Building Real-Time Video Agents with VAST Data Engine
Details
NOTE: REGISTER HERE
PLEASE REGISTER ON LUMA TO BE ACCEPTED.
Most video AI demos stop at simple playback or offline analysis. Real-time video intelligence at scale requires ingesting streams, processing content, and retrieving meaningful insights instantly.
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## WHAT YOU'LL BUILD
A working real-time video agent powered by VAST DataEngine.
You'll implement a full pipeline: from ingesting video streams to generating summaries, detecting events, and retrieving relevant moments using embeddings.
By the end, you'll have a system you can run, tweak, and take back to your team, capable of processing video in real time, flagging key events, and integrating with downstream tools like Slack.
Your pipeline will:
- Ingest video via event-driven triggers (S3 buckets)
- Generate LLM-powered video summaries
- Detect events from video streams
- Create video embeddings for semantic search
- Retrieve relevant video segments using vector search
- Send automated notifications for key events
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## KEY TOPICS
- Event-driven architectures for video processing
- Building with VAST DataEngine for AI pipelines
- LLM-based video summarisation
- Video embeddings and vector search
- Designing scalable, real-time video pipelines
- Translating prototypes into production systems
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## AGENDA
4:00 PM — Doors Open: Welcome & Check-In
Security check-in - elevator to 7th floor - grab a coffee/water/soda
4:30 PM — Framing & Vision: What We’re Building and Why
4:45 PM — Live Demo: End-to-End Video Agent in Action
5:00 PM — Guided Build Part 1: Core DataEngine Foundations
(Connect to VAST lab, trigger functions, LLM integration)
6:00 PM — Break
6:10 PM — Guided Build Part 2: Production Features
(Video embeddings, vector queries, user-facing applications)
6:55 PM — Production Wrap-Up: Scaling to Real-World Systems
7:10 PM — Q&A & Next Steps
7:25 PM — Networking with Peers and the VAST Team
8:00 PM — Event Close
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## WHO SHOULD ATTEND
Intermediate to senior developers, ML/AI engineers, agent builders, and data engineers.
Industries: AI, Media & Entertainment, Financial Services
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## PREREQUISITES
Required:
- Laptop
- Comfortable coding in Python
- Familiarity with APIs and basic ML workflows
Helpful (not required): Experience with LLMs, embeddings, or event-driven systems
Setup: You'll connect to the VAST lab environment (no local setup required). Instructions sent 3-5 days before the workshop.
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PLEASE REGISTER ON LUMA
https://luma.com/h8muplvs
https://luma.com/h8muplvs
https://luma.com/h8muplvs
Seats are limited: register now to secure your spot!