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AdMesh SDK Documentation

AdMesh SDK Documentation provides comprehensive technical guidance for integrating AI-powered product recommendation capabilities into enterprise applications and AI systems.

What is AdMesh?​

AdMesh is an enterprise-grade recommendation engine that enables developers to integrate intelligent product suggestions into applications. The platform supports chatbots, AI assistants, e-commerce platforms, and business applications requiring contextual product recommendations.

Available SDKs​

AdMesh provides three production-ready SDKs for different development environments:

Python SDK​

Backend integration for AI applications, data processing pipelines, and server-side implementations.

from admesh import Admesh

client = Admesh(api_key="your-api-key")
response = client.recommend.get_recommendations(
    query="Enterprise CRM solutions for distributed teams",
    format="auto"
)

TypeScript SDK​

Node.js integration for serverless functions, API services, and modern web backends.

import Admesh from 'admesh';

const client = new Admesh({ apiKey: 'your-api-key' });
const response = await client.recommend.getRecommendations({
  query: 'Enterprise CRM solutions for distributed teams',
  format: 'auto'
});

UI SDK​

React component library for frontend recommendation display with integrated analytics and tracking.

import { AdMeshLayout } from 'admesh-ui-sdk';

<AdMeshLayout
  recommendations={recommendations}
  autoLayout={true}
  onProductClick={(adId, admeshLink) => {
    window.open(admeshLink, '_blank');
  }}
/>

AI Agent Integration​

AdMesh provides enterprise-grade integration capabilities for AI applications and intelligent agents:

  • Intent Detection Engine - Automated query analysis and categorization
  • Contextual Recommendations - Context-aware product suggestions
  • Citation Integration - Numbered reference system for conversational interfaces
  • Automated Recommendations - Trigger-based suggestion generation
  • Conversational Components - Chat-optimized UI elements

Key Features​

Smart Recommendation Engine​

  • Machine learning-powered intent detection
  • Semantic matching using cosine similarity algorithms
  • Trust score-based quality filtering
  • Real-time recommendation processing

Analytics and Tracking​

  • Automated view and interaction tracking
  • Conversion monitoring and attribution
  • Performance metrics and reporting
  • Revenue analytics and insights

UI Component Library​

  • Production-ready React components
  • Citation-based conversational interfaces
  • Sidebar and floating chat implementations
  • Automated recommendation widgets
  • Theme customization support

Developer Experience​

  • Full TypeScript support with type safety
  • Comprehensive error handling and validation
  • Asynchronous operation support
  • Complete documentation and implementation examples

Quick Start​

  1. Obtain API credentials from the AdMesh Dashboard
  2. Select appropriate SDK based on your technology stack
  3. Install SDK using your package manager
  4. Implement integration following our technical guides

Documentation Structure​

Support Resources​

Resources​

Begin integration by following our Getting Started Guide.