# Orchestrate multi-agent energy optimization with OpenAI: n8n workflow

> Started by an event in a connected app. It calls services over plain HTTP rather than through connectors. It hands the judgement calls to Claude and OpenAI.

Source: https://millionrounds.com/workflow/orchestrate-multi-agent-energy-optimization-with-openai (Millionrounds; every figure on the page links to its filing or article)

[Automation library](https://millionrounds.com/workflows) · [AI assistants](https://millionrounds.com/workflows?category=AI+assistants#library)

# Orchestrate multi-agent energy optimization with OpenAI

Started by an event in a connected app. It calls services over plain HTTP rather than through connectors. It hands the judgement calls to Claude and OpenAI. 25 steps, 1 branch: large, and worth reading before you trust it with anything live.

Large Calls a model: Claude, OpenAI

[Download free](https://millionrounds.com/login?next=%2Fapp%2Fworkflow%2Forchestrate-multi-agent-energy-optimization-with-openai)

**25 steps** Large: read it before trusting it with anything live

**1** Branch: places the flow splits

**0** Loops or waits

**0** Services by connector: it calls them over plain HTTP

## The flow

Starts it 1 Model 19 Logic 4 Service 1

The steps in the order they run, from what starts it.

- 1 **Initialize System** Manual trigger *Starts it*
- 2 **GPT Model - Perception** Lm Chat Open Ai *Model*
- 3 **Perception Output Parser** Output Parser Structured *Model*
- 4 **GPT Model - Energy** Lm Chat Open Ai *Model*
- 5 **Thermodynamic Calculator** Tool Calculator *Model*
- 6 **Energy Analysis Tool** Tool Code *Model*
- 7 **Energy Output Parser** Output Parser Structured *Model*
- 8 **GPT Model - Planning** Lm Chat Open Ai *Model*
- 9 **Planning Output Parser** Output Parser Structured *Model*
- 10 **Claude Model - Execution** Lm Chat Anthropic *Model*
- 11 **Execution Output Parser** Output Parser Structured *Model*
- 12 **Claude Model - Validation** Lm Chat Anthropic *Model*
- 13 **Validation Output Parser** Output Parser Structured *Model*
- 14 **Claude Model - Execution1** Lm Chat Anthropic *Model*
- 15 **Perception Agent** Agent *Model*
- 16 **Energy Optimization Agent** Agent *Model*
- 17 **Planning Agent** Agent *Model*
- 18 **Execution Agent** Agent *Model*
- 19 **Validation Agent** Agent *Model*
- 20 **Recalibration Agent** Agent *Model*
- 21 **Route by Validation** Switch *Logic*
- 22 **Send Alert** Http Request *Service*
- 23 **Generate System Report** Set *Logic*
- 24 **Merge Final Results** Merge *Logic*
- 25 **Final System State** Set *Logic*

## How it's built

- **Starts on:** An event in a connected app
- **Steps:** 25, with 1 branch
- **Size:** Large: read it before trusting it with anything live
- **Connects to:** Nothing by connector; it calls services over plain HTTP
- **Model:** Claude, OpenAI

## Questions

What does it need to run?

An n8n account, and a key for Claude and OpenAI. You connect your own accounts after importing it; none are included.

What starts it?

It starts on an event in a connected app.

Does it use AI?

Yes. It calls Claude and OpenAI. Model calls are billed by the provider, not by n8n.

How long does it take to set up?

Take your time. At 25 steps it is large: read it before trusting it with anything live.

How do I import it?

Copy the workflow, open a new workflow in n8n and paste. The steps appear on the canvas, ready for your own accounts.

**Before you run it**

Nothing here has been tested by us. It is somebody's working automation, read and described from its own steps. Treat the connections it wants as a list of accounts it will touch, and read the 25 steps before you point it at anything that matters.

## Run it in n8n

- **Create your n8n account** Free to start. n8n is where the workflow runs. [Create an n8n account ↗](https://millionrounds.com/n8n)
- **Download the workflow** Free with a Millionrounds account. [Download free](https://millionrounds.com/login?next=%2Fapp%2Fworkflow%2Forchestrate-multi-agent-energy-optimization-with-openai)
- **Paste it into n8n** Open a new workflow in n8n and paste. Then connect your own accounts.

Stored with the author's traces removed: canvas notes, instance identifiers, saved credential names and any live document they had left behind.

## Workflows like it

Also ai assistants, with the same services where possible, closest in size first.

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- [**Automate Job applications with Gemini and OpenAI** 25 steps · calls a model · Gmail](https://millionrounds.com/workflow/automate-job-applications-with-gemini-and-openai)
- [**Automating WhatsApp replies with Go High Level and Redis** 25 steps · calls a model · Google Drive, Redis](https://millionrounds.com/workflow/automating-whatsapp-replies-with-go-high-level-and-redis)
- [**Build a self-updating RAG system with OpenAI and Qdrant** 25 steps · calls a model · Google Drive, Qdrant](https://millionrounds.com/workflow/build-a-self-updating-rag-system-with-openai-and-qdrant)
- [**Building RAG chatbot for movie recommendations with Qdrant** 25 steps · calls a model · GitHub, Qdrant](https://millionrounds.com/workflow/building-rag-chatbot-for-movie-recommendations-with-qdrant)