The Automated Metadata Indexing and Analysis (AMIA) project aime to provide an effectve digital asset management(DAM) tool for large digital asset databases.We began with text-based indexing since it is still the most reliadle approacch as compared with other content-based media features.AMIA not only searches for the text of the file nname,but also utillizes embedded information such as the metadata in MAYA files.The AMIA system builds a linked map between all dependency files.We present an approach of preserving previously established metadata created by the old DAM toois,such as AlienBrein,and integrating them into the new system.Findings indicate that AMIA has significantly improved search performancre comparing to previous DAM tools.Finally,the ongoing and future work in the AMIA project is described.