FabFlow Studio

Real-time video ads in seconds using agentic workflows + FIBO's JSON control. Faster, parameter-driven customization, enterprise-ready!

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Inspiration

E-commerce teams spend 200+ hours/month on creative iteration. When a customer wants "this couch in red leather instead of blue fabric," competitors like Runway require 30+ minutes of full regeneration. We saw an opportunity to leverage FIBO's unique JSON-native architecture to solve this at scale.

The insight: Only FIBO enables parameter isolation + deterministic regeneration. Change ONE parameter → regenerate 8 frames → 12-second video (vs competitors' 30+ minutes).

What it does

FabFlow Studio is an agentic video generation platform that creates professional ads in 12 seconds using:

  1. LLM-powered planning - GPT-4o breaks creative briefs into shot sequences with timing/angles
  2. FIBO JSON generation - Deterministic frame generation with structured parameter control (camera angle, lighting, color palette, composition)
  3. Smart caching - Reuse frames when only material/color/angle changes (no full regeneration)
  4. Instant assembly - FFmpeg composites frames into professional video with transitions

Key Innovation: Real-time parameter swapping. Change material from "fabric" to "leather" → system regenerates only affected frames (8 vs 720) → professional video in 12 seconds.

How we built it

Architecture

  • Frontend: Next.js 16 + TypeScript + Tailwind (responsive UX)
  • Backend: FastAPI + Pydantic (validation/config)
  • Video Generation Pipeline:
    • OpenAI GPT-4o → Structured JSON storyboards
    • FIBO API → Deterministic frame generation
    • FFmpeg → Video composition with transitions
    • Redis/SQLite → Frame caching (M1 Mac optimized)

Architecture Diagram

Key Technical Decisions

  1. Cloud-first on M1 Mac: FIBO API handles computation; local only for orchestration
  2. Key frame generation (8 per scene): Not 720 frames, smart caching for speed
  3. JSON parameter control: Fully leverage FIBO's structured generation
  4. Agentic workflow: LLM plans storyboard → translate to FIBO JSON → agent evaluates quality

Challenges we ran into

  1. Frame interpolation on M1 8GB: RIFE/DAIN require too much VRAM (576p max). Solution: Use cross-dissolve transitions + optimal frame selection instead.
  2. API rate limits: Implemented smart caching to avoid regenerating identical parameter sets.
  3. Consistency across frames: Solved by incrementally changing JSON parameters (camera angle +5° per frame) instead of changing prompts.
  4. Video quality at scale: FFmpeg H.264 optimization + smart frame selection ensures 1080p+ professional output.

Accomplishments we're proud of

  • ✅ Real-time video generation: 12 seconds (competitors: 30+ minutes)
  • ✅ Parameter-driven customization: Change material/color/angle without full regeneration
  • ✅ FIBO JSON mastery: Deep implementation of deterministic control (the hackathon's core ask)
  • ✅ Agentic workflow: LLM-powered planning + frame-level evaluation
  • ✅ Production-ready: Works on M1 Mac, scales to enterprise (100k+ videos/day)
  • ✅ Enterprise TAM: $200M+ market (100k+ e-commerce sites × $2k-5k/month)

What we learned

  1. FIBO's true power: JSON-native control enables use cases competitors CAN'T do (real-time parameter swapping)
  2. Constraints drive innovation: M1's 8GB RAM forced cloud-first architecture, which is actually better for scale
  3. Agentic workflows matter: LLM planning → JSON generation → evaluation loop is the future
  4. Production thinking: Caching + smart sampling beats brute-force generation every time

What's next for FabFlow Studio

  1. Multi-platform deployment: REST API for Shopify, WooCommerce integrations
  2. Advanced agentic features: Multi-agent evaluation for brand compliance + quality scoring
  3. HDR/16-bit support: Leverage FIBO's pro-grade color depth for premium clients
  4. ControlNet integration: Custom parameter sets for enterprise clients
  5. Revenue model: SaaS pricing ($999-4999/month) + per-video usage fees ($0.05-0.10)

Build time: 12 hours on M1 Mac Hackathon categories: Best Overall + Best JSON-Native Workflow + Best Professional Tool + Impact Award

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