We help studios, streamers, publishers, and gaming companies harness AI to personalize content discovery, automate production workflows, combat piracy, and grow audience engagement and monetization.
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Average streaming churn rates of 30–40% annually bleed subscriber bases faster than acquisition can fill them. Without AI-powered retention, platforms are stuck on a treadmill of expensive acquisition cycles.
Over 50% of streaming subscribers cancel because they can't find content they love. Poor recommendation engines waste the value of massive content libraries and directly drive churn.
The global cost of content piracy exceeds $71 billion annually. Sophisticated watermarking circumvention and credential sharing erode the revenue base that funds new content creation.
Content production costs have soared 20–40% in five years. Without AI-driven audience analytics and greenlight models, studios continue betting hundreds of millions on gut instinct over data.
Industry Data
Annual Piracy Cost
$71BAvg. Streaming Churn Rate
35%Engagement Lift from AI Recs
3.4×Subscribers Lost to Discovery Failure
50%COPPA-compliant family content filtering, GDPR/CCPA audience data governance, and SAG-AFTRA AI guidelines awareness embedded into every media technology product we build.
Multi-signal recommendation models combining viewing history, real-time session context, social signals, and mood inference to surface content audiences love before they know they want it.
ML models that identify at-risk subscribers 30–60 days before cancellation — enabling targeted content nudges, personalized offers, and engagement campaigns before the decision is made.
Automated content tagging, scene classification, transcript generation, and mood/genre tagging at scale powering search, recommendations, and ad targeting without manual effort.
Audience affinity modeling, sentiment analysis, and greenlight scoring that help studios and platforms predict content performance before a dollar is spent in production.
Forensic watermarking, peer-to-peer monitoring, and credential sharing detection that protect content revenue and identify leakage sources in real time.
Contextual AI ad targeting, pod optimization, and yield management for AVOD and FAST channels maximizing CPMs without disrupting the viewer experience.
How We Do It
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Age-gating, parental consent workflows, and content filtering for platforms with under-13 audiences meeting FTC COPPA requirements.
Consent management, data subject rights, and cross-border transfer controls for all audience behavioral data collected by recommendation and ad targeting systems.
Automated rights clearance workflows, takedown management, and watermarking systems that protect your content and manage third-party rights obligations.
Disclosure and transparency mechanisms for AI-generated content and recommendation systems aligned with emerging EU AI Act requirements.
Workflow guardrails and consent management for AI tools that interact with performer likenesses, voices, and performances staying ahead of evolving talent union requirements.
Real-money gaming and loot box mechanics designed with jurisdiction-specific age verification, spend limits, and disclosure requirements built in for gaming platforms.
We know that financial services firms can't afford mistakes. Our engagement model is built around compliance, structured approvals, and measurable milestones at every stage.
We analyze your engagement data, content catalog metadata quality, and recommendation infrastructure to identify the highest-impact AI opportunities.
Custom recommendation, churn, and monetization models designed for your catalog scale, audience size, and business model.
Controlled holdout tests with statistically significant audience segments to validate engagement, retention, and revenue impact before full rollout.
Production deployment with real-time A/B testing infrastructure, model retraining on new viewing data, and monthly KPI reporting.
The passive churn model found subscribers we never would have reached with our old campaign triggers. We're retaining people who didn't even know they were leaving.
tripled after we deployed the recommendation engine. Our 'started but never finished' rate dropped to an all-time low. Audiences are actually watching what we recommend."
The greenlight scoring model helped us pass on three projects that our instincts said yes to. We reallocated that $18M to content the model predicted would overperform — and it did.