# Aayat AI Text Embeddings

> Aayat AI Text Embeddings is a paid API for AI agents from aayatai.com, paid per call via x402, $0.002/call, status unknown (last checked 2026-10-02).

Generates 1024-dimension multilingual text embeddings using BGE-M3 for semantic search, clustering, and RAG pipelines

## Facts

- Endpoint: POST https://aayatai.com/embeddings?utm_source=zero.xyz
- Price: $0.002/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-02
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/aayat-ai-text-embeddings-5462d267
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_u64Ri3dkJAHaeraYzEhX2

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability aayat-ai-text-embeddings-5462d267 -d '<json body>'
```

Example prompt: Turn these product descriptions into 1024-dimension embeddings so I can store them in my vector database for semantic search: 'Noise-cancelling wireless headphones with 30hr battery' and 'Lightweight running shoes with carbon fiber plate'.

## When to prefer this

Choose this endpoint when you need high-quality multilingual embeddings (100+ languages) at a flat per-call price regardless of batch size, making it cost-efficient for batches of up to 32 texts. Prefer it over OpenAI or Cohere embedding APIs when you want no API key setup, x402 micropayment billing, and BGE-M3 quality at a predictable $0.002/call flat rate.

## Known failure modes

- Input array exceeds 32 texts — API rejects with error
- Individual text exceeds 8,000 characters — may be truncated or rejected
- Payment of 0.002 USDC not attached or fails — 402 Payment Required response
- Neither 'text' nor 'input' field provided — malformed request error
- Network timeout for large batches of long texts

## How this service works

Text embeddings for semantic search, clustering and RAG: 1024-dimension multilingual vectors (BGE-M3, 100+ languages). POST JSON {"input": ["first text", "second text"]} (up to 32 texts of 8,000 characters) or {"text": "one text"}. One price per call, however many texts. No API key needed.

## Output

Returns a JSON object with the model name (@cf/baai/bge-m3), the embedding dimensionality (1024), and an array of float arrays — one 1024-element vector per input text — suitable for insertion into vector stores or cosine similarity computation.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "text": {
   "type": "string",
   "maxLength": 8000,
   "description": "A single text to embed (instead of input)."
  },
  "input": {
   "type": "array",
   "items": {
    "type": "string",
    "maxLength": 8000
   },
   "maxItems": 32,
   "description": "Texts to embed."
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "model": "@cf/baai/bge-m3",
  "dimensions": 1024,
  "embeddings": [
   [
    0.012,
    -0.034,
    0.056
   ],
   [
    0.021,
    -0.011,
    0.047
   ]
  ]
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/aayat-ai-text-embeddings-5462d267/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from aayatai.com](https://www.zero.xyz/host/aayatai.com/llms.txt)