AI & Automation
Custom AI Business Chatbot
Discipline
AI / RAG Chatbot
RAG-powered chatbot trained on company knowledge base. 80% query accuracy, deployed in days.

The brief
From a real problem to a working product.
Most chatbots answer generic questions. A custom AI chatbot trained on your specific business knowledge — your product documentation, SOPs, FAQs, pricing, support history — can handle the questions your team gets asked every day, consistently and at scale.
Golden Sea builds RAG-powered chatbots using Dify as the orchestration layer and Pinecone as the vector database. The process: upload your documents (PDFs, Notion pages, Google Docs, web pages), the system chunks and embeds them, and the chatbot retrieves relevant passages when a user asks a question — grounding every response in your actual content rather than hallucinating.
The LLM layer (GPT-4 or Claude, depending on requirements) synthesizes the retrieved context into a natural conversational response. System prompts enforce tone, scope, and escalation rules: the bot knows what it's allowed to answer and when to hand off to a human.
Deployment integrations include website chat widgets, Slack, WhatsApp Business, and LINE — wherever your users already are. An admin dashboard lets non-technical staff update the knowledge base, review conversation logs, rate responses, and monitor accuracy metrics over time. Typical deployment timeline: 5–10 business days from kickoff to go-live. Average query accuracy on client-specific knowledge: 80%+.
Scope delivered
The work behind the outcome.
- 01RAG architecture — answers grounded in your documents
- 0280%+ query accuracy on company-specific knowledge
- 03Connects to Slack, WhatsApp, website chat, and more
- 04Admin panel for knowledge base management
- 05Human handoff escalation built in
Category
AI & Automation
Technology
Dify · LLM (GPT-4 / Claude) · Pinecone · Python · FastAPI · React · Slack / WhatsApp API
Studio
Golden Sea Studios
Ho Chi Minh City, Vietnam
Have a similar challenge?


