> ## Documentation Index
> Fetch the complete documentation index at: https://ixoworld-canonical.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Agentic Oracles Architecture

> Build intelligent prediction networks using AI-powered oracles with decentralized identity

<Tip>
  IXO Oracles are autonomous AI agents that provide verifiable services through decentralized identity, secure data storage, and blockchain integration.
</Tip>

## Key Components

<CardGroup>
  <Card title="Identity Layer" icon="fingerprint">
    DID-based domains with verifiable credentials
  </Card>

  <Card title="AI Layer" icon="brain">
    Langraph framework for cognitive workflows
  </Card>

  <Card title="Storage Layer" icon="database">
    Encrypted Matrix rooms and vector stores
  </Card>

  <Card title="Blockchain Layer" icon="cube">
    Impact Hub integration via MultiClient SDK
  </Card>
</CardGroup>

## Oracle Domain

### DID Configuration

<CodeGroup>
  ```json DID Document theme={null}
  {
    "@context": ["https://www.w3.org/ns/did/v1"],
    "id": "did:ixo:oracle/123",
    "verificationMethod": [{
      "id": "#key-1",
      "type": "Ed25519VerificationKey2018",
      "controller": "did:ixo:oracle/123",
      "publicKeyBase58": "..."
    }],
    "service": [{
      "id": "#ai",
      "type": "LangraphService",
      "serviceEndpoint": "https://oracle.emerging.eco/ai"
    }]
  }
  ```

  ```python Create Oracle theme={null}
  from emerging import Oracle, Domain

  # Create oracle domain
  oracle = Oracle.create(
      name="CleanCookingOracle",
      capabilities=["verification", "prediction"],
      controllers=["did:ixo:org/456"]
  )

  # Configure services
  oracle.add_service(
      type="LangraphService",
      endpoint="https://oracle.emerging.eco/ai"
  )
  ```
</CodeGroup>

### Memory Storage

```python theme={null}
from emerging import VectorStore, Matrix

# Initialize vector store
store = VectorStore.create(
    type="weaviate",
    index="oracle_memory",
    schema={
        "class": "Verification",
        "properties": ["context", "decision"]
    }
)

# Create Matrix room
room = Matrix.create_room(
    oracle_id="did:ixo:oracle/123",
    encryption=True
)
```

## AI Workflows

### Langraph Integration

<CodeGroup>
  ````python Verification Flow theme={null}
  from emerging import Langraph, Flow

  # Create verification flow
  flow = Flow.create(
      name="device_verification",
      input_schema={
          "measurements": "DeviceTelemetry",
          "baseline": "BaselineData"
      }
  )

  # Add processing nodes
  flow.add_node(
      "validate_data",
      type="DataValidation",
      rules=validation_rules
  )

  flow.add_node(
      "analyze_patterns",
      type="AnomalyDetection",
      model=anomaly_model
  )

  flow.add_node(
      "verify_compliance",
      type="ComplianceCheck",
      standards=["GS_MMECD_1.0"]
  )

  # Deploy flow
  flow.deploy()

  ```python

  ```javascript
  import { Langraph, Flow } from '@emerging/sdk';

  // Create verification flow
  const flow = await Flow.create({
    name: 'device_verification',
    inputSchema: {
      measurements: 'DeviceTelemetry',
      baseline: 'BaselineData'
    }
  });

  // Add processing nodes
  await flow.addNode({
    name: 'validate_data',
    type: 'DataValidation',
    rules: validationRules
  });

  await flow.addNode({
    name: 'analyze_patterns',
    type: 'AnomalyDetection',
    model: anomalyModel
  });

  await flow.addNode({
    name: 'verify_compliance',
    type: 'ComplianceCheck',
    standards: ['GS_MMECD_1.0']
  });

  // Deploy flow
  await flow.deploy();
  ````
</CodeGroup>