Video Intelligence for Media and Entertainment Hackathon

Build the Future of Media Tech Before NAB 2026

Video is 82% of internet traffic and 90% of unstructured enterprise data. Yet most systems managing this data treat video like it's just a series of images. They sample frames, run object detection, and call it done.

That's why studios spend $75K-150K per editor annually on manual search labor. Why compliance review runs at 1:1 ratio (one hour of watching per hour of content). Why editors spend 4-8 hours scrubbing footage to find a single moment.

This hackathon asks you to close that gap.

What You're Building

Choose one of three challenge tracks, each addressing a real production bottleneck with quantifiable costs:

🔍 Archive Intelligence Build semantic search that makes petabyte-scale libraries actually queryable. Most studios can't find 80%+ of the footage they own. Your solution should let producers search in natural language ("sunset over water with birds flying") and get timestamped results in seconds instead of hours.

✂️ Intelligent Segmentation Create systems that detect semantic boundaries in long-form video. Think ad breaks that feel natural (not mid-sentence cuts), news story segmentation based on topic changes (not just camera cuts), or structural analysis that understands narrative flow. Manual segmentation costs $50-100 per hour—your solution should make it minutes.

✅ Compliance Guardian Automate content review with explainable AI. Build a system that flags violations ("beer bottle at 3:42 in scene with minors") with enough context for fast human validation. Compliance delays cost days of time-to-market and single violations risk $10K-$10M+ fines. Your solution needs to be both fast and auditable.

Why This Matters

NAB 2026 starts three weeks after this hackathon. While NAB will be full of vendor pitches about the future, this weekend is about actually building infrastructure that works today.

Several past TwelveLabs hackathon projects have turned into production deployments and formal vendor evaluations. The judges sitting in this room represent the buyers and technical decision-makers at tier 1 media companies. What you build here has legs beyond the weekend.

Technology Stack

TwelveLabs Marengo + Pegasus via AWS Bedrock All participants receive AWS Bedrock credits to access TwelveLabs' video foundation models. Marengo handles multimodal embeddings and semantic search. Pegasus generates descriptions and structured outputs. Bedrock provides enterprise infrastructure with built-in governance controls.

Sponsor Platforms (Recommended)

• Baseten: Production model serving and application orchestration
• LTX: Video generation and editing for post-processing workflows
• TrackIt: AWS solutions architecture expertise for media workload optimization
• NVIDIA: GPU-accelerated inference guidance

Prizes & Recognition

Total Prize Pool: $2,250 + Extended API Credits

• 1st Place: $1,000 + API Credits
• 2nd Place: $750 + API Credits
• 3rd Place: $500 + API Credits

More valuable than prizes: Technical validation from practitioners who've shipped these systems in production. Judges include TwelveLabs engineering leadership, AWS solutions architects, studio executives, and sponsor technical teams.

Event Schedule

Saturday, March 28

• 9:00 AM: Registration & Breakfast
• 10:00 AM: Opening Keynote + Challenge Introductions
• 10:45 AM: Team Formation
• 11:00 AM: Hacking Begins (AWS Bedrock credits + API keys distributed)
• 12:00 PM: Lunch Provided
• 1:00-3:30 PM: Technical Workshops (TwelveLabs, AWS, Baseten, LTX, NVIDIA)
• 4:00 PM: Office Hours Begin
• 5:00 PM: Venue Closes (continue remotely or rest)

Sunday, March 29

• 9:00 AM: Venue Opens, Final Sprint
• 9:30 AM: Morning Office Hours
• 12:00 PM: Lunch Provided
• 12:30 PM: Submissions Due (Hard Deadline)
• 1:00 PM: Project Presentations (10 min each: 7-min demo + 3-min Q&A)
• 4:00 PM: Judging Deliberation
• 4:30 PM: Awards Ceremony + Closing Reception
• 5:00 PM: Venue Closes

Who Should Participate

We're looking for technical practitioners who understand media workflows and want to build enterprise-grade solutions. Ideal participants include:

• Software engineers and ML engineers at media companies
• Solutions architects working with video infrastructure
• Technical product managers evaluating video AI platforms
• Developers building production systems at studios, broadcasters, or platforms

This is an application-based event. We're selecting for technical depth, not volume.

Location

Culver City, Los Angeles—walking distance from major studio campuses. You're building in the heart of the entertainment industry, surrounded by the production facilities that will actually use these solutions.