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March 2026 Innovation

BrainCode

Mathematical data compression for enterprise AI. BrainCode encodes your data into a compact latent space using a Tabular Autoencoder, removes statistical noise, and seals the result with HMAC-SHA256 — reducing your data footprint by 60–80% while preserving 98%+ reconstruction fidelity.

On-premise only — data never leaves your infrastructure. GDPR Art. 25 compliant.

How BrainCode Works

1
Raw Data
Tabular enterprise data (CSV, Parquet, JSON)
2
Scale + PCA
StandardScaler → PCA whitening (95% variance)
3
Encoder
3-layer PyTorch MLP → 32-dim latent space
4
HMAC Seal
Tenant-specific HMAC-SHA256 integrity seal
5
Compressed
60–80% smaller, noise-free, cryptographically sealed

Compression Estimator

Compression Engine

  • Tabular Autoencoder (PyTorch)
  • 3-layer encoder + decoder MLP
  • BatchNorm + GELU activations
  • Latent dimension: 32
  • PCA whitening (95% variance retained)

Integrity & Security

  • Seal: HMAC-SHA256
  • Tenant-specific derived key
  • Tamper detection on decompression
  • Zero data leaves premises
  • GDPR Art. 25 data minimisation

Performance

  • Compression: 60–80% size reduction
  • Fidelity: 98%+
  • 10× faster ingestion (Arrow pipeline)
  • Works on CSV, Parquet, JSON, dict
  • REST API: /api/v1/braincode

API Quick-Start

# Compress and seal your data
curl -X POST https://brainpredict.ai/api/v1/braincode/compress \
  -H "Content-Type: application/json" \
  -d '{
    "tenant_id": "acme-corp",
    "data": [{"revenue": 142500, "units": 1200, "margin": 0.34}, ...],
    "fit_if_needed": true
  }'

# Response: compressed payload with HMAC seal + compression stats
# {"success": true, "stats": {"compression_ratio": 0.72, "size_reduction_pct": 72.0, ...}}