Move blockchain app READMEs to centralized documentation

- Relocate blockchain-event-bridge README content to docs/apps/blockchain/blockchain-event-bridge.md
- Relocate blockchain-explorer README content to docs/apps/blockchain/blockchain-explorer.md
- Replace app READMEs with redirect notices pointing to new documentation location
- Consolidate documentation in central docs/ directory for better organization

docs/apps/agents/ai-engine.md

@@ -0,0 +1,179 @@
+# AI Engine
+
+## Status
+✅ Operational
+
+## Overview
+AI engine for autonomous agent operations, decision making, and learning capabilities.
+
+## Architecture
+
+### Core Components
+- **Decision Engine**: AI-powered decision making module
+- **Learning System**: Real-time learning and adaptation
+- **Model Management**: Model deployment and versioning
+- **Inference Engine**: High-performance inference for AI models
+- **Task Scheduler**: AI-driven task scheduling and optimization
+
+## Quick Start (End Users)
+
+### Prerequisites
+- Python 3.13+
+- GPU support (optional for accelerated inference)
+- AI model files
+
+### Installation
+```bash
+cd /opt/aitbc/apps/ai-engine
+.venv/bin/pip install -r requirements.txt
+```
+
+### Configuration
+Set environment variables in `.env`:
+```bash
+AI_MODEL_PATH=/path/to/models
+INFERENCE_DEVICE=cpu|cuda
+MAX_CONCURRENT_TASKS=10
+LEARNING_ENABLED=true
+```
+
+### Running the Service
+```bash
+.venv/bin/python main.py
+```
+
+## Developer Guide
+
+### Development Setup
+1. Clone the repository
+2. Create virtual environment: `python -m venv .venv`
+3. Install dependencies: `pip install -r requirements.txt`
+4. Download or train AI models
+5. Configure model paths
+6. Run tests: `pytest tests/`
+
+### Project Structure
+```
+ai-engine/
+├── src/
+│   ├── decision_engine/     # Decision making logic
+│   ├── learning_system/     # Learning and adaptation
+│   ├── model_management/    # Model deployment
+│   ├── inference_engine/    # Inference service
+│   └── task_scheduler/      # AI-driven scheduling
+├── models/                  # AI model files
+├── tests/                   # Test suite
+└── pyproject.toml           # Project configuration
+```
+
+### Testing
+```bash
+# Run all tests
+pytest tests/
+
+# Run specific test
+pytest tests/test_inference.py
+
+# Run with GPU support
+CUDA_VISIBLE_DEVICES=0 pytest tests/
+```
+
+## API Reference
+
+### Decision Making
+
+#### Make Decision
+```http
+POST /api/v1/ai/decision
+Content-Type: application/json
+
+{
+  "context": {},
+  "options": ["option1", "option2"],
+  "constraints": {}
+}
+```
+
+#### Get Decision History
+```http
+GET /api/v1/ai/decisions?limit=10
+```
+
+### Learning
+
+#### Trigger Learning
+```http
+POST /api/v1/ai/learning/train
+Content-Type: application/json
+
+{
+  "data_source": "string",
+  "epochs": 100,
+  "batch_size": 32
+}
+```
+
+#### Get Learning Status
+```http
+GET /api/v1/ai/learning/status
+```
+
+### Inference
+
+#### Run Inference
+```http
+POST /api/v1/ai/inference
+Content-Type: application/json
+
+{
+  "model": "string",
+  "input": {},
+  "parameters": {}
+}
+```
+
+#### Batch Inference
+```http
+POST /api/v1/ai/inference/batch
+Content-Type: application/json
+
+{
+  "model": "string",
+  "inputs": [{}],
+  "parameters": {}
+}
+```
+
+## Configuration
+
+### Environment Variables
+- `AI_MODEL_PATH`: Path to AI model files
+- `INFERENCE_DEVICE`: Device for inference (cpu/cuda)
+- `MAX_CONCURRENT_TASKS`: Maximum concurrent inference tasks
+- `LEARNING_ENABLED`: Enable/disable learning system
+- `LEARNING_RATE`: Learning rate for training
+- `BATCH_SIZE`: Batch size for inference
+- `MODEL_CACHE_SIZE`: Cache size for loaded models
+
+### Model Management
+- **Model Versioning**: Track model versions and deployments
+- **Model Cache**: Cache loaded models for faster inference
+- **Model Auto-scaling**: Scale inference based on load
+
+## Troubleshooting
+
+**Model loading failed**: Check model path and file integrity.
+
+**Inference slow**: Verify GPU availability and batch size settings.
+
+**Learning not progressing**: Check learning rate and data quality.
+
+**Out of memory errors**: Reduce batch size or model size.
+
+## Security Notes
+
+- Validate all inference inputs
+- Sanitize model outputs
+- Monitor for adversarial attacks
+- Regularly update AI models
+- Implement rate limiting for inference endpoints