Wasabi AiR launches AI-powered media storage to boost efficiency

Wasabi Technologies has launched Wasabi AiR, an artificial intelligence-enabled media storage platform aimed at organisations managing large volumes of unstructured data.

Wasabi AiR is designed for industries such as media and entertainment, healthcare, education, and sport, offering storage and automatic analysis of digital content. The new solution combines Wasabi's object storage capabilities with AI-powered metadata auto-tagging and speech-to-text transcription that supports multiple languages.

According to the company, video files uploaded to Wasabi AiR are analysed automatically, generating a second-by-second metadata index to aid quick and accurate retrieval. One of the notable aspects of Wasabi AiR is that users pay only for storage, not for the use of AI features.

Automated indexing in action

Organisations relying on manual methods to categorise and search through large content archives could see productivity gains. Liverpool Football Club has taken part in the beta-testing phase of Wasabi AiR, using it to tag videos and classify players and logos. This integration of AI is intended to allow the club's staff to assemble and produce new content more efficiently.

Drew Crisp, Senior Vice-President of Digital at Liverpool Football Club, commented on the practical impact:

"Wasabi AiR significantly reduces our manual efforts due to its seamless use of AI recognition technology to identify, organise and categorise files. At the club we handle extensive media content, and so this enhanced efficiency could really help us to locate specific content quickly and accurately within our archive, and create new content streams quickly, empowering our creativity and innovation. Wasabi AiR transcends mere storage; it will become another key to unlocking the full potential of our content."

The rollout of Wasabi AiR follows Wasabi's earlier acquisition of Curio AI, a platform engineered to analyse and index large video libraries. Features in the new product include facial recognition, searchable speech-to-text, multilingual translation, speaker recognition, optical text recognition, logo identification, and recognition of sounds.

Applications and capabilities

Wasabi AiR is positioned for scenarios such as post-production, facilitating easy assembly of video segments for news packages and social media content. It is also suitable for sponsorship and marketing analysis, as it can automatically detect and index logos within video footage for return-on-investment purposes. Additionally, the platform supports tailoring content for geographically diverse audiences through its multilingual transcription and indexing.

The AI-enabled features are designed to give structure to video archives that have traditionally been stored on tapes or in other formats where content is not easily searchable. Wasabi stated that previously 'dead' content stored on tapes can become accessible and create new opportunities for monetisation and engagement when uploaded to Wasabi AiR.

Dave McCarthy, Research Vice President at IDC, provided perspective on the broader context:

"Wasabi AiR introduces a groundbreaking solution to a persistent 25-year-old challenge, combining AI-driven search capabilities with high-performance cloud storage. This marks a transformative shift in media management, offering efficiency and accessibility for businesses dealing with massive unstructured data." According to Dave McCarthy, Research Vice President at IDC, "Wasabi AiR represents a significant advancement in tackling the longstanding issue of managing extensive data archives, within a substantial market for intelligent media storage solutions."

Metadata and searchability

David Friend, co-founder and Chief Executive Officer of Wasabi Technologies, outlined the rationale for the product:

"Why move to the cloud if you still can't find anything? Object storage without metadata is like a library without a catalog. Wasabi AiR works right out of the box and it's as simple to use as popular search engines. For example, if it finds a face that it doesn't recognise, it asks 'Who is this?' Using a simple UI, the user can train their own models. You can have tens of thousands of hours of video, and Wasabi AiR will take you right to the moment you are looking for. And you can search as much as you want – we only charge for the storage."

Pricing, security and data ownership

Wasabi said the platform adopts a capacity-based pricing model with no additional fees for AI operations, data egress, or programming integration requests, positioning their pricing as up to 80% lower than some competitors. The company states that customers retain exclusive ownership of both their original files and generated metadata. Wasabi also confirmed that customer data is not used for training models accessible by others and that files and metadata are protected using their security measures, including immutable storage and multi-user authentication to guard against ransomware and accidental deletions.

Wasabi AiR is aimed at improving efficiency for media organisations and others with large content libraries, supporting their search and production workflows with AI-based features linked closely to cloud storage capacity rather than data processing costs.