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@Zer0pa

Zer0pa

Zero-Point Architecture For Intelligent Machines

Zer0pa

Deterministic compression for structured signals. One geometric architecture, eleven applied domains.

Zer0pa builds codecs that compress domain-specific data — sensor telemetry, hand-pose streams, robot motion, geospatial trajectories, financial time-series, neural signals, biosignals, motion capture, speech prosody, digital ink, and multimodal content — using a unified set of eight geometric primitives.

Every codec guarantees bit-exact deterministic replay. No GPU required. No neural network. No probabilistic reconstruction. What you encode is exactly what you decode, every time.

The Repos

Package Domain Headline
zpe-iot IoT / Sensors 17× compression on real sensor datasets, edge-deployable (Rust + Python)
zpe-xr XR / Hand Tracking 56× compression, sub-mm pose fidelity, 0.025ms latency
zpe-robotics Robotics / Motion 187× compression on LeRobot data, wire-format replay
zpe-geo Geospatial Trajectory codec, sub-metre fidelity, zero dependencies
zpe-ft Financial Data OHLCV + tick-stream codec, ≥13× on synthetic benchmarks
zpe-neuro Neural Signals Extracellular spike-train codec, DANDI-validated
zpe-bio Biosignals ECG + EEG codec in Rust and Python, embedded reference path
zpe-mocap Motion Capture Joint-angle compression, search-without-decode
zpe-prosody Speech Prosody Pitch/rhythm/stress codec, 4/6 gates verified
zpe-ink Digital Ink .zpink stylus codec, >5× vs raw float32
zpe-imc Multimodal Platform 10 modality lanes, 276.8k IMC words/s, integration layer

License

All repos are source-available under SAL v6.0. Free below USD 100M annual gross revenue. Commercial, hosted, or legal-interpretation questions: architects@zer0pa.ai.

Who This Is For

  • Developers building on constrained devices, real-time pipelines, or audit-grade data infrastructure
  • Investors and evaluators conducting technical due diligence on codec IP
  • Grant reviewers assessing computational physics or information-theory research
  • Deep tech engineers who want deterministic, verifiable compression — not black-box approximation

Where to Start

Pick the domain repo closest to your signal type. Each repo has a quickstart, proof artifacts, and benchmark data. ZPE-IMC ties the architecture together across domains.

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  1. ZPE-IMC ZPE-IMC Public

    ZPE-IMC V0.0: MULTIMODAL MULTI-SENSORIAL CODEC: Text | Emojis | Images | Diagrams | Voice | Music | Touch | Taste | Smell | Mental

    Python

  2. ZPE-XR ZPE-XR Public

    ZPE-XR V0.0: DETERMINISTIC XR HAND-STREAM CODEC: Hand Tracking | Pose Compression | ContactPose Benchmark | Gesture Transport | Rust-Backed Wheel

    Python

  3. ZPE-Robotics ZPE-Robotics Public

    ZPE-Robotics V0.0: DETERMINISTIC MOTION KERNEL: Wire-V1 Transport | Replay | Search Without Decode | Anomaly Detection | 187x Real-Data

    Python

  4. ZPE-Neuro ZPE-Neuro Public

    ZPE-Neuro V0.0: DETERMINISTIC NEURAL SIGNAL CODEC: Extracellular Spikes | Neuropixels | DANDI-Anchored | IBL Validated | Spike Train Transport

    Python

  5. ZPE-Geo ZPE-Geo Public

    ZPE-Geo V0.0: DETERMINISTIC GEOSPATIAL CODEC: Trajectory Compression | H3 Hexagonal Roundtrip | Maneuver Search | Fidelity Validation | AIS Baseline

    Python

  6. ZPE-IoT ZPE-IoT Public

    ZPE-IoT V0.0: DETERMINISTIC IOT SENSOR CODEC: 1D Time-Series | Chemosense | 17x Mean Compression | Rust Core | PyO3 Native | Edge-Deployable

    Python

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