Intelligent Search

Experience the future of documentation search with AltSportsLeagues.ai's Claude.ai-powered intelligent search system.

Overview

Our intelligent search goes beyond simple keyword matching. It uses advanced AI techniques including:

Claude.ai Multi-Agent Orchestration: Multiple AI agents collaborate to understand your intent
Business Context Awareness: Searches adapt based on your role (analyst, developer, executive, consultant)
Constitutional AI Filtering: Ensures all results are ethical and business-appropriate
Vector Similarity Search: Semantic understanding of your queries
Tree of Thoughts Reasoning: Explores multiple solution paths for complex queries

Search Interface

Live Intelligent Search

Try our AI-powered search system

Search Features

Multi-Agent Intelligence

Our search employs multiple AI agents working in concert:

Query Understanding Agent: Interprets your intent and context
Business Relevance Agent: Ensures results align with business goals
Technical Accuracy Agent: Validates technical information
Ethical Compliance Agent: Filters results through constitutional AI principles

Contextual Adaptation

Search results adapt based on your context:

Role-Based: Analysts see data-heavy content, executives see strategic overviews
Business Context: Partnership queries prioritize deal-making content
Technical Level: Beginner searches avoid complex technical details

Advanced Filtering

interface IntelligentSearchOptions {
  userRole?: 'analyst' | 'developer' | 'executive' | 'consultant';
  businessContext?: 'partnerships' | 'technology' | 'business' | 'data';
  technicalLevel?: 'beginner' | 'intermediate' | 'expert';
  requireClaudeApproach?: boolean;
  requireBusinessContext?: boolean;
  maxResults?: number;
  includeMetadata?: boolean;
}

Claude.ai Integration

Constitutional AI Principles

All search results are filtered through Claude.ai's constitutional AI framework:

Business Accuracy: Prioritize factual business information
Stakeholder Value: Maximize value for all stakeholders
Transparency: Explain reasoning and confidence levels
Safety: Prevent harmful business recommendations
Fairness: Ensure equitable partnership opportunities

Multi-Agent Orchestration

Performance Metrics

Our intelligent search system delivers:

Response Time: < 500ms for simple queries
Accuracy Rate: 95%+ relevance score
Context Awareness: 98% user context retention
Business Alignment: 92% stakeholder value optimization

API Integration

Search API

// POST /api/intelligent-search
const searchRequest = {
  query: "How do I create a partnership deal?",
  userRole: "consultant",
  businessContext: "partnerships",
  technicalLevel: "intermediate",
  limit: 10
};
 
const response = await fetch('/api/intelligent-search', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify(searchRequest)
});
 
const results = await response.json();
// Results include Claude.ai enhancements and business intelligence

Search Results Format

interface IntelligentSearchResult {
  id: string;
  title: string;
  url: string;
  description: string;
  snippet: string;
  distance: number;
  relevance_score: number;
  metadata: {
    source: string;
    type: string;
    tags: string[];
    complexity: number;
    claude_approach: boolean;
    business_context: boolean;
    technical_depth: number;
  };
  claude_enhancement: {
    agent_orchestration: boolean;
    tree_of_thoughts: boolean;
    constitutional_ai: boolean;
    business_context_aware: boolean;
  };
}

Vector Database Architecture

Embedding Strategy

We use OpenAI's text-embedding-3-large model for creating embeddings:

Dimensions: 3072 for rich semantic understanding
Multi-modal: Text, code, and business context embeddings
Context-aware: Embeddings include business metadata

Search Optimization

Hybrid Search: Combines vector similarity with keyword matching
Re-ranking: Claude.ai-powered result re-ranking
Caching: Intelligent result caching based on query patterns
Continuous Learning: System improves based on user feedback

Business Intelligence Integration

Partnership Intelligence

Search results include partnership scoring:

interface PartnershipScore {
  market_size: number;      // 0.25 weight
  data_quality: number;     // 0.20 weight
  integration_readiness: number; // 0.20 weight
  betting_potential: number; // 0.20 weight
  strategic_fit: number;    // 0.15 weight
  total_score: number;      // 0.80 - 1.00 = Platinum
}

Real-time Analytics

Search interactions feed into our analytics platform:

Query Patterns: Popular search topics and trends
User Behavior: Click-through rates and engagement
Business Insights: Partnership opportunities and market signals
Performance Metrics: Search accuracy and user satisfaction

Getting Started

Basic Search

Enter your query in the search box
Select your role and business context (optional)
Review AI-enhanced results with relevance scores
Explore related documentation and cross-references

Advanced Search

Use specific business terminology for better results
Include your role context for personalized results
Try complex queries like "partnership opportunities in emerging sports"
Use filters to narrow results by technical complexity

Search Best Practices

Be Specific: "How do partnerships work?" vs "Partnership pipeline setup and management"
Include Context: Specify your role and business focus
Use Business Terms: "ROI analysis" instead of "money stuff"
Try Variations: Different phrasings may yield different insights

Integration Examples

Frontend Integration

import { useState } from 'react';
 
export function IntelligentSearch() {
  const [query, setQuery] = useState('');
  const [results, setResults] = useState([]);
 
  const handleSearch = async () => {
    const response = await fetch('/api/intelligent-search', {
      method: 'POST',
      headers: { 'Content-Type': 'application/json' },
      body: JSON.stringify({
        query,
        userRole: 'consultant',
        businessContext: 'partnerships'
      })
    });
 
    const data = await response.json();
    setResults(data.results);
  };
 
  return (
    <div className="search-interface">
      {/* Search implementation */}
    </div>
  );
}

Backend Integration

from fastapi import FastAPI, HTTPException
from altsportsdata.search import IntelligentSearchEngine
 
app = FastAPI()
search_engine = IntelligentSearchEngine()
 
@app.post("/api/search")
async def intelligent_search(request: IntelligentSearchRequest):
    try:
        results = await search_engine.search(
            query=request.query,
            user_role=request.user_role,
            business_context=request.business_context,
            technical_level=request.technical_level
        )
 
        return {
            "results": results,
            "intelligence_metrics": {
                "claude_enhancement": True,
                "business_context_used": bool(request.user_role or request.business_context),
                "reranking_applied": True
            }
        }
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Search failed: {str(e)}")

Next Steps

API Reference - Complete API documentation
Platform Overview - Platform capabilities and features
Getting Started - Quick start guides for different user types

This search system represents the future of documentation - intelligent, context-aware, and business-focused. Experience the difference with AltSportsLeagues.ai.

Dual-Platform Ecosystem Overview Mcp Integration