RingFront Ai: Deploy a Business-Trained AI Chat & Voice Assistant on Any Website in Minutes

Off-the-shelf chatbot platforms either give generic GPT responses that don't reflect the business's actual products, services, or policies — or they require months of manual FAQ building to reach acceptable accuracy. Both approaches erode visitor trust. Small and mid-size businesses needed a way to deploy an AI assistant that answers questions strictly from their own content — without needing a data science team, without manual training, and without the risk of the bot confidently saying something wrong about their business.

We built RingFront Ai as a full-stack SaaS platform: a powerful backend handling all crawling, embedding, chat, and voice — paired with an intuitive Next.js 14 business dashboard. After domain verification (file-based or DNS TXT), the intelligent crawler launches in the background. A three-stage filter removes junk URLs (blog posts, auth pages) via keyword blocklist, then runs a DeepSeek AI URL classifier in batches of 20, then applies a minimum 80-word content quality gate. Approved pages are cleaned to Markdown, stripped of all media and UI chrome, and bulk-saved as WebsiteDocument records. Embedding runs OpenAI text-embedding-3-large on each document chunk, storing vectors in a per-business Qdrant collection (named by website UUID) with cosine similarity search. At chat time, the visitor's message is embedded, the top-k most similar chunks are retrieved, and DeepSeek Chat generates a response grounded entirely in that context. The voice agent runs over LiveKit WebRTC with Deepgram STT and TTS, Silero VAD for turn detection, and full call recording + transcript storage. The embeddable JavaScript widget is fully themeable with six colour fields, position options, custom icons, and quick-action prompt buttons.

Django + DRF API. Django Channels WebSockets for real-time crawl progress. Qdrant vector database (gRPC + HTTP, cosine similarity, per-business collections). OpenAI text-embedding-3-large for document embedding. DeepSeek Chat for RAG response generation. LiveKit WebRTC for voice sessions. Deepgram Nova-2 STT + Aura Asteria TTS. Silero VAD for voice activity detection. aiohttp async crawler with 10 concurrent workers. PyPDF2, python-docx, markdownify for document parsing. dnspython for DNS TXT verification. Next.js 14 App Router frontend. Redis for channel layer.