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🤖 AI Agent Team Builder

Automate with AI Agent Teams

Multi-model (Claude, Gemini, GPT) + isolated agents + flow automation to transform your business.

Build role-based independent agent teams and automate complex workflows with node-based pipelines.

70%
Average Time Saved
3+
Multi-Model Support
N
Concurrent Agents

3 Service Models

Build agent teams with the optimal approach for your business scale and requirements

Multi-Model

Agent Team Building

Design optimal teams with role-based independent agents using multi-models (Claude, Gemini, GPT).

  • Role-based independent agents
  • Optimal model per task
  • Independent subscription & rate limit
Flow Builder

Agent Flow Design

Automate complex workflows with node-based pipelines (LLM→Agent→Human→Output).

  • Node-based flow builder
  • Human-in-the-loop review
  • Repeatable execution & flow saving
Workspace

Workspace Delivery

Build and deliver an in-house agent operating environment based on Marblo.

  • Kanban board + real-time management
  • Code viewer + multi-terminal
  • Real-time PM feedback injection

Diverse Use Cases

AI solutions as part of your agent team, tailored to your industry and business needs

Agent Team Building Workflow

Systematic process from task analysis to workspace delivery

1

Task Analysis & Decomposition

Analyze business goals and auto-generate task DAG

2

Agent Team Design

Assign optimal models (Claude, Gemini, GPT) by role

3

Flow Building & Testing

Design node-based pipelines and test with real scenarios

4

Workspace Delivery & Operations

Deliver workspace with dashboard monitoring environment

System Architecture

👤

Input

User Request / Data

🎯

Orchestrator

Task DAG / Routing

🤖

Agent Team

Claude Code / Codex / Antigravity

👁

Human Review

PM Feedback

Output

Automated Actions

Tech Stack

Core technologies for multi-model agent teams and flow automation

Agent

Claude Code (Anthropic)

Agent

Codex (OpenAI)

Agent

Antigravity

Protocol

MCP (Model Context Protocol)

Platform

Marblo

Runtime

Node-PTY

AI

Vector DB + RAG

Automation

Flow Engine

Core Features

Isolated agents (independent subscription & rate limit)
Multi-model optimal routing per task
Node-based flow builder
Real-time kanban board
Real-time PM feedback injection
Enterprise-grade security

Frequently Asked Questions

How long does an AI agent build take?

Typically 8 weeks (4 PoC + 4 settlement). Can range 4-12 weeks by complexity. The free diagnostic workshop produces an exact estimate.

What tech stack do you use?

Flask/FastAPI + GCP Cloud Run backend, OpenAI/Claude/Gemini APIs, RAG (Vector DB), and MCP for integrating with your internal systems. Our team operates on Marblo workspace.

Can it integrate with our ERP, CRM?

Yes, via MCP (Model Context Protocol) — connects to filesystems, databases, APIs, Git, and most internal systems.

How much does it cost?

Quoted by scope and requirements. The free diagnostic workshop produces a detailed quote.

Do you provide ongoing operational support?

Yes, 3 months of operational support is included by default — monitoring, tuning, and continuous learning.

Build Your AI Agent Team Today

Explore multi-model agent team + flow automation packages

AI Agent Team Building | Multi-Model Agent Teams + Flow Automation | Hypemarc