Communication, Media & Technology Solutions

The Business Challenge

The Pressures Facing Media & Telecom Companies

Media companies and telecom operators face a structural shift — audiences are fragmenting across hundreds of platforms, attention spans are shrinking and advertising models that sustained broadcasters for decades are being disrupted by streaming giants with superior personalisation technology. Competing requires the same AI-first infrastructure that the major platforms have built.

Content Discovery Overload

Subscribers who cannot find content they want within 90 seconds cancel their subscription. With catalogues running to thousands of titles, manual curation cannot scale — AI recommendation is the only mechanism that works at library depth.

Subscriber Churn at Scale

Monthly churn rates of 5–10% are common across streaming platforms. Each percentage point of churn represents millions in lost annual recurring revenue — and most platforms cannot identify at-risk subscribers before cancellation happens.

Legacy Broadcast Infrastructure

Traditional broadcast technology stacks were not designed for the on-demand, multi-device, global delivery requirements of modern streaming. Rebuilding on cloud-native infrastructure while keeping existing services live is the central engineering challenge for legacy media businesses.

Fragmented Audience Analytics

Viewing data, subscription data, social engagement and ad performance sit in separate systems that cannot talk to each other. Without a unified audience view, content investment decisions and advertising products are built on guesswork rather than behavioural insight.

Our Capabilities

How We Apply AI & Engineering in Media & Telecom

Six specific capabilities we deploy for media companies and telecom operators — each tied to a measurable business outcome: engagement, churn reduction or content monetisation.

OTT Platform Development

End-to-end OTT platform engineering: video ingestion, transcoding, adaptive bitrate streaming (HLS/DASH), DRM, multi-device apps (iOS, Android, Smart TV, Web) and a CMS for content operations teams — built on cloud-native infrastructure that scales to millions of concurrent streams.

AI Content Recommendation Engine

Collaborative filtering, content-based and hybrid recommendation models trained on viewing history, engagement signals and contextual data — delivering personalised content discovery rows that increase session length, reduce time-to-play and measurably lower churn.

Real-Time Streaming Infrastructure

Cloud-native streaming pipelines using Kafka, Flink and WebRTC for low-latency live event delivery — supporting sports broadcasts, live news and interactive events with sub-second latency at global scale, with automatic failover and multi-CDN routing.

Audience Analytics & Segmentation

Unified audience data platforms that aggregate viewing behaviour, subscription lifecycle, device usage and ad exposure — feeding ML segmentation models that enable hyper-targeted content marketing, dynamic ad insertion and subscriber lifetime value optimisation.

Automated Content Moderation

Computer vision and NLP models that automatically classify, tag and moderate user-generated content — detecting policy violations, adult content and misinformation at the speed and scale that manual review teams cannot match, with human escalation workflows for edge cases.

Telecom Churn Prediction & Retention

ML models trained on usage patterns, billing history, support interactions and network experience data that identify at-risk subscribers 30–60 days before cancellation — enabling targeted retention campaigns with personalised offers delivered at exactly the right moment.

Our Approach

Media Platform Delivery in Four Phases

A phased approach that puts core streaming infrastructure first, then layers AI personalisation and analytics on a solid foundation — so each phase delivers business value independently.

Platform Architecture & Audit

We assess your current streaming stack, content catalogue and audience data maturity — defining the target architecture, identifying quick wins and building the business case for cloud migration.

Stack Audit CDN Evaluation Data Audit

Core OTT Platform Build

Video ingestion pipeline, transcoding, DRM, adaptive streaming and multi-device apps delivered — with content CMS, subscription management and payment integration live for launch.

HLS / DASH React Native AWS / GCP

AI & Analytics Integration

Recommendation engine trained on initial viewing data, audience data platform unified and churn prediction model deployed — validated against baseline engagement metrics before full rollout.

Recommendation ML Kafka Pipeline A/B Testing

Scale & Monetisation

Platform scaled to full audience; dynamic ad insertion and programmatic advertising integrated; content moderation AI deployed; live event infrastructure commissioned for high-concurrency broadcasts.

SSAI / CSAI Live Streaming Moderation AI

Capabilities

What a Media Tech Engagement Delivers

OTT & Streaming Platform

End-to-End OTT Platform & AI Recommendation — Representative Engagement

A representative Barquecon media technology engagement delivers a complete OTT platform for a broadcaster or streaming startup: video pipeline (ingestion, transcoding, adaptive streaming), multi-device apps, subscription and payment systems, and a content CMS — with an AI recommendation engine trained on viewer behaviour to personalise the experience from day one. The same engineering team handles backend API, frontend apps and ML models — removing the coordination overhead that typically derails media platform projects.

Full OTT stack — video pipeline, DRM, adaptive streaming and multi-device apps (iOS, Android, Web, Smart TV)
AI recommendation engine personalising content discovery from launch — trained on real viewing data
Audience data platform unifying viewing, subscription and engagement data for content and marketing teams
Churn prediction model identifying at-risk subscribers with 30–60 days lead time for retention campaigns

Discuss Your Media Platform Requirement →

Media & Telecom Digital Transformation