🧠 Live Recommendation
AI Live Recommendation — Personalized in Real Time
Every conversation becomes an opportunity.
💡 The Challenge
Static Recommendations Fall Short
Customers crave personalization — "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.
🧩 Solution Overview
Real-Time Intelligent Recommendations
Voxket's AI Recommendation Engine listens, learns, and acts in real-time — suggesting products, upgrades, or next steps dynamically across chat, voice, and video.
Recommendations that feel human — delivered at the perfect moment.
⚙️ 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 — add to cart, open link, navigate screen directly in conversation.
Co-Pilot Integration
Works seamlessly with your front-end app via Co-Pilot Engine.
🔗 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
💼 Business Impact
Measurable Revenue Growth
🛒 Upsell Rate
+30% per session
⚡ Session Duration
+25% engagement
💬 Conversion Rate
+18% higher
⚙️ 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)
🎯 Ready to Personalize?
