Remotion
Pipelines,
SHA256-Cached,
Multi-Provider
Deterministic AI video pipelines — multi-provider orchestration, brand-aware composition, content-addressed caching. From script to rendered output, no manual intervention.
Video as Engineering, Not Editing
Deterministic Video Pipelines
Job → Storyboard → Assets → Assembly → Render → QA
Multi-Provider AI
Gemini (image), Veo/Seedance (video), ElevenLabs (voice)
Brand Profile Enforcement
Colors, fonts, tone, banned claims, duration limits
Content-Addressed Caching
SHA256 canonical JSON → immutable artifacts, zero invalidation
Paid API Gating
Dry-run → human review → GO GENERATE token validation
Remotion Compositions
ProductReel, KpiClip, DemoWalkthrough, JewelryShowcase
3D Rendering Research
Image-to-3D conversion, 10+ models evaluated, IoU metrics
From Job Definition to Final Render
Job Definition
Define the video — type, brand profile, target audience, key messages. Zod-validated schema.
Creative Direction
AI generates creative direction from job spec — visual style, pacing, shot composition, music cues.
Storyboard
Scene-by-scene breakdown with timing, transitions, text overlays, and asset requirements.
Asset Generation
Multi-provider AI generates images, video clips, and voiceover. SHA256 caching prevents regeneration.
Assembly & Render
Remotion compositions assemble assets into deterministic video. Pure functions — same input, same output.
QA & Delivery
Automated quality checks, compliance verification against brand profile, final render output.
Built and Rendered
A deterministic video pipeline produces the same output from the same input — every time. No randomness, no Date.now(), no network calls during rendering. The Remotion compositions are pure functions of resolved input JSON. This means you can reproduce any video, debug any frame, and guarantee brand consistency. Most AI video tools are black boxes. This is engineering.
Every asset request is serialized to canonical JSON and SHA256 hashed. The hash becomes the cache key. If the same request comes in again — same prompt, same model, same parameters — the cached artifact is returned instantly. No cache invalidation logic, no TTLs, no stale data. If inputs change, the hash changes, and a new artifact is generated. This saves thousands of dollars in API costs across production runs.
AI image and video generation APIs cost real money. The pipeline implements 3-level confirmation before spending: (1) dry-run plan showing exactly what will be generated and estimated cost, (2) human review of the plan, (3) explicit GO GENERATE <job_id> token validated at the provider level. No accidental $500 API bills. Every dollar spent is intentional.
Yes. The pipeline is designed for multi-brand operation. Each brand gets a profile that enforces colors, fonts, tone, banned claims, CTA patterns, and duration limits at assembly time. Adding a new brand is a configuration file, not a code change. Current profiles serve 4 projects with completely different visual identities from a single codebase.
REMOTION PIPELINES
SHA256-CACHED · MULTI-PROVIDER
Deterministic AI video pipelines — multi-provider orchestration, brand-aware composition, content-addressed caching. From script to rendered output, no manual intervention.
Video as Engineering · Not Editing
From Job Definition to Final Render
Job Definition
Define the video — type, brand profile, target audience, key messages. Zod-validated schema.
Creative Direction
AI generates creative direction from job spec — visual style, pacing, shot composition, music cues.
Storyboard
Scene-by-scene breakdown with timing, transitions, text overlays, and asset requirements.
Asset Generation
Multi-provider AI generates images, video clips, and voiceover. SHA256 caching prevents regeneration.
Assembly & Render
Remotion compositions assemble assets into deterministic video. Pure functions — same input, same output.
QA & Delivery
Automated quality checks, compliance verification against brand profile, final render output.
Built and Rendered
Deterministic Video Pipeline
Built a production video generation pipeline as a pnpm monorepo: 12 CLI commands (init, new-job, director, storyboard, gen-assets, assemble, preview, render, qa, cost, models, cache). Multi-provider AI with model registry YAML. Zod v3/v4 validation at every stage.
3D Product Visualization R&D
Evaluated 10+ generation and reconstruction models for image-to-3D jewelry rendering: Hunyuan3D, Tripo3D, Trellis, TripoSR, Meshy, Rodin. Quantitative silhouette IoU metrics, depth map assessment, custom Blender automation for comparison. Research-grade methodology.
What is a deterministic video pipeline?
A deterministic video pipeline produces the same output from the same input — every time. No randomness, no Date.now(), no network calls during rendering. The Remotion compositions are pure functions of resolved input JSON. This means you can reproduce any video, debug any frame, and guarantee brand consistency. Most AI video tools are black boxes. This is engineering.
How does content-addressed caching work?
Every asset request is serialized to canonical JSON and SHA256 hashed. The hash becomes the cache key. If the same request comes in again — same prompt, same model, same parameters — the cached artifact is returned instantly. No cache invalidation logic, no TTLs, no stale data. If inputs change, the hash changes, and a new artifact is generated. This saves thousands of dollars in API costs across production runs.
What's paid API gating?
AI image and video generation APIs cost real money. The pipeline implements 3-level confirmation before spending: (1) dry-run plan showing exactly what will be generated and estimated cost, (2) human review of the plan, (3) explicit GO GENERATE <job_id> token validated at the provider level. No accidental $500 API bills. Every dollar spent is intentional.
Can you build a video pipeline for my brand?
Yes. The pipeline is designed for multi-brand operation. Each brand gets a profile that enforces colors, fonts, tone, banned claims, CTA patterns, and duration limits at assembly time. Adding a new brand is a configuration file, not a code change. Current profiles serve 4 projects with completely different visual identities from a single codebase.