Backend automation with Airtable as main source of data

Client
Zeway
Secteur
Automobile
Année
Service
Automatisation

Project summary

Implementation of a set of automations for customer service:

  • Creation of declaration automations: data scraping and form automation - Python, Selenium
  • Implementation of customer review collection automation: creation of a Make scenario for collecting reviews and sending SMS - Make, Airtable, Twilio
  • Data collection automation: automation, reconciliation, and processing of data between different SaaS to always have real-time data - API, Airtable, Make, Python, JavaScript
  • Creation of Airtable automations: management of external APIs and data reprocessing in Airtable - Airtable Script
  • Deployment of automations: deployment of Python functions in the cloud - AWS Lambda
  • Document OCR (Optical Character Recognition): AWS Textract
  • Webapp: creation of a webapp to trigger automations on demand - Django, AWS Elastic Beanstalk

Technologies used

  • Zapier
  • Make
  • Airtable
  • Javascript
  • Docker
  • AWS Lambda
  • AWS
  • Python

Case studies

Make, Airtable and backend automation

The service aimed to enhance existing workflows using Make by integrating them with an established Airtable base. Solutions included refining these workflows, managing APIs with external tools like Edusign, and providing guidance on automation creation.

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