Beacon AILaunch AI assistants in minutes. Let our backend do the heavy lifting.
Built with streaming responses, smart suggestions, copy & feedback controls, and beautiful markdown with code highlighting - all ready to embed in your product experiences.
BEACON AI
AI ASSISTANT READY IN MINUTES
About Beacon AI
Launch an AI assistant in minutes
Beacon AI is an advanced, generic RAG application. Bring your own data, wire a product, and go live fast. No heavy front‑end lift required.
Generic RAG core
Retriever‑augmented generation with streaming responses and feedback signals baked in.
Product‑aware UX
Assistants (products) use your branding and context; suggestion chips and headers adapt automatically.
Fast to production
Minimal config to ship: register → add products → add data → run sync → live.
Get started
Four steps to go live
Register a company
Create your organization account to manage assistants and data.
Add products (assistants)
Create one or many AI assistants - each product is its own chatbot surface.
Connect data
Upload PDFs, DOCX, XLSX, CSV, TXT, or provide a website URL to crawl per product.
Run sync
We ingest, chunk, index, and wire the context. Boom - your assistant is live.
Bring your data
Upload files or crawl a website
Attach data per product. Beacon AI handles the rest - parsing, chunking, indexing, and retrieval wiring.
Upload your docs or point the assistant to a site. Ideal for knowledge bases, FAQs, and product docs.
Website crawl
Provide a URL and we’ll crawl and sync content into the assistant’s index. Re‑run sync any time to refresh.
What’s inside
Production‑ready chat UX
The chat surface ships with input growth, new‑chat control, typing indicator, scroll anchoring, suggestion chips, and more.
Streaming chat (SSE)
Real-time token streaming for snappy UI feedback and fluid conversations.
Markdown + code highlight
Beautiful markdown rendering with copyable code blocks.
Feedback hooks
Like/Dislike, copy, and toasts wired to backend for measurable quality.
Smart suggestions
Clickable starter prompts fetched per product (client & product aware).
How it works
A clean flow from prompt → streamed answer → feedback
Thin client; our backend does the heavy lifting. This page keeps things fast, polished, and accessible.
Embed & route context
Pass client_id, product_id, and user_id via URL params. The UI fetches product details and suggestion tags automatically.
- ?cid=<client>&pid=<product>&uid=<user>
- Shows product name/logo and description in the header
- Populates suggestion chips for quick starts
Stream replies
Messages are sent to API and streamed back via event-stream for instant rendering.
- Token-by-token UI updates with graceful completion
- Abort control to stop generation
- Real-time typing indicators for better user experience
Capture feedback
Each assistant message can be liked/disliked and copied; events are posted back for analytics.
- Toast confirmation + visual state
- Actionable signal for quality loops
- Detailed interaction tracking for continuous improvement
Want to see it live with streaming & suggestions?
Open the chat window demo.
Development Roadmap
What's Next in Our Pipeline
Our journey from basic RAG to advanced AI agent ecosystem. See what we've accomplished and what's coming next.
Version 1
✓ CompletedFoundation & Core RAG
Essential RAG application with intuitive user interface
Version 2
✓ CompletedEnhanced RAG & UX
Advanced retrieval techniques with improved user experience
Version 3
⟳ In ProgressMCP Integration & Security
Model Context Protocol servers with enhanced security measures
Version 4
◯ PlannedAI Agents & Memory
Intelligent agent connectors with enhanced user memory systems
Development Progress
Bring Beacon AI into your product
Drop in the chat window, route context, and start streaming answers from your RAG backend.