Infrastructure

Scalable Media Infrastructure.
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Proprietary GL-based processing for global platforms. Secure, frame-accurate, and optimized for high-performance pipelines.

Architecture X-Ray — GL Renderer / Neural Layer / API Gateway
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Enterprise Grade

Built for Scale.

Deterministic Performance

Zero-latency media manipulation. Every frame is processed with mathematical precision.

Architecture Scalability

Optimized for high-scale GPU clusters. Elastic scaling for enterprise-level demand.

Radical Cost Reduction

Up to 3x faster than standard FFmpeg-based cloud pipelines. Lower compute, higher throughput.

Security & Sovereignty

Deploy on private clusters with dedicated 24/7 technical support. Your data never leaves your infrastructure.

The Core Stack

Modular Working Units.

Each unit integrates independently or orchestrates as a full pipeline.

Unit 01

Neural Visual Perception

  • AnyObject Segmenter — Natural language driven object detection with pixel-accurate RLE-encoded segmentation.
  • Vocabulary Perceptor — Temporal object tracking across video streams with visual and semantic embedding generation.
  • Universal Segmenter — High-fidelity point-and-stroke tracking for complex visual isolation and masking.
Neural Visual Perception

Unit 02

Kinetic & Temporal Analysis

  • Motion Analyzer — Extracting optical flow, motion vectors, and camera trajectory.
  • Temporal Consistency — Ensuring pixel-level persistence across variable frame rates.
  • Saliency Mapping — Calculating visual importance scores for intelligent auto-cropping and focus-tracking.
Kinetic & Temporal Analysis

Unit 03

Acoustic Intelligence

  • Stem Separator — High-fidelity isolation of vocals, drums, bass, and instruments for deep audio re-composition.
  • Structural Detector — Self-Similarity Matrix (SSM) analysis for identifying chorus, verse, and bridge transitions.
  • Event Perceptor — Detection of specific acoustic triggers — from drops and claps to environmental sound events.
Acoustic Intelligence

Unit 04

Semantic & Multi-modal Encoding

  • Hybrid Semantic Encoder — Dense and sparse embedding generation for transcripts and text-based search.
  • Audio-Visual Embedder — Multi-modal vectorization for semantic search and reranking across heterogeneous media libraries.
  • Context Injection — Enhancing embedding quality through source-level metadata and temporal context.
Semantic & Multi-modal Encoding

Developer Experience

Built for Engineers.

Native SDKs for Python, Rust, and Ruby. Full API reference and documentation. 

# Unit 03: Acoustic Event Detection
from ferment import AudioEngine, AcousticEventInput

result = AudioEngine.process(
    AcousticEventInput(
        source="track_01.mp3",
        target="beats"
    )
)

for event in result.events:
    print(f"Beat at {event.timestamp}ms — confidence: {event.score}")
API Reference SDK Binaries System Status

Scale Your Pipeline.

Tell us about your media pipeline. We'll show you what the Engine can do.