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 Google Gemini, Airtable and completes multi-step tasks for you automatically — the kind of work you'd otherwise hand to a virtual assistant.
16
Nodes
3
Integrations
16
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
When clicking ‘Test workflow’· manualTrigger
Google Gemini Chat Model For Summarization· lmChatGoogleGemini
Webhook HTTP Request· toolHttpRequest
Google Gemini Chat Model· lmChatGoogleGemini
Google Gemini Chat Model for AI Agent· lmChatGoogleGemini
Set Bright Data Zone· set
Indeed Summarizer· chainSummarization
Indeed Expert AI Agent· agent
Markdown to Textual Data Extractor· chainLlm
Airtable· airtable
Loop Over Items· splitInBatches
Wait· wait
If Link field is not empty· if
Perform Indeed Web Request· httpRequest
💼 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 Google Gemini, HTTP / REST API, Airtable 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.