates multiple specialized AI agents that independently analyze the submitted code from different engineering perspectives. The *Security Agent* focuses on security risks and unsafe coding patterns, the *Performance Agent* examines inefficient operations and complexity-related issues, and the *Logic & Edge-Case Agent* evaluates correctness, error handling, boundary conditions, and potential logical defects. Their results are then passed to a *Review Synthesis Engine, which consolidates the findings into a structured, actionable engineering review containing severity, confidence, evidence, impact, file and line references, and recommendations. Developers can interact with ArchSentinel either by providing a GitHub repository or by directly pasting source code, while the dashboard provides real-time visibility into the review pipeline through Server-Sent Events (SSE), allowing users to observe repository ingestion, agent execution, parallel analysis, synthesis, and completion. The primary target users are software developers, engineering teams, security teams, code reviewers, and organizations seeking faster and more consistent code-quality analysis. What makes ArchSentinel unique is its **multi-agent specialization and parallel review architecture, rather than depending on a single generic AI prompt; each agent approaches the same code from a different engineering perspective, while the synthesis layer creates one unified review. The platform was developed using an AI-assisted workflow with **IBM Bob*, which supported implementation, debugging, refinement, and integration while the development process remained focused on architecture, testing, validation, and engineering decisions. By combining AI reasoning, specialized review agents, structured validation, repository analysis, and real-time execution visibility, ArchSentinel aims to transform code review from a primarily manual and reactive process into a more intelligent, observable, and actionable engineering workflow.
27 Sep 2026