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AI Chatbot That Reduces Support by 70% (RAG + OpenAI + Custom Data)
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I designed and deployed a custom AI Agent built to handle real operational workloads — not just chat responses. This system combines reasoning, memory, and tool‑use to execute tasks autonomously, reduce manual overhead, and deliver consistent, high‑quality outputs.
What it does:
Processes inputs and makes decisions without supervision
Runs multi‑step workflows with logic and error‑handling
Integrates with APIs, databases, and internal tools
Summarizes, routes, and evaluates information
Operates asynchronously and scales with workload
Why it matters:
This agent replaces repetitive manual tasks, increases operational clarity, and creates a reliable automation layer that founders can trust. It’s built with security, auditability, and real‑world constraints in mind.
Tech used:
LLMs, embeddings, secure tool‑use, workflow orchestration, async operations, and custom logic modules.
Outcome:
A stable, autonomous system that reduces cognitive load, accelerates execution, and frees teams to focus on higher‑value work.
This is the future and most people still aren't paying attention.
Everyone is talking about AI but very few are actually building with it at this level reasoning, memory, tool-use, real workflows. Not a chatbot. Not a gimmick.
A system that actually WORKS while you sleep.
...
Building an AI-Powered WhatsApp Sales & Support Platform for Businesses
Overview
Wabrix is a WhatsApp automation platform designed to help businesses handle customer conversations at scale using AI. The platform enables brands to automate support, qualify leads, answer FAQs, recover abandoned customers, and manage conversations directly through WhatsApp with a fast, human-like AI assistant.
I led the end-to-end development of the platform, including the AI chat infrastructure, WhatsApp integration system, onboarding flow, automation builder, analytics dashboard, and real-time conversation management tools.
Goal
The main goal was to turn WhatsApp from a manual support channel into an AI-powered operational workflow that could increase response speed, reduce support workload, and improve customer conversion.
From a business perspective, the platform needed to do more than simply auto-reply messages. It had to function as an intelligent sales and support assistant that could:
- qualify leads automatically
- guide customers through buying decisions
- handle repetitive support requests
- recover potential lost sales
- escalate conversations to human agents when needed
The product was designed to help businesses respond instantly while maintaining a natural and branded customer experience.
What I Did
I built the platform from the ground up with a strong focus on scalability, automation, and real-world business usability.
My work included:
- Building the WhatsApp AI chat infrastructure and messaging workflows
- Developing the admin dashboard and conversation management system
- Creating automation flows for support, lead qualification, and customer follow-up
- Integrating WhatsApp Cloud API for real-time messaging
- Designing AI context handling for better response accuracy and brand consistency
- Implementing multilingual support for broader business adoption
- Building analytics and reporting systems for tracking engagement and response performance
- Creating human handoff systems for support escalation
- Developing onboarding flows to simplify setup and adoption for businesses
Workflow / System Design
One of the most important parts of the project was designing the platform as a business workflow system rather than a simple chatbot.
The AI layer needed structured access to:
- customer conversations and message history
- business knowledge and FAQs
- sales and support workflows
- lead qualification logic
- human escalation rules
- response behavior and brand tone
This allowed the AI to operate more like a real support and sales team member instead of a generic assistant.
The platform was designed around operational efficiency: automated responses, structured customer flows, measurable outcomes, and smooth human collaboration when needed.
Implementation
The platform was built using modern full-stack architecture and real-time messaging systems:
- React-based admin dashboard
- WhatsApp Cloud API integration
- AI-powered conversational workflows
- real-time messaging infrastructure
- automation and escalation systems
- analytics and conversation tracking
- multilingual AI response handling
- role-based workspace management
- performance monitoring and reporting tools
Result
The platform successfully helped businesses automate customer communication while improving operational efficiency and response speed.
Businesses were able to:
- reduce manual support workload
- respond to customers instantly
- increase lead engagement
- improve conversion opportunities
- manage conversations more efficiently through centralized workflows
The system achieved extremely fast AI response times, averaging around 17 seconds for automated support interactions.
Outcome
This project demonstrated how AI can be applied to WhatsApp in a practical, business-focused way. not as a gimmick, but as a scalable communication workflow that supports sales, support, and customer experience simultaneously.
The result was a platform that helped businesses operate faster, respond smarter, and create a more seamless customer journey directly inside WhatsApp.
Good work!
AI Hiring Workflow & Candidate Automation System
I built an end‑to‑end AI‑powered hiring workflow that automates the entire candidate lifecycle — from screening to onboarding. This system replaces manual review, inconsistent communication, and slow decision‑making with a clean, structured, and fully automated pipeline.
What it does:
• Screens resumes and applications with role‑specific criteria
• Extracts skills, experience, and red flags automatically
• Generates structured candidate summaries for fast review
• Automates candidate communication and follow‑ups
• Schedules interviews and routes candidates to the right stage
• Delivers onboarding steps and training materials automatically
Why it matters:
Hiring is one of the most chaotic operational areas for most teams. This system turns it into a predictable, auditable workflow that saves hours per week and improves candidate experience.
Tech used:
AI models, embeddings, workflow automation (n8n), async operations, secure data handling, custom scoring logic.
Outcome:
A fast, fair, and scalable hiring pipeline that reduces time‑to‑hire, improves clarity, and eliminates repetitive manual work.
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