AI-Powered Product Data Automation

Target Audience

This workflow is ideal for:

• Building Surveyors: Professionals who need to identify and document various objects from images.
• Data Analysts: Individuals looking to automate data enrichment processes using AI.
• Developers: Those interested in integrating AI and automation into their applications, particularly with Airtable and LangChain.
• Businesses: Companies that require efficient data collection and analysis methods to save time and reduce manual work.

Problem Solved

This workflow addresses the challenge of manual data entry and object identification by automating the process of:

• Scanning an Airtable database for product images.
• Using AI to analyze and identify product attributes from images.
• Performing reverse image searches and web scraping to enrich product data.
• Updating the Airtable records with the enriched data, thus saving significant time and improving accuracy.

Workflow Steps

1. Manual Trigger: The workflow starts when the user clicks the "Test workflow" button.
2. Get Applicable Rows: It retrieves rows from the Airtable database that contain product images needing analysis.
3. Analyze Image: The workflow sends the image URL to an AI model to extract attributes like description, model, material, color, and condition.
4. Object Identifier Agent: This agent uses the extracted data and may call tools for further data enrichment if necessary.
5. Actions Router: Based on the identified needs, it routes to either the SERP Google Reverse Image API for image search or the Firecrawl Scrape API for web scraping.
6. Scrape Success Check: It verifies if the scraping was successful and processes the response accordingly.
7. Enrich Product Rows: Finally, the workflow updates the Airtable records with the enriched product data, ensuring all relevant attributes are captured.