SIX|V4 DocumentationReal-World IntelligenceCurrent
Current VersionV4 Live

V4: Real-World Intelligence Integration

Transform from generative UI demo to real-world connected commerce platform by integrating live web intelligence via Tavily. Bridge the gap between "art of the possible" and "production-ready agentic commerce."

Vision

V4 transforms SIX from a generative UI demo into a real-world connected commerce platform by integrating live web intelligence via Tavily. This bridges the gap between "art of the possible" and "production-ready agentic commerce."

Strategic Rationale

Current State (V2)
  • • AI generates layouts based on static inventory + persona
  • • Product recommendations use internal metadata only
  • • No connection to real-world trends, pricing, or expert opinions
V4 Target State
  • • AI enriches decisions with live web context
  • • Products show real-time social proof and expert validation
  • • Layouts adapt to trending styles and market conditions
  • • Demonstrates enterprise-grade agentic commerce patterns
Visitor ReactionV2V4
"Is this real?"Impressive UI simulationThis is connected to the real world
"Can this scale?"Maybe, needs more workYes, clear production path
"What's the ROI?"Hard to quantifyTrend detection, competitive intelligence

Key Features

Real-Time Context Enrichment

Inject trending product context based on persona and occasion. For example, when a Gift Shopping persona selects "Birthday" occasion, the agent queries Tavily for "trending birthday gift ideas 2024" and enriches the layout with real-world trend data.

Cost: Free tier (~1,500 calls/month) | Impact: High

Product Justification with Social Proof

Display live expert reviews and citations. For example, show "★★★★★ 'Best lightweight layer' - Wirecutter Top Pick" on product cards, powered by real-time Tavily searches for expert reviews.

Cost: Free tier (~500 calls/month) | Impact: High

Price/Stock Validation (Goal-Oriented Persona)

Compare inventory against real-world availability and pricing. Show "✓ Best price we found" or "⚠️ $20 cheaper at REI" using Tavily Extract API to parse competitor product pages.

Note: For demo, use simulated data with tooltip explaining production behavior

Expert Comparison Context (Comparing Persona)

Power "What experts say" panels using domain-filtered searches (Wirecutter, RTings, CNET). Provide real-time expert recommendations and comparison guides for products.

Cost: Free tier (~500 calls/month) | Impact: High

Trend-Aware Refinement Suggestions

Suggest refinements based on trending styles. For example, when detecting "Gorpcore trend" is hot, show refinement chip: "🔥 Try Gorpcore style" in the FloatingRefinementChat component.

Cost: Free tier (~300 calls/month, pre-fetched) | Impact: Medium

Tavily Integration Architecture

┌─────────────────────────────────────────────────────────────┐
│                    SIX V4                      │
├─────────────────────────────────────────────────────────────┤
│                                                              │
│  ┌──────────────┐    ┌──────────────┐    ┌──────────────┐  │
│  │   Persona    │    │   Context    │    │   Inventory  │  │
│  │   Selection  │    │   (weather,  │    │   (products, │  │
│  │              │    │   occasion)  │    │   stock)     │  │
│  └──────┬───────┘    └──────┬───────┘    └──────┬───────┘  │
│         │                   │                   │           │
│         └───────────────────┼───────────────────┘           │
│                             │                               │
│                             ▼                               │
│              ┌──────────────────────────┐                   │
│              │   LangGraph Merchandiser │                   │
│              │         Agent            │                   │
│              └────────────┬─────────────┘                   │
│                           │                                 │
│         ┌─────────────────┼─────────────────┐              │
│         │                 │                 │              │
│         ▼                 ▼                 ▼              │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐        │
│  │   Tavily    │  │   Tavily    │  │   Tavily    │        │
│  │   Search    │  │   Extract   │  │   Search    │        │
│  │  (Trends)   │  │  (Prices)   │  │  (Reviews)  │        │
│  └─────────────┘  └─────────────┘  └─────────────┘        │
│         │                 │                 │              │
│         └─────────────────┼─────────────────┘              │
│                           │                                 │
│                           ▼                                 │
│              ┌──────────────────────────┐                   │
│              │   Enriched Layout with   │                   │
│              │   Real-World Context     │                   │
│              └──────────────────────────┘                   │
│                                                              │
└─────────────────────────────────────────────────────────────┘

Implementation Phases

Phase 1: Trending Context Enrichment

Priority: P0 (Highest Impact, Lowest Cost) | Effort: 4-6 hours | Cost: Free tier

Inject real-world trend context into layout generation. When Gift Shopping persona selects "Birthday" occasion, agent queries Tavily for "trending birthday gift ideas 2024" and enriches layout with trending badges.

Phase 2: Expert Review Integration

Priority: P1 | Effort: 3-4 hours | Cost: Free tier

Add real expert citations to Comparing persona's comparison view. Query Tavily for expert reviews from Wirecutter, RTings, CNET and display in comparison tables.

Phase 3: Price/Stock Validation

Priority: P2 | Effort: 4-6 hours | Note: Simulated for demo

Show competitive pricing validation for Goal-Oriented persona. For demo, use simulated data with tooltip: "In production, this checks REI, Backcountry, Amazon in real-time."

Phase 4: Trend-Aware Refinements

Priority: P2 | Effort: 2-3 hours | Cost: Free tier (pre-fetched)

Suggest refinements based on trending styles. Pre-fetch category trends at build time and surface trend-aware suggestions in FloatingRefinementChat.

Demo Cost Strategy

Tier 1: Always On (Free Tier) ✅

Trending context on generation~1,500 calls/month
Expert reviews for comparison~500 calls/month
Category trend badges (pre-fetched)~300 calls/month
Total~2,300 calls/month = $0

Tier 2: On-Demand (User Triggered) ⚠️

Load expensive features only when user requests:

  • • Product "Why this?" - Click to load
  • • Deep dive research - "Get expert analysis" button

Tier 3: Simulated (Show the Pattern) 🎭

Demonstrate capability without real API calls:

  • • Competitor pricing - Mock data + UI with tooltip
  • • Real-time stock from competitors - Mock data + UI

Quick Win: Start Here

"Trending Now" Badge

Highest impact, lowest cost entry point. One API call per layout generation:

// On layout generation
const trendContext = await tavily.search({
  query: `trending ${persona} shopping ${season} 2024`,
  max_results: 3,
  search_depth: 'basic' // Cheaper than 'advanced'
});

// Inject into hero component
hero.trendingBadge = {
  text: "Trending on social",
  source: trendContext.results[0].title,
  url: trendContext.results[0].url
};
Cost:~1,500 calls/month = Free
Impact:High - Makes demo feel "connected to the real world"
Time:1-2 days

Get Started

Full Implementation Plan

Complete roadmap and implementation details are available in the markdown documentation

docs/v4/roadmap-implementation-plan.md