Why Scriptlyfy Exists
We are building an operator‑grade layer for creative intelligence: unify ingestion, preserve structure, derive patterns, accelerate repurposing. Faster loops, higher confidence, less manual glue work.
Mission
Compress weeks of fragmented social video research into minutes and turn unstructured multi‑platform media into reusable strategic building blocks. Equip lean teams with leverage previously locked inside large media orgs.
Approach
- Deterministic ingestion & stable IDs.
- Layered enrichment (transcript → segments → hooks → embeddings).
- Composable derivative assets for repurposing.
- Human‑feedback loops to tune extraction precision.
Four Core Pillars
Normalization
Consistent schema across platforms unlocks cross‑surface pattern comparison.
Structure Preservation
We retain timing, segmentation & contextual adjacency— not just text.
Pattern Extraction
Hook archetypes, pacing signals, narrative shape embeddings.
Repurposing Bridge
Immediate scaffolds for variant scripts & short‑form adaptation.
Operator Feedback Loop
- 1Bulk ingest & dedupe
- 2Semantic + structural enrichment
- 3Pattern surfacing & clustering
- 4Human validation / adjustment
- 5Repurpose & test hypotheses
Architecture (Simplified)
Stages write immutable artifacts keyed by content hash + version enabling selective recompute.
Trust & Data Stewardship
Purpose Limited
Research acceleration only—no resale of transcripts or behavioral exhaust.
Access Minimized
Role + time scoped access with audit logging at sensitive boundaries.
User Control
Export / delete pathways honored via verified email request.
Full detail: Privacy Policy.
Roadmap Themes
Adaptive Hook Index
Continuously refreshed archetype taxonomy with drift detection.
Cross-Platform Diffs
Compare structure vs. retention & engagement curves.
Repurposing Automation
AI assisted script variants aligned to pacing heuristics.
Collaboration Layer
Shared libraries, annotations, pattern watchlists.
Live signal: /roadmap
Help Shape the Enrichment Layer
Create a free account to influence extraction depth, pattern surfacing UX, and repurposing scaffold formats. We prioritize feedback with clear operator outcomes.