AI for Media
We help organizations building, operating, and evolving video and streaming platforms integrate AI safely, increasing engineering velocity without compromising reliability, accountability, or control.
Where AI applies across the pipeline
From camera to social feed, AI has applications at every stage of the production chain.
Acquisition & Capture — Getting the signal in, with fewer operators
Virtual PTZ from wide master
Extract multiple framed outputs from a 4K/8K capture in real time, replacing dedicated PTZ operators on the floor.
Auto-framing for vertical output
Continuously crop 9:16 from the 16:9 feed for social with no dedicated operator — one camera, two outputs.
Camera tracking & subject lock
Lock onto subjects and emit tracking data for graphics, AR overlays, and autonomous cameras across the venue.
Live Production — Running the show with a smaller gallery
Graphics & lower-third automation
Populate and trigger scoreboards and ID graphics from data feeds — no graphics operator needed in the gallery.
Real-time commentary assist
Surface live stats and context to commentators, expanding what a single-person booth can carry without a researcher.
Unattended production
A fixed camera plus auto-direction replaces a full crew for grassroots and niche tiers — opening low-cost events as live inventory.
Editorial & Post — From rushes to a first cut, faster
Highlight packaging & auto-clipping
Detect highlight moments and assemble branded short-form packages — table stakes in sports production today.
Concurrent social cut-down
Spin out vertical clips and highlight bundles live, removing the social team as a separate downstream production step.
Rough cut assembly from rushes
Log raw footage, pair it to script or treatment, and build a first-pass edit for the editor to refine — not replace.
Accessibility & Localization — One feed, every audience
Live & frame-accurate captioning
Speech-to-text at sub-second latency for live or full accuracy for VOD — from a single audio feed, multiple languages.
Subtitle & CC translation
Translate source subtitles and audio into target-language closed captions across multiple markets simultaneously.
AI audio description
Generate and voice scene description tracks for low-vision audiences — far faster than human-narrated AD at scale.
Broadcast Ops & QC — Keeping the signal clean automatically
Signal integrity detection
Detect black frames, freezes, macroblocking, and HDR errors in real time on the live feed — alerting before air, not after.
Audio compliance & loudness
Monitor loudness (EBU R128, CALM Act), lip sync, and Dolby metadata continuously across the full signal chain.
Ad-break auto-detection
Multi-model orchestration identifies natural break points and inserts SCTE-35 markers automatically — no operator required.
Fan Engagement & Social — Machine speed around live moments
Vertical highlight clips, auto-cut
Detect goals and key plays, reframe to 9:16, burn captions, and ship Reels/TikTok/Shorts — in minutes from the live feed.
Instant matchday graphics
Auto-generate stat cards, lineups, scorelines, and record graphics straight from the live data feed — no designer in the loop.
Multilingual social posts
Auto-write captions and posts per moment across languages — reaching global fanbases from a single event without a localization team.
Engineering Partners for the AI Era!
We build operating models, not tool deployments
Getting AI to work once is easy. Building the governance, policies, and team practices that make it sustainable is the hard part. That's where we focus.
We speak the language of streaming
Reliability, IP, compliance, live ops — we already know the stakes. Our engineers have spent their careers in this domain.
We transfer ownership
Your team runs this. You stay in control. The goal of every engagement is that you can evolve the capability without us.
AI integrates into engineering, not alongside it
The care taken building your system is the same care we use extending it with AI. Same repositories. Same review processes. Same accountability.
A Journey of Adoption, not a switch
Exploration
We start from your context, not a generic promise. We map your legal, technical, and operational constraints — identify where AI creates real friction reduction — and define a concrete, bounded use case to begin with. We create a safe sandbox where your teams can learn without putting production at risk.
Integration
We integrate AI into your existing workflows in an orderly, visible way — within your repositories, your review processes, your testing infrastructure. We define usage policies, permitted models, data access criteria, and human review gates. AI lives inside engineering, not alongside it.
Scaling
Once something works, we help you document the model, expand to new teams, and adjust governance for organizational adoption. The goal isn't to prove a point of concept — it's to build a way of working that sustains itself over time, with knowledge transfer that gives your team real ownership.
What level makes sense for your context?
Not every engagement needs the same level of AI integration in how we build. We work with each client to define what's right for their platform, their risk tolerance, and their current constraints — from fully restricted environments to AI-driven development with full review infrastructure.
Restricted
No AI toolingNo AI tooling at any stage of the workflow. Every output is produced entirely by humans.
Highly regulated environments or organizations with strict IP policies that haven't yet cleared AI usage.
Documentation & Research
Internal onlyAI for internal knowledge work only! Research, summaries, drafts. No client materials or code involved.
Early exploration phases and conservative organizations building AI literacy before committing to deeper integration.
Engineering Assistance
Dev tasksAI assists with dev tasks! Code generation, refactoring, explanations, without exposing confidential data or proprietary systems.
Teams starting to experiment with AI in real work and wanting to measure impact before going deeper.
AI-Assisted Development
In-workflowAI lives inside the workflow (IDE, repos, review tools) but engineers own every change. AI suggests, humans decide.
Mature engineering teams with strong review culture and the discipline to treat AI output as a draft, not a deliverable.
AI-Driven Development
Full review infraAI agents generate changes and open PRs. Review, testing, and approval gates always apply, autonomy is bounded, not skipped.
Organizations with established governance and review infrastructure mature enough to absorb a higher volume of AI-generated changes.
AI in streaming isn't a generic problem
Platforms where downtime costs millions don't get to experiment carelessly. The AI conversation in media technology is shaped by hard constraints: reliability requirements, IP protection, compliance, real-time operations, and the accountability of engineering teams who can't hide behind "the model decided."
That's why our approach isn't about adopting AI tools. It's about building the operating model that makes AI work safely inside complex, mission-critical streaming systems.
Reliability & Live Ops
Real-time systems can't afford unpredictable outputs or uncontrolled dependencies.
IP & Compliance
Content rights, data residency, and contractual constraints define what AI can touch.
Engineering Accountability
Every change must be reviewed, owned, and traceable. AI doesn't change that.
Operational Complexity
Multi-CDN, adaptive bitrate, DRM, ad-insertion — the stack leaves little room for error.
One safe use case,
one month,
A demonstrable result!
We start small and specific, a bounded scope, a visible outcome, and a working model you can validate before committing to scale.