AI EmbeddingsVector embeddings for semantic search and RAG
The Helix AI Embeddings API turns text into vector embeddings for semantic search, RAG (retrieval-augmented generation), clustering, and recommendation systems. Powered by open-source sentence-transformers — production-grade quality without OpenAI's ada pricing.
- Free tier with 100 requests/month
- Fast, cached responses
- 99.9% uptime target
- Standard REST + JSON
What is the AI Embeddings API?
The Helix AI Embeddings API turns text into vector embeddings for semantic search, RAG (retrieval-augmented generation), clustering, and recommendation systems. Powered by open-source sentence-transformers — production-grade quality without OpenAI's ada pricing.
How it works
- 1POST one or more strings to /embed — receive an array of float vectors.
- 2Choose between all-MiniLM-L6-v2 (384 dim, fast) or all-mpnet-base-v2 (768 dim, better quality).
- 3POST /similarity to get cosine similarity between two texts directly.
- 4Batch up to 100 texts per request — 10x faster than individual calls.
- 5Multilingual support via /embed/multilingual using paraphrase-multilingual-mpnet-base-v2.
Endpoints
3 REST endpoints, all returning consistent JSON.
/embedGenerate embeddings for text(s)
/similarityCompute cosine similarity between texts
/modelsList available models
Code in 5 languages
Copy and paste into your project. Replace YOUR_API_KEY with your RapidAPI key.
// AI Embeddings API
const response = await fetch(
"https://ai-embeddings-by-helix-api.p.rapidapi.com/embed",
{
method: "POST",
headers: {
"X-RapidAPI-Key": "YOUR_API_KEY",
"X-RapidAPI-Host": "ai-embeddings-by-helix-api.p.rapidapi.com",
"Content-Type": "application/json"
},
body: JSON.stringify({ "query": "your input" })
}
);
const data = await response.json();
console.log(data);What developers build with this API
Real use cases from production deployments.
Semantic Search That Actually Works
Replace keyword search (Postgres full-text, Elasticsearch BM25) with vector search. 'cheap laptop for college' finds 'budget notebook for students' — meaning, not exact words.
RAG Pipelines
Embed your docs, store in pgvector/Pinecone/Weaviate, retrieve top-K by similarity, feed to LLM. The backbone of every modern AI chatbot.
Content Recommendations
Embed every product/article/song, recommend N nearest neighbors. Spotify and Netflix do this — now you can too in 10 lines of code.
Duplicate Detection
Find near-duplicates in support tickets, customer reviews, or job listings. Cosine similarity > 0.9 = likely duplicates.
Content Clustering
Embed 10,000 customer feedback items, run k-means, get 20 emerging themes. No manual tagging required.
Pricing
All tiers include this API. No credit card for free tier.
BASIC
Free
- ✓ 100 reqs/month
- ✓ Hard limit
- ✓ All endpoints
PRO
$9.99/mo
- ✓ 10,000/month
- ✓ +$0.005 each
- ✓ All endpoints
ULTRA
$29.99/mo
- ✓ 100,000/month
- ✓ +$0.002 each
- ✓ All endpoints
MEGA
$99.99/mo
- ✓ 1,000,000/month
- ✓ +$0.001 each
- ✓ All endpoints
Frequently asked questions
Real answers to questions developers ask before integrating.