Agent Hive Architecture

🏠 Main System Overview

AGENT HIVE (Mac Mini/Studio)

Agent
Amber

Agent
B

Agent
C

Agent
D

AgentS
GUI

Tier 1: Personal Memory
(SQLite per agent)

sync

Tier 2: Shared Knowledge Server
(Postgres + pgvector)

cache

Tier 3: Hot Cache (Redis)
Sub-millisecond reads

📊 Embedding
Model

💓 Heartbeat
LLM

🔀 LiteLLM
Router

LAN Connection

🎮 GPU Server
(RTX 5090)
UI-TARS-1.5-7B

🔄 Memory Pipeline

💬
Conversations

🔍
Auto-Extract

📄
Memory Items

🏷️
Auto-Categorize

🕸️
Knowledge Graph

Memory Item Types

📊 Profile: "Xcite uses Shopify integration"

📅 Event: "Q4 2025 tax filing completed Jan 15"

🧠 Knowledge: "HST rate is 13% in Ontario"

🎯 Behavior: "Client prefers email over phone"

🛠️ Skill: "Can process AP invoices in ERPNext"

⚡ Dual Retrieval System

⚡ RAG Path

Query → Embed → Vector Search → Results

Fast, milliseconds

🧠 LLM Path

Query → Reason → Deep Search → Results

Deep, seconds

🏢 Deployment Profiles

🏦 Accounting Firm

Strategy: 1 agent per client, strict isolation

Client A Agent

Client B Agent

Client C Agent

Complete client data separation, compliance-ready

🏬 Normal Company

Strategy: 1 agent per role, shared knowledge

HR Agent

Sales Agent

Finance Agent

Cross-department collaboration, unified workflows

💻 Hardware Targets

Mac Mini M4

Memory: 16-64GB
Capacity: 5-10 agents
Use Case: Small teams, startups

Mac Studio TB5

Memory: 128-512GB
Capacity: 10-20 agents
Use Case: Medium companies

GPU Server

Hardware: RTX 5090
Purpose: Vision + grounding models
Function: GUI automation

🛣️ Development Roadmap

Phase 1: Core Memory Engine

Weeks 1-2

Build three-tier memory system with SQLite, PostgreSQL, and Redis. Implement basic agent communication and memory synchronization.

Phase 2: Auto-Categorization

Weeks 3-4

Deploy semantic analysis pipeline with auto-extraction and intelligent categorization. Implement knowledge graph relationships.

Phase 3: Intent Prediction

Weeks 5-6

Add pattern monitoring and predictive capabilities. Enable proactive suggestions and anticipatory agent behaviors.

Phase 4: Multi-Hive Federation

Week 7+

Scale beyond single machines. Implement cross-hive communication, distributed knowledge sharing, and enterprise-grade deployment.