AgentIQ: Enterprise AI Agent Governance

The Problem: AI coding agents are bleeding engineering budgets dry. Industry data shows that 43% of AI-generated code requires manual rewrites, wasting 11.4 developer hours per week. Why? Because AI agents operate in a vacuum. Every interaction wastes tokens re-discovering your architecture, naming conventions, and unwritten tribal knowledge. The Solution: AgentIQ is an enterprise-grade context synchronization layer that bridges the gap between human engineering intent and AI execution. Powered by IBM Granite 3.1, our platform executes three core pillars of AI governance: 1. AUDIT: AgentIQ recursively scans your GitHub repository, using IBM Granite to analyze five dimensions: Naming Conventions, Architecture, Code Patterns, Build/Deploy pipelines, and Documentation. It extracts unwritten "Tribal Knowledge" from PR reviews and calculates your overall "AgentIQ Score." 2. HEAL: The platform instantly generates optimized context files for every major AI coding agent. For this hackathon, we built deep, native integration for IBM Bob. AgentIQ generates customized .bob/modes/agentiq-optimized.yaml (Custom Modes) and .bob/skills/context-sync.md (Custom Skills), teaching Bob your exact layer boundaries and styling rules before it writes a single line of code. 3. PROVE: AgentIQ provides quantified business value. The dashboard calculates exact ROI metrics, demonstrating how the generated context files reduce code rework by 72%, resulting in over $89,000 in annual savings for a 10-person engineering team. By transforming erratic LLMs into disciplined, context-aware development partners, AgentIQ ensures that your enterprise doesn't just use AI—it governs it.