AI Platform Engineering
AI inside the media platform you already run, from discovery to archive.
We engineer AI into the media platform you already run: recommendations that open up the whole catalogue, tagging and archive search by what is said or shown, and subtitles, summaries and clips that wait for an editor before they publish.
Each feature is wired into the asset management, publishing and playback systems you already run, and every release is tested against your own titles before a viewer sees it.
the interview where the founder talks about the first factory
Episode four: the first factory
Said in chapter three
Raw interview, unedited
Found in the transcript
Archive reel, the factory opening
Factory seen on screen
Podcast with the same founder
Another conversation, same guest
A viewer's or an editor's sentence finds the moment in the catalogue or the archive, from the transcript, the people your team has named and what is on screen.
Answers from your catalogue, metadata and subtitles, and only offers what a viewer can watch where they are.
The founder walks the empty factory floor at dawn. Cut from chapter three, captioned and ready for social.
Summaries, chapters, clips and subtitles are drafted from the episode and wait for an editor before they publish.
Ranking, tagging and subtitle changes are checked against your own titles before viewers see them, and the last good release is one step back.
The pieces we build most often. Each one connects to your catalogue, asset library, rights records and player, and each one is judged on your own titles.
Rows, rails and “because you watched” shelves built from viewing behaviour and catalogue metadata, balancing new releases with the back catalogue, under rules your programming team can read and override.
Home screens, row order and artwork that adapt to each viewer, device and time of day, inside the editorial slots, promotions and availability windows your team controls.
Scenes, people, objects, topics, mood and spoken keywords tagged from the picture, sound and script, written into your own metadata schema and checked by your librarians where it matters.
Search footage, audio and print across the whole archive by what is said or shown: a quote, a person your team has named, a place or a scene, landing on the moment rather than the file.
Synopses, chapter markers, highlight clips and social cut-downs drafted from the episode in your house style, waiting in an editor's queue rather than going straight out.
Transcripts, subtitles and translated tracks timed to the cut, with synthetic voices only where the talent and the contract allow, and a linguist or editor reviewing every language before it goes live.
Uploads, thumbnails, live chat and comments screened against your community rules. Clear cases are handled as they arrive; borderline ones go to a moderator with the reason shown.
Territory, window, music and talent clearances checked against your rights records before anything publishes, with age ratings and advertiser-safety signals, so a clip or a dubbed track that is not cleared is held.
A viewer assistant that answers “what was that film where…” from your catalogue, and an editorial copilot over your archive, style guide and rights records, with every source one click away.
Answer engines
AI assistants and answer engines now reply to “what should I watch tonight?” with a summary rather than a list of links. What they say about your titles depends on what they can read, and on what you let them quote.
We make a catalogue legible on your terms: structured metadata and schema for every title, clear licensing signals, an MCP server over the catalogue and its availability, and the rules that decide what an assistant may quote, summarise or link.
Most media platforms start with one feature on one service or one desk. We build it inside your stack, prove it on your catalogue and hand it to your team.
A short readiness sprint in your catalogue, metadata, viewing data and rights records to choose the first feature and agree how it will be judged.
Engineers work in your repositories and your cloud, wiring the feature into the asset management, publishing and playback systems you already run.
We test on your own titles and archive before launch, then release to a share of viewers or to one editorial desk and watch the measures you chose, with a rollback ready.
Runbooks, dashboards and a trained team. You own the code, the prompts, the tag schema and the evaluation set; we can stay on to run it if you want.
Tell us the platform you run and the feature you have in mind, and we will come back with a first view of how we would build it.