Intelligent Personalized Feeds As A Service

TensorLite empowers developers to build context-aware personalized feeds and search experiences with vector embeddings and conversational AI.

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// 1. Initialize a collection
const response = await fetch('https://api.tensorlite.ai/initCollection', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    "collectionName": "articles",
    "userId": "user123"
  })
});

// 2. Index your content
await fetch('https://api.tensorlite.ai/index/articles', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    "title": "Getting Started with Vector Search",
    "content": "Vector search is a technique that leverages...",
    "tags": ["search", "vector", "tutorial"]
  })
});

// 3. Search with semantic understanding
const searchResponse = await fetch('https://api.tensorlite.ai/search/articles', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    "query": "How to implement vector search?",
    "limit": 5,
    "filter": {
      "tags": ["tutorial"]
    }
  })
});

// Search response
/*
{
  "results": [
    {
      "title": "Getting Started with Vector Search",
      "content": "Vector search is a technique that...",
      "relevance_score": 0.92,
      "tags": ["search", "vector", "tutorial"]
    },
    // More results...
  ],
  "found": 8,
  "took_ms": 45
}
*/

// 4. Chat with your data
const chatResponse = await fetch('https://api.tensorlite.ai/chat', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    "collectionName": "articles",
    "query": "Find the latest on machine learning",
    "conversation_id": "conv-123", // Optional, to continue a conversation
    "user_context": {
      "interests": ["AI", "neural networks"]
    }
  })
});

// Chat response
/*
{
  "results": [
    {
      "title": "Advances in Neural Networks",
      "description": "Latest research in ML architectures...",
      "relevance_score": 0.95
    },
    // More results...
  ],
  "conversation_id": "conv-ae251",
  "context_used": true,
  "conversation_model_id": "model-gpt4"
}
*/

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Features

Build intelligent data experiences

TensorLite combines vector search, conversation history, and analytics to create personalized data experiences.

Vector Collections

Organize and manage your data with intelligent vector-based collections. Automatic schema detection and optimization for search and chat.

Conversational AI

Enable natural conversations with your data using powerful AI models. Built-in conversation history and context management.

Semantic Search

Go beyond keyword search with semantic understanding. Find relevant content based on meaning, not just exact matches.

Engagement Analytics

Track user interactions with your content. Automatically optimize search results based on engagement metrics.

Secure API Keys

Manage access with granular API key permissions. Create scoped keys with built-in rate limiting and usage tracking.

Performance & Scale

Built for speed and scale with sub-50ms response times. Handles millions of documents with intelligent caching and optimization.

How It Works

Build powerful data experiences in minutes

From initialization to production in three simple steps

1. Initialize Collections

Create intelligent data collections with a single API call. TensorLite automatically configures optimal settings for search and chat.

// Initialize a collection
const response = await fetch('https://api.tensorlite.ai/initCollection', {
  method: 'POST',
  body: JSON.stringify({
    "collectionName": "articles"
  })
});

2. Index Documents

Add content to your collections with the indexing API. Vector embeddings are automatically generated for semantic search and AI chat.

// Index a document
await fetch('https://api.tensorlite.ai/index/articles', {
  method: 'POST',
  body: JSON.stringify({
    "title": "Vector Search",
    "content": "A guide to vector search..."
  })
});

3. Search & Chat

Enable users to find and interact with your content through powerful search and natural language conversation APIs.

// Chat with your data
const response = await fetch('https://api.tensorlite.ai/chat', {
  method: 'POST',
  body: JSON.stringify({
    "collectionName": "articles",
    "query": "How do I implement search?"
  })
});

API Reference

Powerful, flexible endpoints

Our comprehensive REST API makes it easy to integrate personalized feeds and conversational AI into any application.

Collection Management

Create, configure, and optimize data collections with full control

Advanced Indexing

Single and bulk indexing with automatic vector embeddings generation

Conversational AI

Natural language interaction with conversation history and context management

Event Tracking

Record user interactions to optimize ranking and personalization

API Endpoints
Method
Endpoint
Description
POST
/initCollection
Initialize collection
POST
/search/:collectionName
Search documents
POST
/chat
Conversational search
POST
/index/:collectionName
Index document
POST
/bulk_index/:collectionName
Bulk index documents
POST
/events/:collectionName
Track events

Pricing

Simple, transparent pricing

Start for free, then scale as you grow

Free

Perfect for personal projects and prototypes

$0 /month

Get Started Free

What's included

  • Up to 10,000 documents
  • 5,000 API calls per month
  • 1 active collection
  • Basic analytics
  • Community support

Pro

For production applications and growing teams

$49 /month

Get Started

What's included

  • Up to 100,000 documents
  • 100,000 API calls per month
  • 10 active collections
  • Advanced analytics
  • Email support
  • Advanced AI models
  • Custom API keys

Enterprise

For organizations with advanced needs

Custom

Contact Sales

What's included

  • Unlimited documents
  • Custom API volume
  • Unlimited collections
  • Enterprise analytics
  • Dedicated support
  • Custom integrations
  • SLA guarantees

Ready to enhance your data experience? Start building with TensorLite today.

Create a free account and build your first intelligent feed in minutes. No credit card required.