SSCA v7 – How It Works

The Full Layer Stack: From Raw Data to Revolutionary Compression

The full SSCA v7 layer stack — how raw data becomes ultra-efficient, lossless, searchable meaning.

SSCA v7 is not just another compressor — it's an intelligent, self-adapting system that understands meaning, learns from your data, and optimizes itself for any device or scale — including scanned documents and PDFs.

Below is the complete journey your data takes through the SSCA stack — from raw input to ultra-compact, lossless, searchable output.

INPUT
Raw Data (Any Format)

JSON • Logs • Telemetry • Social Threads • Video Metadata • Images • Audio • Scanned PDFs • Custom Streams

Layer 0 – Intelligent Analyzer (Proprietary Brain)

Detects device constraints • Analyzes data format • Creates custom parsers on-the-fly • Optimizes for speed/memory/power • Routes intelligently

Key power: Makes SSCA adaptive & edge-ready

Layers 1–4
(MIT Open Source)

Basic parsing → Build semantic graph → Factor repeats → Pack to binary

Role: Turn raw data into structured meaning

Layer 5 – Meaning Compression (Patented)

Ontology primitives & differential encoding

Breakthrough: 15–20% ratios on structured data

Layer 6 – Handover Manager (Patented)

Smart routing: primitives for structured data • fallback to Brotli/zstd/LZ4 for random

Best of both worlds

Layer 7 – Streaming & Scale (v8)

Chunk-by-chunk processing • Incremental graphs • Disk-backing → Handles 1GB+ & live streams

Layer 8 – Multimodal (v8)

Scene graphs from images/video/audio

Layer 9 – Dynamic Learning (v8)

Self-improving primitives

Layers 10–11 – OCR & PDF

Extract text from scanned PDFs/images → semantically compress → reconstruct searchable PDF

Breakthrough: 89–95% compression on scanned documents with perfect text fidelity

OUTPUT
Ultra-Compact .ssca File(s) + Reconstructed PDFs

Lossless • Semantic • Searchable • Edge-efficient • Scalable to petabytes • Fully readable PDFs from scans

Layer 0 – The Brain

Device detection, custom parsers, optimization

Deep Dive →

Layer 5 – Meaning Compression

Ontology primitives & differential encoding

Deep Dive →

Layer 7 – Streaming & Scale

Chunking, incremental graphs, petabyte-ready

Deep Dive →

Layer 8 – Multimodal

Scene graphs from images/video/audio

Deep Dive →

Layer 9 – Dynamic Learning

Self-improving primitives

Deep Dive →

Layers 10–11 – OCR & PDF

Scanned documents → searchable compressed PDFs

Deep Dive →

Full Stack Overview

All layers at a glance

See Overview →