IronClaw Agent Findings Visualization

The IronClaw agent feature is now accessible via UI buttons on project and analysis pages, deployed from commit e383323, with full functionality including chat, findings, and GDPR features. It is production-ready and live for user interaction. IronClaw Agent Feature relies on PostgreSQL database with 6 new tables created to function correctly. IronClaw Agent Feature uses FastAPI for backend API implementation including asynchronous generators. IronClaw Agent Feature was verified and validated by the comprehensive E2E test suite. IronClaw Agent Feature deployment depends on Coolify for container build and deployment orchestration. E2E test suite tests IronClaw Agent Feature for functionality and stability. IronClaw Agent Feature integrates with Datalens platform for agent-driven data analysis. LocalAgentClient is used by IronClaw Agent Feature to maintain session state across API calls. IronClaw Agent uses IronClawClient to connect and send messages to the remote IronClaw service. IronClaw Agent uses FindingsGenerator to generate findings from query results including handling PostgreSQL Decimal types. IronClaw Agent falls back to using LocalAgentClient when IronClaw environment variables are missing, resulting in local message processing and inability to complete queries successfully. IronClaw Agent requires IronClaw database to be configured and operational to persist sessions and support agent session creation. IronClaw Agent depends on QuestionRouter.route() to route queries and execute them correctly as part of the async processing pipeline. IronClaw Agent Findings Visualization uses the Live Backend to process and visualize data.