Freelancers using HubSpot in KarnatakaFreelancers using HubSpot in Karnataka
Digital Marketing Expert
Digital Marketing Expert
Helping B2B businesses unlock growth with AI & Automations
$5k+
Earned
5x
Hired
5.0
Rating
17
Followers
Helping B2B businesses unlock growth with AI & Automations
Your Webflow partner for conversion-first, scalable websites
$5k+
Earned
2x
Hired
5.0
Rating
14
Followers
Your Webflow partner for conversion-first, scalable websites
I turn websites and products into conversions and cash.
I turn websites and products into conversions and cash.
Java Engineer Building AI Automations & Integrations
New to Contra
Java Engineer Building AI Automations & Integrations
Cover image for AI Document Intelligence & Invoice
AI Document Intelligence & Invoice Processing Platform Description Built an AI-powered document intelligence platform designed to automate invoice processing, document classification, data extraction, and approval workflows. The system uses AI, OCR, and workflow automation to process business documents automatically, eliminating manual data entry and reducing processing delays across finance and operations teams. By integrating with existing databases and business systems, the platform transforms unstructured documents into actionable business data. Key Features • AI-powered document analysis • Invoice data extraction • OCR-based document processing • Automated approval workflows • Purchase order matching • Vendor management integration • Document classification • Data validation system • Real-time processing dashboard • Automated reporting and audit trails Business Impact ✓ Reduced manual data entry ✓ Faster invoice processing ✓ Reduced processing errors ✓ Improved financial visibility ✓ Faster approval cycles ✓ Reduced operational costs ✓ Increased productivity across teams Technology Stack • Java • Spring Boot • PostgreSQL • OpenAI API • OCR Processing • REST APIs • Workflow Automation • Analytics Dashboard Results • Automated document processing workflows • Reduced invoice processing time by approximately 75% • Improved data accuracy • Reduced manual administrative effort • Accelerated approval and payment cycles This solution demonstrates how AI-powered document intelligence can automate finance and operational processes while improving accuracy, compliance, and efficiency.
0
36
Cover image for AI Customer Support Assistant
Built an
AI Customer Support Assistant Built an AI-powered customer support platform designed to automate customer interactions, reduce support workload, and provide instant assistance using company documentation and knowledge base content. The system leverages OpenAI, enterprise knowledge bases, and backend automation to deliver accurate, context-aware responses while seamlessly escalating complex issues to human agents when needed. Key Features: • OpenAI-powered conversational assistant • Knowledge base search and retrieval • FAQ automation system • Context-aware customer responses • Human escalation workflow • Multi-channel support integration • Customer interaction analytics • Real-time response monitoring • REST API architecture • Enterprise-grade backend services Business Impact: ✓ Reduced repetitive support workload ✓ Faster customer response times ✓ 24/7 automated customer assistance ✓ Improved customer satisfaction ✓ Consistent support experiences ✓ Lower operational costs ✓ Increased support team efficiency Technology Stack: • Java • Spring Boot • PostgreSQL • OpenAI API • REST APIs • Docker • Maven • Knowledge Base Integration Results: • Automated approximately 80% of common support requests • Reduced average response time from hours to seconds • Reduced manual support workload by approximately 60% • Improved scalability without increasing support staff This solution demonstrates how AI-powered customer support systems can improve customer experience while significantly reducing operational overhead.
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46
Automation Consultant — n8n & Make.com | Lead Intake Systems
New to Contra
Automation Consultant — n8n & Make.com | Lead Intake Systems
Cover image for AI-Powered Lead Qualification System —
AI-Powered Lead Qualification System — Zero Manual Data Entry Built an end-to-end lead capture and qualification system for a B2B service business using Make.com (http://Make.com), OpenAI GPT-4, and HubSpot. THE PROBLEM: The sales team was manually copying lead data from forms into CRM, losing 6+ hours per day and missing hot leads entirely. By the time a rep reached out, the prospect had already talked to 3 competitors. THE SYSTEM I BUILT: → CAPTURE: Typeform webhook triggers automation the instant a form is submitted → QUALIFY: OpenAI GPT-4 scores lead intent (1-10) based on message content, budget signals, and role seniority → ENRICH: Apollo.io (http://Apollo.io) API appends company size, revenue, tech stack, and LinkedIn URL automatically → ROUTE: Hot leads (score 7+) create HubSpot deals + instant Slack alert to assigned sales rep with full context → NURTURE: Cold leads enter a 7-day email sequence before sales touches them → SYNC: Bi-directional sync between HubSpot and Google Sheets reporting dashboard for real-time pipeline visibility THE RESULTS: • Lead-to-CRM time: 4 hours → 90 seconds • Sales rep prep time per lead: 15 minutes → 30 seconds • Data loss rate: 0% • Sync accuracy: 99.7% TECH STACK: Make.com (http://Make.com) | OpenAI GPT-4 | HubSpot | Apollo.io (http://Apollo.io) | Slack | Google Sheets | Typeform WHY THIS WORKS: Sales teams shouldn't do data entry. This system ensures every lead is scored, enriched, and routed before the prospect even closes the Typeform tab.
