eMAM is a media asset management platform that provides an online proxy library of digital content with powerful tools accessible from any web browser, Android tablet, or iPad. eMAM is packaged for different applications. EMAM Vault for archiving, eMAM Publish for social media and VOD, eMAM Workgroup, eMAM Enterprise and eMAM Online (a SaaS (software offering where Empress manages the software and the storage: customers pay only for their use of the system).

ARCHITECTURE: eMAM can be installed on-premise, in the cloud, or hybrid. There is no mention of multi-site support. It has a Service Oriented Architecture (SOA) and any number of servers can be clustered to provide the processing power required. eMAM supports RESTful and SOAP APIs. No mention of underlying technology (database used etc), nor security.

INTEGRATION: eMAM has a large list of third party resource integrations, spanning archives, cloud, newsroom computer systems, editing, online video platforms, accelerated file transfer, AI (Amazon, Google, IBM and Microsoft), and storage (on-prem and cloud). No mention of a plugin approach or support for integration through scripting is mentioned.

AUTOMATION: While eMAM marketing refers to multiple workflows, it appears that these are all hard coded - “We can implement middleware and adapters with all your other systems for a seamless integrated workflow solution”. There is no mention of a graphical workflow design tool, nor of real-time workflow status monitoring. Workflows available include live capture and logging, automated AI video analysis, collaborative editing, Avid Media Composer and Interplay workflow.

METADATA: eMAM supports an Admin widget that includes functionality for managing metadata structures for various asset types (video, audio, images and other). Metadata fields can be added (limited to 8 different types) to schemas with group level permissions and asset set. Dublin Core metadata structure is supported as standard. Tags can be added and managed. No mention of more complex metadata (taxonomies, thesaurus, hierarchies).

USER EXPERIENCE: eMAM user interfaces are modern in style, seem intuitive, but maybe too simplistic. They are widget-based, enabling different widgets to be presented, arranged and sized for different users. Media can be managed by categories, projects, or tags.

ANALYTICS: eMAM includes a Site Analytics tab in the Admin Tools, which includes selecting the feature to analyse (external approvals, archived assets, delivery, report by asset type ec), date range selection, chart type (line, column, pie, pyramid, area) charts and tables on different areas of system performance. It is not clear if asset or user audit trails are supported.

ARTIFICIAL INTELLIGENCE: eMAM integrates with AI partners Amazon, Google, IBM, and Microsoft to generate facial recognition from video and photos, speech-to-text, annotations and sentiment metadata adding value to media. There is no mention of using this metadata for anything other than improved search.