OpenClaw AI Employee Technical Architecture Diagram
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This diagram illustrates OpenClaw AI's technical architecture from an employee perspective, clearly defining the responsibilities of each technical team in areas such as R&D, platform, data, algorithms, and engineering implementation. Through a clear hierarchy and functional relationships, it reflects how the company organizes its technical resources to support the development and iteration of AI products.
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Intelligent decision-making algorithm
GraphQL
vector database
WebSocket
Sentiment analysis
Slack/Teams
Jira/Asana
Multi-agent collaboration
Knowledge base management
PostgreSQL
Dalog management
OpenClaw AI employee technical architecture diagram
AI employee core functional modules
GPT-4/Claude
Open source model fine-tuning
AI core engine layer
A/B testing
Continuous learning
Multimodal understanding
Basic models and algorithm capabilities
Big Language Model
Workflow orchestration
Data and knowledge layer
Application interface layer
Task execution engine
Knowledge map reasoning
Enterprise knowledge map
Document understanding
Reinforcement learning
Capability service layer
feedback collection
Mail/Calendar
Data storage
Integration adapters
Redis
SDK/CLI
Code generation
Natural language processing
Memory system
API call
API Gateway
model fine-tuning
performance monitoring
Automation of
CRM/ERP
Tool integration
document storage
External services and integration
Elasticsearch
RESTful API
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