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14
Cover image for Agency Onboarding Automation — From
Agency Onboarding Automation — From Contract to Project Launch Without Manual Setup Built a client onboarding machine for a digital agency that eliminates 2+ hours of manual admin every time a new client signs. THE PROBLEM: New client signs the contract → account manager manually creates a Slack channel, Google Drive folder, Asana project, and sends a welcome email 2 days later. Clients felt ignored. Projects started slow. Project managers wasted hours on setup instead of strategy. THE SYSTEM I BUILT: → TRIGGER: PandaDoc/HelloSign contract signature instantly fires webhook → QUALIFY: Parse contract value, service type (SEO, PPC, Web Design), and team size to determine onboarding tier (Standard vs. Premium) → CREATE: Auto-generate Slack channel with client + internal team, Google Drive folder structure with template documents, and Asana project from pre-built template with all milestones → ASSIGN: Push client data to HubSpot CRM, notify finance team in Slack, and assign project manager based on current workload and expertise match → WELCOME: Client receives personalized welcome email with project timeline, team contacts, kickoff meeting link, and onboarding checklist within 10 minutes of signing → SYNC: All project data synced to agency dashboard for leadership visibility THE RESULTS: • Onboarding initiation: 48 hours → 10 minutes • Admin time per new client: 2 hours → 5 minutes • Client satisfaction score (onboarding phase): +40% • Project setup consistency: 100% across all teams TECH STACK: Make.com (http://Make.com) | PandaDoc | Slack | Google Drive | Asana | HubSpot | Google Workspace WHY THIS WORKS: First impressions are everything. This system makes clients feel like they're working with a machine-precision agency from minute one — because they are.
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23
Cover image for E-Commerce Auto-Fulfilment System — From
E-Commerce Auto-Fulfilment System — From Order to Label Without Touching a Spreadsheet Built a fully automated order-to-fulfillment pipeline for a D2C brand selling across Shopify, Amazon, and their own store. THE PROBLEM: The operations team manually copied orders into spreadsheets, checked inventory against 3 separate sources, created shipping labels one by one, and updated tracking numbers by hand. 3 hours of daily grunt work. 8% error rate. Delayed shipments. Angry customers asking "where is my order?" THE SYSTEM I BUILT: → CAPTURE: Shopify order webhook fires instantly on every purchase. Amazon SP-API pulls orders every 15 minutes into the same pipeline. → VALIDATE: Auto-check inventory in Google Sheets. Flag low-stock SKUs for reorder. Route expedited orders to priority queue. → PROCESS: Generate shipping label PDF automatically via Shiprocket API. Create invoice in Zoho Books. Update inventory count across all channels in real-time. → SYNC: Push order status, tracking number, revenue data, and shipping cost to master Google Sheets dashboard for ops visibility. → NOTIFY: Customer receives automated email/SMS with tracking link within 5 minutes of order confirmation. → ALERT: Operations manager gets daily summary + instant alert on failed orders with retry logic and error context. THE RESULTS: • Manual processing time: 3 hours/day → fully autonomous • Order processing errors: 8% → 0.2% • "Where is my order?" support tickets: -60% • Scales to 10,000+ orders/month without adding staff TECH STACK: Make.com (http://Make.com) | Shopify | Amazon SP-API | Google Sheets | Shiprocket | Zoho Books | Twilio | PDF Generator WHY THIS WORKS: E-commerce margins are thin. Every minute of manual processing and every fulfillment error eats profit. This system runs 24/7 without breaks, mistakes, or overtime pay.
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17
Cover image for Real Estate Auto-Response System —
Real Estate Auto-Response System — Capture Every Inquiry in 60 Seconds Designed a 24/7 inquiry response engine for a real estate agency handling 50+ daily leads across property portals, Facebook, and WhatsApp. THE PROBLEM: Agents were responding to inquiries 4-6 hours later. By then, prospects had already contacted 3 competitors and scheduled viewings elsewhere. The agency was bleeding money on ad spend but losing deals to response speed. THE SYSTEM I BUILT: → CAPTURE: All form submissions and WhatsApp messages hit a unified n8n webhook → QUALIFY: Parse budget range, location preference, and property type from natural language inquiry text using regex + AI classification → MATCH: Query Airtable inventory database and return top 3 matching listings based on budget, location, and availability → RESPOND: Send personalized WhatsApp auto-reply with listing photos, prices, and agent contact within 60 seconds — 24/7, even at 2 AM → LOG: Every conversation automatically logged to Airtable CRM with full context → FOLLOW-UP: Create follow-up task with reminder for agent if no response within 24 hours → ALERT: Agent gets mobile Slack notification with full inquiry context, suggested response, and client LinkedIn profile THE RESULTS: • First response time: 4 hours → under 60 seconds • Inquiries lost to delay: 0 • Agent conversations handled per day: 3x increase • Listing view-to-meeting conversion: +35% TECH STACK: n8n | Airtable | WhatsApp Business API | Google Forms | Slack WHY THIS WORKS: In real estate, speed wins. This system ensures every inquiry gets a personalized, instant response with matching listings — while the prospect is still interested.
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Generalist, Founder and Growth guy for Startups!
2x
Hired
4
Followers
Generalist, Founder and Growth guy for Startups!