The AI industry has a multi-trillion dollar problem. It's running out of high-quality, legally-sound training data. The public internet, once a vast resource, is now a polluted well of synthetic sludge and legal risk. The brute-force era of scraping is over.
Odyssey trains robots through real-time data streaming. Our custom API delivers vision, language, and physics insights directly to your robot's brain, enabling continuous learning and adaptation.
Continuous data flow from vision, language, and physics channels.
End-to-end encryption with NaCl and TLS 1.3 ensures data security.
Models run locally, enabling instant adaptation without cloud dependency.
This is where other platforms have failed. They saw code as a commodity to be hoarded. They tried to boil the ocean and were left with salty, unusable water. They missed the fundamental truth: the value isn't in the code itself, but in the quantifiable intelligence embedded within it.
We are not a data marketplace. We are an AI company that has built the definitive Quality Engine for software. Our technology is the first of its kind to understand and appraise the objective value of code, creating a new, strategic asset class for the AI economy.
We start with a rigorous, objective analysis of structural complexity, token density, and semantic uniqueness using a high-performance vector index.
We then deploy a fine-tuned AI layer that acts as an expert engineer, assessing architectural quality, clarity, and novelty.
Get started with Odyssey by installing the stream package. Requires Python 3.8+ and network connectivity.
pip install odyssey-streamAuthenticate your robot with a unique ID and secret key. All communications are encrypted end-to-end.
from odyssey import Stream
# Initialize with authentication
robot = Stream(robot_id="RX-77", secret_key="a1b2c3d4...")
await robot.start()# Subscribe to vision, language, and physics channels
robot.subscribe(channels=["vision.v3", "language.pro", "physics.real"])@robot.on_data
async def process_data(insight):
decrypted = robot.decrypt(insight)
await robot.brain.update(decrypted["data"])
print(f"Processed: {decrypted['source']['type']}")Configure Odyssey for different environments including cloud and edge deployments.
# Configure for edge deployment
robot.configure(
environment="edge",
latency=15,
cache_size="2GB"
)Contribute high-quality training data to the Odyssey network. All contributions are evaluated by our Quality Engine and rewarded based on their intelligence value.
Our hybrid engine combines quantitative and qualitative analysis to assess the objective value of training data. This engine is origin-agnostic—it doesn't care if code was written by a human or an AI assistant. It only measures one thing: "signal".
If a contribution is complex, unique, and well-engineered, it has high value. If it's generic, simple, or repetitive, it has low value. This is our moat.
Odyssey implements military-grade security with zero-knowledge encryption and blockchain-based proofs.
NaCl for end-to-end encryption, TLS 1.3 for secure transport
Verify data integrity without exposing sensitive information
Low-Rank Adaptation - A technique for efficient fine-tuning of large models
High-performance asynchronous messaging library for distributed systems
Transport Layer Security protocol for encrypted network communications
Networking and Cryptography library for encryption and authentication
Processing data near the source rather than in centralized cloud servers
By using Odyssey, you agree to our terms of service. Please read carefully before integrating our API into your robotic systems.
Your privacy is our priority. We implement zero-knowledge encryption to ensure that even we cannot access your robot's training data. All data is encrypted end-to-end and stored securely.