AI Agents

Extract personal data using self-hosted language models

13 nodes 350 138 Automatic trigger
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Workflow Description

Automation that receives text messages through a chat interface, processes them using a locally hosted language model (Ollama), parses and validates the output, then structures the extracted data for storage or downstream actions.

How it works

  1. 1.Receive user input via chat trigger
  2. 2.Send text to local Ollama model for processing
  3. 3.Parse model response and auto-correct extraction errors
  4. 4.Structure extracted data into organized format
  5. 5.Deliver results for storage or further processing

Use cases

  • Extract personal information from customer forms or verbal inquiries
  • Automate data ingestion from unstructured text input

Requirements

  • Ollama server installed and running on local network or machine
  • Stable network connection between n8n and self-hosted model server

Service Value

Ideal as a smart automation service combining integrations and AI to produce ready-to-use results.

Apps Used

Chat Trigger Lm Chat Ollama Output Parser LLM Chain

Details

Trigger Automatic trigger
Nodes 13
Apps 4
Views 350
Downloads 138

How to Use

  1. 1.Click "Download Template"
  2. 2.Open your n8n dashboard
  3. 3.Go to Workflows > Import from File
  4. 4.Select downloaded file and configure credentials

Nodes Used (13)

/

When chat message received

Chat Trigger

#1

Ollama Chat Model

Lm Chat Ollama

#2

Auto-fixing Output Parser

Output Parser Autofixing

#3

Structured Output Parser

Output Parser Structured

#4

Basic LLM Chain

LLM Chain

#5

On Error

No Op

#6

Sticky Note

Sticky Note

#7

Sticky Note1

Sticky Note

#8

Sticky Note2

Sticky Note

#9

Extract JSON Output

Set

#10

Sticky Note3

Sticky Note

#11

Sticky Note6

Sticky Note

#12

Sticky Note7

Sticky Note

#13