We present MicrostructureDB, a new platform that demonstrates how AI can enhance metallurgical data analysis and laboratory management. This beta release introduces practical tools for automating common challenges in materials characterization: identifying experimental anomalies, filling missing data, and finding related samples across datasets. The platform includes an integrated metallurgical AI assistant that helps researchers interpret results and maintain consistent documentation standards. Using our curated steel microstructure collection, we demonstrate how these tools can streamline laboratory workflows, improve data quality, and accelerate the analysis of experimental results. Through practical examples, we showcase the platform's capabilities in enhancing materials research while maintaining rigorous scientific standards, illustrating the potential of AI-assisted materials characterization.