FitVoiceVoice AI Shopping Assistant
Your AI shopping assistant.
FitVoice is a voice-driven conversational assistant for e-commerce platforms, whatever they sell. It acts as a personal shopping guide, taking shoppers from item discovery through preference refinement and cart updates to checkout.
- Product
- FitVoice
- Sector
- E-commerce
- Built for
- E-commerce platforms, whatever they sell
- Demo
- 0:44 · English, Arabic, Urdu
The process
How FitVoice works
The shopper talks; FitVoice asks the questions a good sales assistant would (style, colour, size) and does the work in the store behind the conversation.
Step 1 of 5
Ask
The shopper asks for help finding something, such as a suit.
What it brings
Built to do the work,
not describe it.
- 01
Style & preference qualification
Natural dialogue that pins down the need, the look and the colour.
- 02
Interactive item selection
Shoppers choose items mid-conversation and ask for them in the cart.
- 03
Options & cart management
Size or any other option is collected before anything is added to the cart.
- 04
Conversational checkout
Keep browsing or finish the order. The assistant asks, the shopper decides.
- 05
Order confirmation
Orders are processed immediately, with an estimated delivery time.
- 06
Three languages
Demonstrated end to end in English, Arabic and Urdu.
Built from
5 building blocks,
one chain.
FitVoice runs on RohaTech's core AI capabilities, connected in sequence from input to action.
- 01Input
Listen
Multilingual voice and speech across phone, web and mobile.
- 02Input
Understand
Intent, documents and enterprise knowledge.
- 03Judgement
Reason
Models, rules and business context together.
- 04Execution
Act
APIs, applications and workflows.
- 05Execution
Communicate
Voice, web, mobile and outbound.
Listen → Understand → Reason → Act → Communicate
The same building blocks, other workflows
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The portfolio
All 9 products, running.
Every demo, in every language it ships in.
The next step
Bring us the challenge.
We'll build what solves it.
We scope one workflow with your team, build it against the systems you already run, prove it on numbers you already trust, then scale what works.
Let's start the conversation →