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:Built an AI-powered chatbot that handles customer queries automatically using the OpenAI API and Node.js backend. Integrated with webhooks to trigger follow-up automation flows, reducing manual response time by 80% and improving lead response quality.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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There247 is building an AI-powered communications platform that helps service businesses capture missed customer enquiries. Our MVP answers inbound calls when a business is unavailable, captures the customer’s details, creates a clear summary, and sends the business an actionable SMS.
We’re looking for a practical backend developer to support our lead developer across the MVP build. You’ll work on Node.js/TypeScript APIs, Twilio call handling, webhooks, Pipedrive integration, SMS/email notifications, database models, event logging, testing, and AWS deployment support.
This is a fast-moving startup role. We need someone who can work from a detailed specification, build reliable backend features quickly, communicate clearly, and help us deliver a commercially usable MVP.
Natural Language Workflow Editing Title: "Editing AI Workflows Using Chat" Description: "Demo of RAPR AI's chat-based workflow editor — modifying a live workflow and adding nodes through natural language. No manual config, just conversation.
AI-Powered Email Processing & Business Data Extraction (n8n)
Built an automated workflow system using n8n to handle intelligent email processing, retailer data enrichment, and decision-based automation for business operations.
The system runs on a scheduled trigger (every 30 minutes) and processes customer data in a fully automated pipeline. When a user logs in, their data is stored with a pending status. The workflow then retrieves these records, analyzes recent business emails, and extracts key information such as sender domain and transactional details.
Using domain-based logic, the system cross-checks retailer data from a centralized database (Google Sheets). If retailer information is incomplete, the workflow automatically performs web scraping and enrichment to fetch return policies, business details, and relevant metadata before continuing execution.
Once validated, the system parses emails, extracts structured data, triggers external APIs, and marks processed emails accordingly. It ensures idempotent processing by updating statuses and avoiding duplicate handling.
Additionally, the workflow supports continuous monitoring by scanning unread business emails for completed users and processing them in real time.
Key Highlights
Fully automated email parsing & classification system
Dynamic data enrichment from web sources
Domain-based retailer validation logic
Seamless integration with APIs, databases, and Google Sheets
Built for scalability, reliability, and minimal manual intervention
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