MEDIA & ENTERTAINMENT
AI for Media and Entertainment
Personalization, smarter content operations and audience insight, with rights and creators protected.
We help media, entertainment and content companies in the US and Australia use AI across the content lifecycle, from tagging and localization to recommendations and audience analytics.
More Content, More Channels, Tighter Budgets.
Audiences expect content that fits their tastes, in their language, on every device. Meanwhile, content libraries grow faster than teams can tag, translate and package them.
Generative AI opens new creative and production options, but it also raises real questions about rights, provenance and the use of people’s likeness.
The winners will use AI to scale content operations and understand audiences, with clear controls that protect creators and content.
Untagged Libraries
Content is hard to search and reuse.
Slow Localization
Subtitles and translations take too long.
Audience Churn
Viewers leave when content does not fit.
Rights Risk
AI use raises rights and likeness questions.
Our Media and Entertainment AI Services
Content Personalization
Recommendation engines that help each viewer, listener or reader find content they will enjoy.
Automatic Tagging and Search
AI that tags video, audio, images and text so teams and audiences can find content fast.
AI-Assisted Localization
Subtitling, translation and dubbing support that speeds up global releases, with human review.
Audience Analytics
Insight and predictive models for engagement, retention and churn.
Generative Production Tools
AI tools for scripting, editing and asset creation, with clear controls on rights and provenance, built with our AI and generative AI team.
Not sure where AI fits in your content operation?
In a 30-minute call we’ll look at your workflows and tell you honestly where AI can help.
Practical AI, Real Workflows
How We Use AI in Media and Entertainment
We use AI to scale content operations and understand audiences, while editors, producers and creators stay in control of what is published.
Common use cases include:
- Recommending content based on viewing, listening and reading behavior
- Tagging and indexing large video, audio and image libraries
- Generating subtitles, translations and transcripts for review
- Summarizing content for metadata, trailers and promotion
- Predicting engagement and churn to guide programming decisions
- Detecting unauthorized copies of premium content
We start with one high-impact workflow, prove the results, then scale across your catalog.
What We Aim to Improve
What Your Organization Gains
The outcomes we design for from day one, tracked against the measures we agree with you.
Higher engagement
Content that fits each audience.
Easier discovery
Libraries that are easy to search.
Faster global reach
Quicker localization.
Time back for teams
Less manual tagging and editing.
Protected rights
Clear controls on AI use.
Better decisions
Insight from audience data.
Our Process
A clear path from first use case to AI across your content lifecycle, as part of a wider digital transformation where needed.
1. Discover
We review your content, workflows, platforms and audience data.
2. Prioritize
We rank use cases by value, effort and rights considerations.
3. Pilot
We test on a defined catalog or workflow with real users.
4. Scale
We roll out across your library, channels and teams.
5. Measure and Improve
We track engagement and efficiency, and keep improving.
Have a content challenge in mind?
Bring it to a 30-minute call and leave with a clear next step.
Who We Work With
We partner with organizations that create, manage and distribute content. We work with:
- Streaming services and broadcasters
- Publishers and digital media companies
- Music, gaming and entertainment businesses
- Marketing and production studios
Work with us the way that suits you: start with a fixed-scope pilot, move to a wider program, or add data and AI engineers through our staff augmentation and consulting model.
Technology and Platforms
We integrate with your content platforms and add AI where it helps.
Media Asset Management
MAM and DAM systems for video, audio and images
Streaming and Delivery
Streaming platforms and content delivery networks
Recommendation Engines
Personalization and recommendation models
Speech and Translation
Speech-to-text, translation and voice models
AI Models
OpenAI, Anthropic, Google and open-source models
Audience Data
Analytics, data warehouses and customer data platforms
Cloud Platforms
AWS, Microsoft Azure, Google Cloud
Rights, Security and Responsible AI
Content is your most valuable asset, so we build protection for rights, creators and audiences into every solution. Your teams make the final call.
- Rights awareness: AI use respects licensing, contracts and talent agreements.
- Provenance: we support content provenance standards such as C2PA where relevant.
- Likeness and consent: voice and likeness tools are used only with clear permission.
- Content security: premium content is protected with access controls and monitoring.
- Human review: editors approve AI-generated subtitles, metadata and assets before release.
- Audience privacy: viewer data is protected in line with privacy laws in the US and the Privacy Act in Australia.
Frequently Asked Questions
How much does a media AI project cost?
It depends on the use case, catalog size and platforms involved. Most clients start with a fixed-price pilot, then scale. We’ll give you a clear estimate after the discovery call.
How long before we see results?
A focused pilot on one workflow or part of your catalog usually comes first, so you see results early. We agree timelines up front.
Can AI tag our existing content library?
Yes. AI can tag video, audio, images and text at scale, with people reviewing results to keep metadata accurate.
How accurate is AI translation and subtitling?
Quality is high for many languages, but we always include human review before release, especially for creative content.
How do you handle rights and likeness?
We build rights checks, consent and provenance into the workflow, and avoid using voices or likenesses without permission.
Can you improve our recommendations?
Yes. We build and tune recommendation models on your audience data, and measure the impact on engagement.
Do you work with companies in Australia?
Yes. We work with clients in the United States and Australia.
What happens on the AI Discovery Call?
It’s a 30-minute conversation about your goals and current content operations. We’ll suggest where to start, outline next steps and answer your questions. There’s no obligation.
Ready to Put AI to Work for Your Content?
Book a 30-minute call with our team. We’ll review your content operations and show you where AI will make the biggest difference.