Strawberry Media Intelligence
Projective
projective.io/strawberry-media-intelligence
Category Streaming
Strawberry Media Intelligence is Projective’s answer to the biggest problem in AI for post: most tools sit adjacent to the workflow, forcing teams to connect every piece of the pipeline to a separate AI engine. We designed Media Intelligence to live where the media lives, not as another silo to wire up.
Built into Strawberry’s existing Production Asset Management (PAM) toolset, it runs in the background as content lands on existing storage and delivers visual search, automated transcription with speaker labelling, shot detection and multilingual discovery across active projects and archives. Users prompt in natural language, (e.g. “close‑up of cyclist at sunset with brand logo” or “all soundbites from the producer in interview B”) and get precise timecode ranges back in seconds.
Results flow natively into Adobe Premiere Pro, After Effects, Illustrator, DaVinci Resolve and Media Composer as subclips with handles, SRT captions or structured queries. There are no connectors to maintain, no recall‑from‑archive delays and no cloud egress costs to tap petabytes of indexed data. Visual search runs on existing hardware, on‑premises, with a coherent project structure and permissions model so AI never exposes assets a user shouldn’t see.
WHAT MAKES THIS AI TOOL SPECIAL/UNIQUE?
Most AI implementations in post and broadcast create a new connectivity problem. A typical facility might have an Isilon with five years of content, a NEXIS for current work, and another tier for offline or social editing, then try bolting an AI tool on to track changes across those silos. That “AI to the left of your workload” pattern means constant reconfiguration, fragile integrations and metadata that never quite matches reality.
Strawberry Media Intelligence fundamentally fixes this. Because the Strawberry PAM already unifies the facility’s disparate storage pools, the AI isn't a bolted-on afterthought: it is native, systematic, and works on a complete dataset. It indexes content silently in the background on existing hardware, eliminating the need to connect storage silos. Furthermore, it inherits Strawberry’s existing project framework and access controls, ensuring users only see search results for media they are explicitly permitted to view.
All your content—video, audio, graphics, stills and images—is in one coherent, controlled environment, instantly queryable across active projects and deep archives.
WOULD THESE FEATURES BE POSSIBLE WITHOUT AI?
Rushes never get tagged, so traditional metadata is worthless for repurposing raw footage. Transcriptions can be done, but the usual approach from the creative applications is piecemeal, and the results of the transcription have no value to the broader production. Shot detection, object/brand/text spotting, scene understanding, plus speaker‑aware transcription across 100+ languages, require models that can generalise beyond human‑defined taxonomies. Strawberry's project framework takes these technologies and makes them work for the creative user.
IMPACT ON OUR CLIENTS: EFFICIENCIES, CREATIVE BENEFITS, SPEED
By collapsing years of rushes, current projects and archives into one index, we remove the “hunt and assemble” tax that dominates post. Typical outcomes include: 30‑second savings per asset multiplying into hours per day across teams; editors jumping straight to the exact shot instead of scrubbing long files; colour and VFX artists reusing known looks found by visual similarity; and sound teams locating speech segments by speaker without manual logs. Because indexing happens in the background on existing hardware, clients gain AI capability without CapEx or new server racks. Archives become revenue‑generating material again, with no egress fees and no waiting for restores.
HOW IS THE AI TRAINED?
Strawberry’s models are pre‑trained for broad media understanding (shots, objects, text in frame, actions, mood) and then adapted through continuous, on‑prem indexing of each facility’s library. Speaker labelling and custom vocabularies improve as users search and confirm results, keeping sensitive content on‑site while still benefiting from large‑model capability. The unified permissions model ensures that search respects project access controls, so AI never exposes assets a user shouldn’t see.
WHY STRAWBERRY MEDIA INTELLIGENCE STANDS OUT AS AN AI TOOL
Strawberry Media Intelligence delivers end‑user capabilities that fully utilise AI—natural‑language visual search, speaker‑aware transcription, cross‑application subclip creation—while removing the integration overhead that usually cancels out AI’s gains. For global teams and partners, that means faster turnarounds, lower operational waste and a repeatable pattern for scaling post without scaling chaos.
