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AI & Machine LearningCase study

GhostAI

Autonomous AI Agent Platform

Project Focus
PythonFastAPIPostgreSQLDockerWebSocketVector DatabaseAI/LLM APIs
GhostAI
Persistent vector store
Memory
Docker-isolated sandbox
Execution
Leading AI models
Reasoning
Dozens of integrations
Tools
01

Challenge

Current AI assistants lack persistence and autonomy—they forget context between sessions and require constant human guidance. Building agents that work independently requires solving memory persistence, safe code execution, tool orchestration, and multi-agent coordination.

02

Solution

GhostAI implements a full agent runtime with vector-based persistent memory, a sandboxed code execution environment, and an orchestrator that coordinates multiple specialized agents. Leading AI models provide reasoning, while a tool server exposes dozens of integrations. WebSocket connections enable real-time task monitoring.

03

Results

  • Persistent vector memory across sessions
  • Sandboxed code execution environment
  • Multi-agent task orchestration
  • Dozens of tool integrations
  • Real-time WebSocket monitoring
  • Full audit logging for compliance

System Architecture

Multi-agent platform with persistent memory, tool use, and isolated code execution

frontend
backend
database
service
ai
ReasonExecuteRun codeRememberLog
Agent Console
React dashboard
Orchestrator
FastAPI coordinator
AI Engine
Reasoning layer
Tool Server
External integrations
Code Sandbox
Docker isolation
Vector Store
Persistent memory
PostgreSQL
Task & audit logs

Multi-agent platform with persistent memory, tool use, and isolated code execution

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