๐ง Live Recommendation
AI Live Recommendation โ Personalized in Real Time
Every conversation becomes an opportunity.
๐ก The Challenge
Static Recommendations Fall Short
Customers crave personalization โ "What's best for me?" But static recommendation systems can't adapt to live conversation or context.
Context-Blind Systems
Traditional recommendations ignore real-time conversation context and customer emotions.
One-Size-Fits-All
Generic suggestions that don't account for individual preferences or current needs.
Missed Opportunities
Static systems can't capitalize on in-the-moment buying signals or interest spikes.
Poor Timing
Recommendations often come at the wrong time in the customer journey.
๐งฉ Solution Overview
Real-Time Intelligent Recommendations
Voxket's AI Recommendation Engine listens, learns, and acts in real-time โ suggesting products, upgrades, or next steps dynamically across chat, voice, and video.
Recommendations that feel human โ delivered at the perfect moment.
โ๏ธ What It Does
Intelligent Action-Driven Recommendations
Intent Detection
Detects user intent during conversation in real-time for contextual suggestions.
Contextual Pull
Pulls context from CRM, session history, and product catalog for personalization.
Smart Recommendations
Recommends based on preferences, behavior, mood, and conversation context.
Direct Actions
Can take action โ add to cart, open link, navigate screen directly in conversation.
Co-Pilot Integration
Works seamlessly with your front-end app via Co-Pilot Engine.
๐ Integrations
Seamless E-commerce & Analytics Integration
Commerce
Shopify
WooCommerce
Magento
BigCommerce
CRM
HubSpot
Zoho
Salesforce
Pipedrive
Analytics
Segment
Amplitude
Mixpanel
Google Analytics
Recommendation APIs
Algolia
Pinecone
Elasticsearch
Custom APIs
๐ผ Business Impact
Measurable Revenue Growth
๐ Upsell Rate
+30% per session
โก Session Duration
+25% engagement
๐ฌ Conversion Rate
+18% higher
โ๏ธ Technical Highlights
Advanced ML Recommendation Engine
Real-time embedding search (vector-based)
Contextual personalization using memory store
Voice and visual recommendations via SDK
Reinforcement learning from acceptance rate
Multi-modal reasoning (voice + chat + image)
๐ฏ Ready to Personalize?
Recommendations that feel human.
Deliver the right suggestion โ every time, on every channel.
โ FAQ
Frequently asked questions
What does AI Live Recommendation do?
An AI agent suggests the right products or next steps in real time during a conversation, based on context and your catalog.
How does it personalize?
It uses conversation context and your product data to recommend relevant options live, then explains why.
Can it complete the purchase?
Yes. Interactive UI and integrations let it book or check out right in the conversation.
Which channels does it work on?
Chat, voice, and video, on the same agent foundation.
Does it improve over time?
Yes. Deep analytics on every interaction feed continuous improvement.
Ready to put an AI workforce on your frontline?
Deploy voice, chat, and video agents that work 24/7, act in your systems, and hand off to your team when it counts. Build your first agent in minutes.
White-glove onboarding for teams ยท Talk to a human, not a form.
