Furnigenius AI Chatbot
Arckipel developed a multilingual AI chatbot that handles recurring technical questions, delivers certified product knowledge in real-time, and redirects leads efficiently — saving time and improving pre-sales qualification.
The bot is powered by a vectorised knowledge base and Retrieval Augmented Generation (RAG), and is fully integrated into the Furnigenius sales experience.
The Challenge and Solution
The Challenge: Furnigenius needed to reduce time spent on repetitive inquiries from potential customers.
The Solution: Arckipel built and deployed a structured AI chatbot trained on company-specific data and connected to key workflows.
“The result: 20+ hours of team time saved per month, a sharper sales funnel, and a more consistent information flow for early-stage prospects.”
Furnigenius is a contract furniture manufacturer serving interior designers, architects, and procurement teams across Europe. A recurring challenge: prospective clients asked detailed, often technical questions — about materials, certifications, production standards, or logistics — long before booking a call. These queries, while legitimate, consumed valuable team time and frequently led to disqualified leads after avoidable meetings or prolonged email chains.
Implementation Details
To address this, Arckipel implemented a custom AI assistant using Retrieval-Augmented Generation (RAG) and a structured internal knowledge base. The system was trained on all relevant company content — including product specifications, sustainability documentation, safety certificates, and manufacturing policies. The assistant now handles incoming queries in natural language, retrieves precise answers, and guides users to the next logical step: whether that's scheduling a call, accessing the product catalogue, or downloading a compliance certificate.
Technically, the system leverages RAG in combination with a multi-model orchestration approach. Each user prompt is routed through the most suitable model depending on context, language, and query type — balancing accuracy, latency, and privacy. All data is served from a vectorised internal repository, with secure APIs and fallback logic in place.
AI Models Used
The following models were used during implementation:
The architecture is multilingual-ready and modular — making future CRM integration, interface expansion, and industry-specific extensions easy to deploy.
Instead of relying on static FAQ pages or sales calls to convey basic information, Furnigenius now engages prospects through an intelligent, real-time channel — trained on their own data, tailored to their operational context.
