A 27-step ai & agents automation, triggered by manual, connecting HTTP / REST API, OpenAI (LLM), OpenAI, Google Sheets, Google Drive, with built-in AI reasoning.
In plain terms: this is an AI assistant that works on demand. It uses AI to understand and generate content, so it handles judgement-style work, not just moving data. It connects to OpenAI (LLM), OpenAI, Google Sheets, Google Drive and completes multi-step tasks for you automatically — the kind of work you'd otherwise hand to a virtual assistant.
27
Nodes
5
Integrations
30
Connections
Manual
Trigger
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The real node graph exported from n8n — triggers (green), AI nodes (violet), services and logic — laid out as they run.
⚙️ How it works
OpenAI Chat Model· lmChatOpenAi
Call Fal.ai API (WAN2.2)1· httpRequest
When clicking ‘Execute workflow’· manualTrigger
Describe Each Scene for Vid· agent
Structured Output Parser· outputParserStructured
Get Data· googleSheets
Veo· httpRequest
setImgeURL· set
Loop Over Items1· splitInBatches
Call Fal.ai API (nannoBanana)1· httpRequest
HTTP Request· httpRequest
Wait for the video1· wait
Get img status· httpRequest
uploadImagetoGdrive1· googleDrive
💼 Business analysis
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Business use case
Deploys an autonomous AI agent that can reason over instructions, call tools, and take multi-step actions on behalf of a team — replacing repetitive knowledge work. It orchestrates HTTP / REST API, OpenAI (LLM), OpenAI, Google Sheets, Google Drive so a single natural-language request becomes a completed task.
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Market need
Businesses are racing to put AI agents to work but lack the engineering to wire models to their real tools and data. This delivers that wiring as a ready-to-run asset.
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Market value
Custom AI-agent builds are quoted at $3,000–$15,000+ by agencies, with managed retainers on top. As a productised template it commands premium one-time or subscription pricing.