VectorAI

aihttps://api.vectorai.co

Embeddings and semantic search API

What it does

VectorAI offers low-latency embeddings and vector search. Embed text, images, or hybrid inputs and run semantic similarity search. Great for RAG applications, recommendation engines, and content discovery.

Example usage

Copy and run — works out of the box.

curl

curl -X POST https://api.vectorai.co/embed \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"text": "Your document text here", "model": "default"}'

Node.js

const VectorAI = require('vectorai');
const vector = new VectorAI(process.env.VECTOR_API_KEY);

const embedding = await vector.embed('Your document text here');

Python

import vectorai

client = vectorai.VectorAI(api_key=os.environ['VECTOR_API_KEY'])
embedding = client.embed('Your document text here')

Build ideas for this API

AI-suggested app ideas — perfect for indie hackers.

Internal search for company wikis and docs
Product recommendation engine from descriptions
Chatbot with RAG over custom knowledge base