Deterministic Parsing
Precision Anatomy
Watch how our Geometric Engine translates standard PDF coordinates into structured data with sub-millimeter precision.
- X/Y Geometry Analysis: Detection of Scene Headers via vertical displacement and font-weight shifts.
- Margin De-duplication: Intelligent merging of duplicate scene numbers on left/right gutters.
INT. COMMAND CENTER - NIGHT
The hum of servers fills the room. ELARA (30s) stares at the terminal. Her hands tremble.
ELARA
(whispering)
It's working. The protocol is live.
{"type": "SCENE_HEADER","slug": "INT. COMMAND CENTER","metadata": {"loc": "COMMAND CENTER","time": "NIGHT","coord_y": 128.42},"cast": ["ELARA"]}
> Geometry match found
The Bible Protocol
Neural Entity Graph
A persistent memory layer that tracks characters and objects across the entire narrative, ensuring deep storyboard consistency.
Entity Persistence
Storage Layer
Every dynamic entity (Cast, Prop, Wardrobe) is assigned a global UUID. The system cross-references these across the entire narrative timeline.
Cross-Scene Context
Semantic Memory
If character 'A' is described wearing a 'torn leather jacket' on Page 4, the Context Bible maintains this state until a transition event overrides it.
Relational Graphs
Structural Logic
Maps character connections and movement patterns between INT and EXT locations, identifying potential production bottlenecks automatically.
Vector Indexing
AI Acceleration
High-dimensional embeddings of scene descriptions allow for rapid similarity searches, ensuring visual consistency across storyboard frames.
Generative Synthesis
Prompt Evolution
The journey from raw script text to a cinematically controlled visual frame through multi-layered metadata injection.
Lighting Matrix
Automatic shift from 'Golden Hour' to 'High-Key' based on DAY/NIGHT metadata.
Lens Protocol
Dynamic F-stop and focal length selection based on character presence.
MIZA Node Pipeline
Modular Storyboard Architecture
Each scene is decomposed into a directed acyclic graph of interconnected nodes. Characters, beats, prompts, and outputs form a visual pipeline where every parameter feeds into the next stage.
Per-Beat Nodes
MODULAR ATTACHMENTS
Attach Location, Costume, Notes, and Reference nodes to individual beats. Each attachment enriches the generation prompt with targeted context.
Edge Routing
DRAG & CONNECT
Dynamic edges connect attached nodes to beat nodes. Drag edges to reassign, delete to disconnect. All connections persist to backend.
Generation History
VERSIONED OUTPUT
Every output node retains full generation history. Browse, compare, and revert to any previous generation per beat.
Batch Rendering
PARALLEL EXECUTION
Generate all beats simultaneously with a single click. Each beat composes its own prompt from the full node graph context.
Script Bible
Analytical Intelligence Modules
Multi-dimensional script analysis through interactive visualization modules. Character heatmaps, relationship force-graphs, AI-powered pitch generation, and statistical breakdowns provide complete project intelligence from a single interface.
- Character Presence Heatmap with scene navigation
- Force-directed relationship graph with interaction tooltips
- AI Pitching: logline, synopsis, character arcs, tone
- Cast & location management with photo references
Distributed Pipeline
High-throughput architecture designed for asynchronous heavy compute tasks.
Ingestion
Multi-format PDF extraction via coordinate analysis.
Logical Parser
FastAPI Python service for semantic structure identification.
Neural CPU
LLM orchestration for deep summarization and logic extraction.
Visual GPU
SDXL/Banana Pro inference for cinematic frame generation.
Front HUD
React/Next.js dashboard for production verification.
Bible Engine
Analytics, heatmaps, graphs, and AI pitching from script-wide data
Performance Metrics
Ingestion Latency
< 2.4s
Parsing Precision
99.2%
Visual Generation
12-18s
System Scalability
Max Script Length
∞ Pages
Entity Memory
2048 Tok
Concurrent Workflows
128 Units
Compliance & Standards
Supported: FDX, PDF (Standard US Letter), DOCX, Plain UTF-8.
Architecture: Docker Microservices, PostgreSQL 15, FastAPI Pydantic v2.
Industry Benchmarks
Why deterministic geometry beats probabilistic text models every time in production environments.
| Protocol Feature | Generic LLM | Cinemata Engine |
|---|---|---|
| Geometric Parsing | Probabilistic/Token-based | Deterministic X/Y Coordinates |
| Character Memory | Sliding Window (Forgetful) | Global Entity UUID Persistence |
| Frame Synthesis | Randomized Diffusion | Metadata-Constrained Injection |
| Production Intelligence | No script-wide analytics, no heatmaps, no cast management | Bible engine: heatmap, relationship graph, AI pitching, cast & location CRMs |