Media & Entertainment
AI-native engineering for Media & Entertainment
Content costs are rising, churn is hard to contain and audiences expect to find what they want in seconds. We have spent years building the platforms underneath broadcast and streaming, and we now put AI to work across them: in discovery, in metadata and in live production.
Merapar has worked across much of the media value chain: metadata and content discovery, recommendations and personalisation, identity, set-top-box diagnostics, and the operational tooling that keeps it all running, for broadcasters, operators and streaming services in the UK, Belgium, Greece and the US.
AWS audited that depth and awarded Merapar the Media & Entertainment Services Competency, which is granted on demonstrated delivery in this sector rather than on volume of spend.
That depth is why our AI work holds up. Recommendation engines and content discovery are not side projects here. They are systems we have been building and running in production for years.
What we do for media and entertainment
Six areas where we design, build and run the platforms behind live and on-demand services.
Media Supply Chain
We design and implement scalable, cloud-based media supply chains to automate content processing, from ingestion to delivery.
Content Management
We enable centralised content management, ensuring seamless metadata enrichment, version control, and asset distribution across platforms.
Content Search, Discovery & Recommendations
We leverage AI and ML to enhance content discovery and improve personalised recommendations.
Distribution Platforms
We build flexible, cloud-based or hybrid distribution solutions for live and on-demand content across OTT, broadcast, and social platforms.
Dynamic Ad Insertion (DAI)
We enable seamless ad insertion workflows, supporting server-side (SSAI) and client-side (CSAI) solutions to maximise ad revenue.
Customer Data Platforms
We help media companies leverage first-party data for deeper audience insights, targeted advertising, and personalised content experiences.
Where AI already works in media
Four places we put AI into media platforms, each backed by a client case or by something we have built.
Recommendations and personalisation
Recommendation engines on Amazon Personalize for streaming services and public broadcasters, tuned to lift viewing while keeping the cost of serving them under control.
The PBS caseSemantic search and discovery
Search by meaning instead of by title, so a viewer can ask for “a feel-good film with a dog” by voice or text and get an answer. Built on vector search and AI-driven metadata extraction.
How semantic search worksMetadata enrichment
Provider metadata enriched with extra information and images automatically, so catalogues are complete enough for discovery and recommendations to work at all.
The cable operator caseAI-assisted shot logging
Multimodal foundation models on Amazon Bedrock draft the shot log from live sports video, so loggers validate a draft instead of scrubbing footage frame by frame.
See shot logging
The Future of TCO 2025
Our 38-page report with Accedo, for technology and business leaders, on why OTT has fallen behind adjacent industries and what closing the gap involves. Its argument in four lines:
TCO is a living system, a continuous loop between data, architecture and experience, not a one-off CapEx and OpEx trade-off.
AI orchestration is a platform layer. Agents that optimise journeys and triage operational issues move churn, ARPU and lifetime value.
Composability is strategic. Services that can be swapped, scaled or upgraded independently let a platform move in weeks rather than quarters.
Fragmented data comes first. Without one view of users, content and performance, AI on top is guesswork.
No registration required.
Built and running, in media
Recommendations, discovery, metadata and platform migration, for broadcasters and operators with real audiences.
CaseMedia recommendations engine for NBCUniversal’s Hayu
Read the case
CaseAmazon Personalize optimisations for PBS
Read the case
CaseSpeaking through the cloud: RTS’s award-winning digital transformation
Read the case
CaseDigital UK/Freeview reinvented for the cloud
Read the case
CaseMetadata enrichment for a large cable operator
Read the case- Product
AI-assisted shot logging for live sports
See the product 
CaseSet-top box diagnostics for Wind Vision
Read the case
Clients we have worked with
Further reading and listening
PodcastEpisode 10: Total TV: From Linear and Digital to One TV Business
Robert Farazin (tvbeat) and Johan Liljelund (DanAds) on how broadcasters can move beyond fragmented linear and digital advertising.
About the episode
BlogWhy You Need an Automated Media Supply Chain
Learn how automated media supply chains can prevent broadcasting crises by ensuring reliable, on-time content delivery. Discover the future of media workflows with smart, connected solutions.
Read the post- Podcast
Episode 6: Getting up close and personal with AWS Personalize
A deep dive into the role AWS Personalize plays in helping organisations achieve the ultimate customer viewing experience.
About the episode 
BlogA cloud strategy talk with Kevin Savina of AWS
AWS’s Kevin Savina on cloud strategy for media and entertainment companies: agility, cost reduction and scalability.
Read the post
WhitepaperHow to harness the power of AWS Personalize
Most OTT services want recommendations to lift viewership and catalogue breadth. How to deliver them quickly, at scale and with ease.
Read the whitepaper
BlogA new Paradigm for the commissioning and delivery of Video Platforms
Discover how agile, hybrid cloud strategies help media companies stay competitive, reduce costs, and accelerate innovation in the M&E industry.
Read the post
Talk to our media team
We have worked on most parts of this problem before, for national broadcasters and cable operators. If your architecture is fragmented, your data scattered, or your release cycle measured in quarters, we are happy to compare notes.