WaveGuard
Zero-Training
Anomaly Detection
Detect anomalies in any data stream using Klein-Gordon wave physics. No training data. No model fitting. No labeled examples. Just send your data and get a physics fingerprint with anomaly scores in milliseconds.
How It Works
WaveGuard treats your data as a wave signal on a 3D lattice and applies the same physics that governs gravitational waves and quantum fields.
Encode to Lattice
Your data is mapped onto a 3D cubic lattice using GOV-01 (Klein-Gordon) encoding. JSON, time-series, tabular — all become wave amplitudes.
Evolve with Physics
The lattice evolves under GOV-01 + GOV-02 wave equations on GPU. Normal data produces stable patterns; anomalies create instabilities and resonances.
Read the Fingerprint
Statistical analysis of the evolved field (energy, chi-well depth, spectral peaks) produces a physics fingerprint. Mahalanobis distance gives the anomaly score.
Works on Any Data
No domain-specific training. The physics doesn't care what your data means — it detects structural anomalies in the signal itself.
Server Monitoring
CPU spikes, memory leaks, latency anomalies. F1 = 0.882 on production metrics.
Crypto Markets
Pump-and-dump detection, wash trading, abnormal volume patterns.
IoT Sensors
Equipment failure prediction, drift detection, environmental monitoring.
Financial Data
Transaction fraud, market manipulation, unusual trading patterns.
Start in 30 Seconds
One POST. One fingerprint. No setup required.
curl -X POST \
"https://api.emergentphysicslab.com/waveguard/v1/scan" \
-H "Content-Type: application/json" \
-d '{
"data": [100, 102, 101, 105, 130, 108, 107],
"encoder": "json"
}'pip install WaveGuardClient
from waveguard_client import WaveGuardClient
client = WaveGuardClient(
base_url="https://api.emergentphysicslab.com/waveguard"
)
result = client.scan(
data=[100, 102, 101, 105, 130, 108, 107],
encoder="json",
)
print(result.is_anomaly) # True
print(result.score) # 0.87
print(result.fingerprint) # Physics fingerprintimport requests
resp = requests.post(
"https://api.emergentphysicslab.com/waveguard/v1/scan",
json={
"data": [100, 102, 101, 105, 130, 108, 107],
"encoder": "json",
},
)
result = resp.json()
print(result["is_anomaly"]) # True
print(result["score"]) # 0.87Pay Per Scan
x402 Micropayments
- USDC on Base L2
- Pay-per-request (no subscription)
- All 37 endpoints
- Built for AI agent workflows
- x402 protocol standard
Direct REST API
- No API key required
- Rate-limited (fair use)
- All endpoints available
- Swagger UI included
- MCP integration ready
Integrate Anywhere
REST API, Python SDK, MCP for AI agents, or x402 micropayments — use whichever fits your stack.
Anomaly detection without the ML pipeline.
No training. No labels. No model drift. Just physics.
Send your first scan now.