# Altair AI Research Signals

> Altair AI Research Signals is a paid API for AI agents from altairworld.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-28).

Returns AI-generated stock research signals including buy/sell/underweight decisions and summaries for specific tickers

## Facts

- Endpoint: GET https://altairworld.com/api/research/signals?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-28
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/altair-ai-research-signals-7e4fe434
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap__M2gOHzuw1I_QTv4QijQ6

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 altair-ai-research-signals-7e4fe434
```

Example prompt: What's Altair AI's latest research signal and buy/sell recommendation for NVDA right now?

## When to prefer this

Use this endpoint when you need AI-generated equity research signals with explicit buy/sell/underweight decisions tied to a specific ticker, especially when you want a report URL for deeper analysis. Prefer this over generic financial data APIs when you specifically want Altair's research-model-generated recommendations rather than raw price data or consensus analyst ratings.

## Known failure modes

- Invalid or missing properties parameter may return empty signals array
- Ticker not covered by Altair research model returns count of 0
- Service unavailable or payment failure returns HTTP 402 or 5xx
- Stale data if research model has not run recently for requested ticker
- Malformed query returns 400 bad request

## How this service works

Altair is an applied AI lab in the San Francisco Bay Area. We build AI-guided intake, verification and matching for trusted local providers, plus tools like a document review workspace.

## Output

Returns a JSON object with a count of signals, a generatedAt timestamp, and an array of signal objects each containing the ticker symbol, date, AI model name, a brief summary (e.g. 'Sell / Underweight'), an investment decision label (e.g. 'UNDERWEIGHT'), and a URL to the full research report.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "properties": {
   "type": "string"
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "count": 1,
  "signals": [
   {
    "url": "https://altairworld.com/TradingAgents/NVDA/20261008_research-model_20261009_015920/complete_report/",
    "date": "2026-10-08",
    "model": "research-model",
    "ticker": "NVDA",
    "summary": "Sell / Underweight",
    "decision": "UNDERWEIGHT"
   }
  ],
  "generatedAt": "2026-10-13T00:00:00.000Z"
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/altair-ai-research-signals-7e4fe434/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from altairworld.com](https://www.zero.xyz/host/altairworld.com/llms.txt)