Build the web users can talk to.
BoloSite is a voice-first interface layer for websites, with navigation, sales guidance, and a roadmap for future personalization and scale.
Talk to websites.
Don’t just click them.
BoloSite turns a normal website into a voice-driven assistant that understands the user, navigates the page, answers questions, and switches into sales mode when the conversation becomes product-focused.
Voice + AI
Hands-free website interaction
Hindi + English
User speaks naturally
Auto Actions
Scroll, open, read, navigate
BoloSite Live Flow
User: Show pricing and best plan
BoloSite: I’ll open the plan section and explain the best option.
Modesales
Actionnavigate + explain
Languagesame as user
01
Problem
Websites still ask the user to do all the work
Most websites are informative, but not guided. Users have to search, compare, and click through the entire journey by themselves.
Too many clicks before a user gets to the answer
Navigation is usually built for the site, not for the user’s intent
Non-technical users often get stuck or drop off
Language friction makes the experience weaker for many users
Businesses lose attention before the user reaches the buying moment
The business result
Slow journey
Low engagement
Lost conversions
A website should reduce effort, not add effort. That is the gap BoloSite is built to close.
02
Solution
BoloSite is a voice layer for websites
It listens to the user, understands the intent, finds the right context, takes action on the page, and responds in the same language.
Speak
The user talks naturally instead of typing.
Understand
The system detects intent, language, and mode.
Act
The assistant triggers the right website action.
Reply
The answer comes back in a short, natural response.
It feels less like using software and more like being guided
by a smart assistant.
03
Full Logic
How the prototype works end to end
This is the real operating loop: browser voice input, language detection, retrieval of website knowledge, LLM decision making, and action execution.
1
Voice capture
The browser continuously listens and captures the user’s speech.
2
Language detection
The system keeps the reply in Hindi or English based on the user.
3
Context search
It fetches the most relevant website's content and sales context from separate RAG stores.
4
LLM decision
The model returns strict JSON: mode, agent, action steps, and reply text.
5
Execution + speech
The frontend performs the actions and speaks the response aloud.
Current backend stack
Flask API, Groq LLM, language detection, per-user mode state, and ChromaDB retrieval.
Two knowledge sources
• One store handles website guidance. (main agent)
• the other handles sales and
product guidance. (Sales agent)
Safe fallback
If the model output is invalid, the system returns a safe response instead of failing silently.
main mode
sales mode
The assistant stays in sales mode for product, price, and buying questions. It returns to main mode when the topic changes.
Ex. of Practical actions
Scroll up, scroll down, open social links, show photos, close modals, read headings, and jump to relevant sections.
04
Product Features
What the user actually gets
This is not a generic chatbot overlay. It is a guided experience that can understand, navigate, and respond inside the website.
Auto navigation
The assistant can move the page and trigger website actions.
Hindi + English
The user speaks naturally and gets the answer back in the same language.
Guided interaction
The website feels like a conversation instead of a manual search task.
Sales mode
For product websites, it can recommend and explain options.
• Act like a Sales person 24*7
Knowledge answers
It answers from site content instead of inventing details.
Interruptible voice
The user can cut in and regain control at any time.
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Why It Is Different
Traditional website vs BoloSite
The core difference is simple: the old model makes the user search; the new model helps the user succeed faster.
Traditional website
Manual navigation The user must figure everything out
alone.
Static experience The site shows information but does not
guide the journey.
Language friction Not everyone thinks or speaks in
English.
Higher drop-off More friction means fewer completions.
BoloSite assistant
Voice interaction The user speaks and the site responds.
Interactive guidance The assistant drives the next useful
step.
Same-language replies Hindi and English are both
supported.
Faster action Less friction means a quicker journey to
value.
Turns static websites into guided, conversational
experiences.
06
Benefits
Why users and businesses care
• For users, it reduces effort.
• For businesses, it creates a clearer path to engagement,
trust, and
conversion.
For users
Saves time
Instant answers, shorter journeys and Auto act.
Easy to use
No learning curve for basic actions.
Natural interaction
Talk like a person, not a machine.
Multi-language
Hindi + English support.
For businesses
More engagement
Users stay longer and interact more.
Higher conversion
Less friction near the buying moment.
Lower support load
AI handles common questions.
Better experience
People feel guided, not lost.
07
Future Improvements
What should be built next
These are the next sensible steps after the current prototype. They are framed as roadmap items, not hype.
Current prototype
- Voice input, language detection, and speech reply.
- Two RAG stores: website guidance and sales guidance.
- Action execution and natural conversation flow.
- Per-user mode state for main vs sales conversation.
Next product step
- Plugin or SDK so any website can add BoloSite faster.
- More languages and better accessibility support.
- Human handoff for complex support or sales cases.
- Personalization using user behavior and history.
Long-term roadmap
- Turn websites into fully autonomous systems that act without manual input.
- Introduce visual guidance with real-time highlighting, comparison, and smart suggestions.
- Extend beyond screens into voice-first and ambient computing experiences.
- Create a universal AI layer that works across all websites with minimal integration.
Phase 1
Prototype hardening
Make the current demo stable, fast, and repeatable.
Phase 2
Productization
Convert the logic into a reusable widget or SDK.
Phase 3
Sales intelligence
Improve recommendations and conversion support.
Phase 4
Platform scale
Analytics, personalization, and multi-site management.
The goal is not just to make a chatbot. The goal is to make websites easier to use by letting people talk to them.
08
Market Opportunity
Why this can become a real business
The opportunity is broad because every website that cares about engagement, support, or conversion is a potential fit.
Massive
Website base
A very large surface area for adoption
Fast
AI adoption
Across companies of all sizes
Rising
Voice behavior
More natural user interaction
Large
Non-English demand
Strong need for accessible guidance
Best-fit customers
Small businesses
Startups
E-commerce
Service platforms
A scalable SaaS opportunity built around better website
interaction.
09
Business Model
How BoloSite makes money
The business model is simple: recurring software revenue, plus setup and enterprise pricing where the customer needs more support.
Business value
SaaS model
Recurring monthly revenue.
Easy integration
Simple setup path for websites.
Scalable
Can fit across industries.
High demand
Riding AI adoption.
Revenue streams
Subscriptions Basic to premium plans.
Enterprise Custom pricing and SLA.
Custom setup Integration and onboarding charges.
Estimated expenses
Initial costs: development, hosting, API integration. Operational costs: servers, AI usage, maintenance.
Unit economics direction
As usage grows, fixed cost is spread across more customers. That is the advantage of a software product.
10
Close
The vision is bigger than a chatbot
BoloSite is the first step toward websites that feel guided, conversational, and much easier to use.
BoloSite is not just a feature — it is a new way to
experience the web.
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