AI Chatbot for 10K+ Daily Website Consultation
Ecommerce - Japan - Software Development - 5 Members - 5 Months
Website consultation is no longer judged on speed alone. As user access grows, businesses also need answers that stay consistent, reliable, and grounded in prepared content. This was the business goal behind the AI chatbot system: scalable website consultation with controlled answer quality. Working closely with the client, Newwave Solutions built a knowledge grounded chatbot that connects the client’s provided question data with vector-based analysis and OpenAI Model integration. The system supports natural user conversations, customizable chat UI and direct consultant fallback. In live operation, the product successfully served more than 10K accesses a day.
Client Context
A Japanese client wanted to turn its website into an AI powered consultation hub as traffic and user inquiries increased.
The system needed to answer common questions based on provided question sets, while still allowing handover to human consultants for purchase support or complex requests. To support future expansion, the solution was designed as a SaaS service that could be embedded into customer or partner websites, with client control over chatbot training and UI elements such as the chat frame, window and interaction button.
Business Stakes
The client was not simply looking for a chatbot that could reply to users. They needed a scalable consultation model that could handle growing inquiry volume. It also had to reduce pressure on human consultants while maintaining consistent answers across repeated questions. Because the product was designed as a SaaS based service, the chatbot also had to be manageable, adaptable, and reliable enough to support different website environments.
As website access increased, a fully manual consultation model would be harder to expand. The chatbot needed to answer repeated questions from provided question sets while keeping consultants available for more complex cases.
Users asking similar questions needed to receive aligned answers, so the business could maintain a reliable consultation experience across high inquiry volume.
AI generated answers had to stay grounded in prepared knowledge to avoid irrelevant responses, unnecessary review effort and loss of user confidence.
The system needed to handle large daily access volumes without turning every user interaction into a manual support task.
Direct consultant chat still had to remain available for complex or sensitive cases, preserving service quality when AI was not the right channel.
Our Approach
Newwave Solutions structured the product as a controlled AI consultation workflow. Common website inquiries could be answered from the client’s provided question data while direct consultant chat remained available for cases requiring human support. To keep responses relevant and manageable, vector-based analysis connected to each user's question with suitable provided content before OpenAI Model generated a conversational answer. Beyond response generation, the system also included chatbot response training, chat UI customization and consultant fallback. This turned the product into a practical AI consultation service for daily website operations and SaaS service model.
Technical Decisions
PHP Development
PHP gave the client a practical foundation to develop and integrate the chatbot service into website environments without adding unnecessary delivery complexity.
MySQL Database
MySQL provided a practical database foundation for managing chatbot question data and related records, supporting the client in operating the chatbot as a configurable website service.
WebSocket
WebSocket kept conversations responsive in real time, which was important for maintaining a smooth consultation experience across both AI chat and direct consultant support.
Vector-Based Analysis
Vector analysis reduced the risk of irrelevant answers by matching user inquiries with the most related provided question data before response generation.
OpenAI Model Integration
OpenAI Model allowed the chatbot to turn matched question content into more natural responses, creating a consultation experience that felt less like static FAQ support.
Chatbot Response Training
Response training gave the client more control over how the chatbot handled common inquiries, making answer quality easier to manage as the service expanded.
Customizable Chat Interface
Customizable chat frame, chat window and chat button settings made the chatbot easier to adapt across customer or partner websites, supporting the product’s SaaS based service direction.
Direct Consultant Chat
Direct consultant chat kept human support available when AI was not suitable, allowing the business to balance automation with service quality and user trust.
Risk Handling
- For an AI consultation service, the main risk is not always a failed response. It is an answer that feels disconnected from the user’s real question. In live customer interactions, irrelevant answers can weaken trust, interrupt the consultation journey, and reduce confidence in the service. Newwave Solutions reduced this risk by placing vector based analysis before OpenAI response generation. Each user query was first matched with the most relevant provided question data. OpenAI Model then generated a more natural answer based on that context. This gave the chatbot a stronger response foundation and helped keep answers grounded in the content provided by the client.
Product Outcomes
Users could ask questions through the website chatbot and receive AI generated answers based on predefined question data, helping reduce the need for manual handling of repeated or common inquiries.
The client could train chatbot responses from prepared question sets, creating a more manageable way to control common answer content.
Vector based analysis and OpenAI Model integration allowed the chatbot to connect user inquiries with relevant question data before generating more natural responses.
Users who did not want to continue with AI could switch to direct consultant chat, keeping human support available within the same consultation flow.
The client could adjust the chat frame, chat window and chatbot button interface, making the chatbot easier to fit into the website experience.
The product was applied to the client’s main system, which recorded 10K+ daily accesses. This showed the chatbot was deployed in a real website environment rather than remaining at a test or demo stage.
The system was developed as a service that could be embedded into customer websites, giving the client a stronger foundation to offer chatbot capabilities to business partners.
Business Impact
The system helped the client add AI assisted consultation alongside human support. Common questions could be answered through AI generated responses based on predefined question data, while direct consultant chat remained available for situations that required human judgment. This created a more balanced consultation flow, with AI supporting repeated inquiries and human consultants staying involved for more complex cases.
This created value in four areas:
- Support capacity: The chatbot could handle common inquiries before consultant handover when suitable, keeping human support available for more complex cases.
- Answer control: Provided question data gave the client a clearer foundation for keeping common responses consistent.
- AI reliability: Vector based analysis reduced the risk of answers drifting away from the available question content before OpenAI Model generated the final response.
- Service deployment model: The SaaS based model made the chatbot easier to embed into customer or partner websites, supporting the client’s plan to offer the service beyond its own website.
- Real website application: The product was applied to the client’s main system, which recorded more than ten thousand daily accesses. This showed that the chatbot was deployed in a real website environment rather than remaining at a demo stage.
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