How We Helped a US-Based Startup Automate Customer Support

Client Overview

We partnered with a startup based in the United States that provides B2C software. As their customer base grew, their support team struggled to keep up with the rising volume of user queries. The client was looking for a scalable solution to automate customer support without compromising quality, personalization, or accuracy.

Their goals were clear:

Reduce support response time
Provide 24/7 live chat support
Handle repetitive customer queries automatically
Improve overall customer satisfaction

‍

The Challenge

High Support Ticket Volume: 80% of tickets were repetitive and could be answered with existing documentation.
Delayed Responses: Average response time ranged from 12–24 hours.
No After-Hours Support: Customers in different time zones were left waiting.
Burnt-out Support Team: Agents were overwhelmed with low-level queries instead of focusing on high-priority issues.

They needed a smart customer service chatbot that could fix all these issues.

‍

Our Solution: An AI Powered Chatbot

We developed a fully customized AI chatbot for customer support powered by OpenAI’s API. This chatbot was tailored to the client's unique product, tone of voice, and frequently asked questions.

Trained on company-specific documentation, FAQs, and chat history to deliver accurate, human-like answers.
The chatbot knows which page a user is browsing and customises its answers accordingly.
Integrated with a vector database to retrieve context-specific information quickly.
Allows the client to edit chatbot knowledge without touching code.

‍

Technology Stack Behind the AI Chatbot

OpenAI API

Powers the chatbot with context-aware, human-like responses trained on support data, FAQs, and product documentation for high accuracy.

‍

Next.js

Serves as the full-stack framework for building the chatbot backend and frontend, enabling fast development, and seamless server-side logic.

‍

Supabase

Serves as the backend for storing user interactions, vector embeddings, and admin controls—secure, fast, and developer-friendly.

‍

How We Did It: Step-by-Step

We followed a focused and proven process to design, develop, and deploy the AI chatbot— ensuring it delivered real value from day one.

Discovery & Research – We reviewed the client’s support docs, ticket logs, and knowledge base.
Chatbot Training – We fine-tuned GPT-4 with proprietary data and tested responses across all major query types.
Custom UI Integration – Built and embedded a floating chatbot widget that matches their brand design.
Testing & QA – Ran usability tests, edge case prompts, and simulated thousands of conversations.
Ongoing Optimization – We continue to improve the bot with real-time analytics and user feedback.

‍

Results After Implementation

Avg. Response Time

Before

12-24 hours

After

Under 1 sec

Weekly Support Tickets

Before

500+

After

~120(only escalations)

Customer Satisfaction

Before

3.8/5.0

After

4.6/5.0

Support Cost per Chat

Before

$ 2.50

After

~ $ 0.10

Support Cost per Chat

Before

$ 2.50

After

~ $ 0.10

How We Helped a US-Based Startup Automate Customer Support

Client Overview

The Challenge

Our Solution: An AI Powered Chatbot

Technology Stack Behind the AI Chatbot

OpenAI API

Next.js

Supabase

How We Did It: Step-by-Step

Results After Implementation

Interested in a Similar Solution for Your Business?