AI that understands the physical world

Naturecode gives AI eyes to see, ears to hear, and senses to feel the real world — through any device, sensor, or signal. A decentralized world model built to understand Earth.

Explore API
Naturecode Earth
A decentralized world model

Naturecode Earth is a decentralized world model — a constellation of domain-expert models that understand the physical world across modalities. An intelligent inference router classifies incoming data, routes it to the right expert, and composes structured understanding. The model learns continuously through data accumulation and few-shot adaptation.

Modalities
Vision
Object detection, segmentation, and visual identification from images and camera feeds.
Audio
Speech recognition, sound classification, and acoustic event detection.
Video
Video understanding, temporal reasoning, and motion analysis.
Depth
Monocular depth estimation, surface normals, and 3D spatial understanding from images and video.
TimeSeries
Forecasting and anomaly detection across sensor telemetry and sequential data.
Text
Semantic understanding, classification, and embedding generation.
OCR
Document text extraction with word-level bounding boxes and confidence scores.
Few-Shot
Learn new categories from a few examples. No retraining required.
Protocols
High Performance
gRPC + Protobuf for structured, high-throughput data ingestion.
Universal
REST / HTTP with JSON for broad device and integration support.
AI Agents
MCP (Model Context Protocol) for AI agent tool use via Streamable HTTP.
IoT
MQTT for lightweight sensor and embedded device communication.
Real-Time
WebSocket for bidirectional streaming and live data feeds.
Naturecode Data
Unified data layer and model memory

Naturecode Data is a managed data layer spanning timeseries, vector, graph, relational, key-value, document, and streaming storage. It serves as both persistent storage for device and sensor data, and as memory for Naturecode Earth — embeddings, knowledge graphs, historical patterns, and working state.

Data Types
TimeSeries
Sensor telemetry, metrics, and temporal data at scale.
Vector
Embedding storage and similarity search across modalities.
Graph
Entity relationships and knowledge representation.
Relational
Structured platform state, identity, and configuration.
Key-Value
Caching, sessions, and fast-access working memory.
Document
Flexible schemas for device configs and inference results.