MX Studio- Domain Specific AI for Media that Brought Licensing Fees to Zero
Breaking the legacy: A transition built for growth
MX Studio — a prominent media processing company has been in the industry since 2008.
While in the early years, a monolithic portal was sufficient to get the job done, MX Studio needed a serious tech upgrade to match its growth.
The challenge lived in two places: technical and operational. Scaling teams on demand and onboarding quickly during high turnover kept delivery on track.
Today, MX Studio’s platform runs at global pace — delivering 25,000 to 30,000 TV shows every month, across streaming platforms, telcos, airlines, and hotels. Petabytes of data. Millions of files. No compromise on speed or accuracy.
Industry
Media
Region
US
“Fix one thing, break two things,” and it never stopped.
The growth was outpacing the systems built to support it. Licensing costs had climbed past $220,000 annually. Quality control was still manual — frame-by-frame, spreadsheet-driven, dependent on headcount that couldn’t scale with volume. Semantic search across millions of assets lagged. Delivery validation against broadcaster specifications required human review at every single stage.
MX Studio needed a partner. Now.
But outsourcing is not simple when the systems are mission-critical. The stakes go up. The product called for a microservice-based, API-first approach, since integration would be central to how the platform functioned.
Even with the platform stabilized, the harder question was less visible: how do studios actually understand and monetize the content they own? MX Studio needed an AI-driven way to unlock the value buried in massive content libraries.
But AI for media demands more than a turnkey fix. Data security and privacy stay non-negotiable. An on-premises deployment was the only answer.
Highlights
Annual software licensing
Search across archive
TV shows/month
Global content distribution
Multilingual Reach
Fully automated
Eight weeks to three: Brisk delivery, zero compromise
Navtech started small: QA and regression testing on a legacy product, and that was the only scope. Every delivery landed clean, and clean delivery builds trust. Modules that once took six to eight weeks now raced down to three. Over time, the trust grew into full project ownership, a long-term partnership earned one sprint at a time.
The next step was deliberate. Navtech built MX Studio — a domain-specific AI platform designed from the ground up for media operations, purpose-built for broadcast content, from subtitle detection to multi-language transcription to delivery validation, all without human intervention.
The underlying data infrastructure came next, re-architected for massive-scale search with sub-second response times and no third-party licensing.
The result: a platform fully owned by the client. No vendor dependency. No roadmap risk. Weeks in, the client was live, hands on the product, shaping it in real use.
Navtech scaled teams up and down as needed — UI-heavy work, deep Python development for the AI platform, Java-based workflow orchestration.
Deploy big. Deploy fast. Deploy anytime.
For the client, moving to live Version 2.0 was an existential shift. Navtech applications went native, designed from the core out.
Every component was designed around a single job — not lifted from a generic toolkit to fit. The difference shows up in accuracy, speed, and performance that off-the-shelf tools simply can’t reach. And because everything runs on the client’s own infrastructure, data never leaves home. No third-party cloud, no outside processing, and no vendor roadmap dictating what comes next.
When the platform is fully owned, the economics only get better with time — content grows, requirements evolve, without a licensing invoice to follow.
Disney+, Apple TV+, the rest of the streaming world — the whole industry raced to launch exclusive content during COVID, right as everyone else ground to a halt. Navtech didn’t stop. Devs, engineers, QA, DevOps — a full agile pipeline, assembled fast, shipping on schedule. MX Studio’s offering, extended without disrupting a single service.