Media & Entertainment
AI that increases audience revenue and cuts content production costs
You get content recommendation agents, audience analytics, ad yield optimisation, and production workflow automation. All running on your cloud, connected to your existing platforms, with governance built in.
Built on your AWS, Azure or GCP tenant. Audience-first. Rights-compliant.
Proof of concept
To measurable ROI
AWS, Azure or GCP
Your audience data is the asset. AI is how you monetise it without hiring 200 more analysts.
You have viewing behaviour, content metadata, ad impression logs, and subscriber data flowing through your systems every second. The media companies pulling ahead are the ones converting that data into personalisation decisions, ad yield optimisation, and content investment signals faster than editorial instinct alone allows.
We build AI agents that connect your audience data to your revenue decisions from content recommendations and churn prediction to ad targeting and production scheduling, with the rights management and data privacy governance your legal team requires.
increase in content engagement from AI-driven personalisation (McKinsey, 2024)
additional ad revenue attributed to AI optimisation in media (BCG X, 2024)
reduction in subscriber churn with AI prediction models (Deloitte Insights, 2024)
of production budgets recoverable through AI workflow automation (McKinsey, 2024)
From audience signal to revenue action, in one workflow
We connect your CMS, audience analytics, ad platforms, CRM, and content management systems to AI agents that personalise experiences, optimise ad yield, predict churn, and generate the audience insights your programming and commercial teams need to make faster, better-informed decisions
CMS, viewer analytics, ad platforms and CRM
- Approval gates
- Human-in-loop
- Audit logging
AWS, Azure or GCP
- Content insights
- Ad performance
- Audience reports
What we deliver for media enterprises
From content recommendation to ad yield, governed, auditable, enterprise-ready
Content recommendation
Deliver personalised content recommendations that boost watch time.
ROI
Process
Aggregate audience signals
Viewing history, completion rates, search behaviour, and content metadata ingested across platforms in real time
Model preferences
AI builds per-user taste profiles combining collaborative filtering, content similarity, and contextual signals
Deliver recommendations
Personalised content surfaces pushed to apps, homepages, and notification systems with A/B test measurement
Sources
Originally published: McKinsey QuantumBlack, 'Personalisation in Streaming' (2024); BCG X, 'AI in Media' (2024), reproduced for illustrative purposes
Audience analytics and segmentation
Segment audiences and predict churn before subscribers leave.
ROI
Process
Capture behavioural data
Viewing patterns, engagement depth, subscription history, and demographic data aggregated across touchpoints
Build audience segments
ML models cluster audiences by behaviour, value, and churn risk with weekly refresh cycles
Activate insights
Segment profiles and churn predictions delivered to marketing, programming, and commercial teams
Sources
Originally published: McKinsey QuantumBlack, 'Customer Analytics in Media' (2024); Deloitte Insights, 'Audience Intelligence' (2023), reproduced for illustrative purposes
Ad yield optimisation
Maximise CPM and fill rates across your ad inventory.
ROI
Process
Integrate ad data
Impression logs, bid data, viewability metrics, and audience segments combined from SSP, DSP, and direct-sold inventory
Optimise yield
AI adjusts floor prices, ad load, placement timing, and targeting parameters to maximise revenue per session
Measure and iterate
Real-time dashboards track CPM, fill rate, viewability, and audience satisfaction with automated A/B testing
Sources
Originally published: BCG X, 'Ad Revenue Optimisation' (2024); McKinsey QuantumBlack, 'Programmatic AI' (2024), reproduced for illustrative purposes
Production workflow automation
Streamline production from script analysis through post.
ROI
Process
Map production pipeline
Script breakdown, scheduling, asset management, and post-production workflows captured in unified system
Automate routine tasks
AI handles transcription, subtitling, metadata tagging, quality checks, and schedule optimisation
Accelerate delivery
Automated handoffs between production stages with bottleneck detection and resource reallocation
Sources
Originally published: Deloitte Insights, 'AI in Content Production' (2024); McKinsey QuantumBlack, 'Media Production Efficiency' (2023), reproduced for illustrative purposes
Content performance prediction
Forecast content performance before release to guide spend.
ROI
Process
Analyse historical patterns
Past content performance, audience overlap, genre trends, and seasonal patterns combined into prediction models
Score new content
AI generates performance forecasts for proposed content with audience size, engagement, and revenue projections
Inform decisions
Commissioning teams receive data-backed content scores alongside marketing budget recommendations
Sources
Originally published: BCG X, 'Content Investment Analytics' (2024); McKinsey QuantumBlack, 'Predictive Content Modelling' (2024), reproduced for illustrative purposes
Rights and royalty management
Track rights windows and flag expiry before legal exposure.
ROI
Process
Ingest rights data
Licence agreements, territory rights, holdback windows, and royalty terms captured from contracts and rights systems
Monitor compliance
AI tracks rights windows in real time, flags approaching expirations, and identifies territorial conflicts
Automate reporting
Royalty calculations and rights compliance reports generated for finance, legal, and distribution teams
Sources
Originally published: Deloitte Insights, 'Digital Rights Management' (2024); BCG X, 'Content Monetisation' (2023), reproduced for illustrative purposes
Metadata and content tagging
Auto-tag and enrich metadata across your content catalogue.
ROI
Process
Process content
Video, audio, and text content analysed using computer vision, speech recognition, and NLP models
Generate metadata
AI produces genre, mood, theme, scene, and entity tags with confidence scores for human review
Enrich catalogue
Standardised metadata pushed to CMS, recommendation engines, and search systems across platforms
Sources
Originally published: McKinsey QuantumBlack, 'Content Metadata AI' (2024); AWS Case Study, BBC, reproduced for illustrative purposes
COO, Activision Blizzard (now Microsoft Gaming)
Daniel Alegre
"Azure AI enables us to personalise content experiences for hundreds of millions of players in real time. We can analyse engagement patterns, predict churn, and deliver tailored recommendations at a scale that was impossible with rules-based systems. The impact on retention and lifetime value is measurable every quarter"
Originally published: Microsoft Customer Stories — Activision Blizzard — reproduced for illustrative purposes
How we work in media environments
Media AI is only valuable when it connects to the audience and content data your platforms already generate. We start by mapping your existing data sources: CMS, audience analytics, ad servers, CRM, and rights management systems. Then we identify the one use case where AI will create the most immediate, measurable revenue impact.
Everything we build runs on your cloud tenant. Your audience data, your content metadata, your ad performance records. None of it goes to a third-party platform. Your rights holders, advertisers, and regulators can audit the system directly.
01
Data and use case mapping
We assess your existing audience and content data sources, identify the highest-value AI use case, and map it to your revenue and compliance requirements.
02
30-day proof of concept
A working AI agent on your cloud, connected to your audience or content data, with demonstrable output in 30 days.
03
Governance by design
Audit trails, rights compliance, and explainable outputs built in, structured to meet data privacy and content rights requirements.
04
Scale in 12-18 weeks
From one validated workflow to measurable revenue or efficiency ROI across your media operation.
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