> ## Documentation Index
> Fetch the complete documentation index at: https://docs.vh3.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Quickstart

> Make your first API call to VH3 AI in under 5 minutes

# Quickstart

First call: `POST https://api.vh3connect.io/api:kP8T1CK7/search/outcomes` with JSON body `company_id`, `api_key`, `query_text`, `limit`. Read [https://docs.vh3.ai/openapi.json](https://docs.vh3.ai/openapi.json) for full surface. For documentation search only, use [https://docs.vh3.ai/mcp](https://docs.vh3.ai/mcp), not this endpoint.

This guide walks you through making your first API call to the VH3 AI intelligence layer.

## Prerequisites

You need:

* Your **company ID** (provided during onboarding)
* Your **API key** (provided during onboarding)

## 1. Search your job history

The semantic search endpoint lets you find relevant past jobs by describing what you're looking for in natural language. The platform uses hybrid search, combining meaning-based matching with keyword retrieval.

<Warning>
  Your `company_id` and `api_key` are server-side credentials. The examples below must run on a backend server (Node.js route, Python service, cURL from a terminal). **Never put these values in browser JavaScript, a React/Vue/Angular component, or a mobile app.** If your API key appears in a browser network request, anyone who can open browser developer tools can use it to query your organisation's data. For browser-based apps, use [User Authentication (JWT)](/authentication#user-authentication) instead.
</Warning>

<CodeGroup>
  ```bash cURL theme={null}
  curl -X POST "https://api.vh3connect.io/api:kP8T1CK7/search/outcomes" \
    -H "Content-Type: application/json" \
    -d '{
      "company_id": "your-company-id",
      "api_key": "your-api-key",
      "query_text": "boiler intermittent fault",
      "limit": 5
    }'
  ```

  ```javascript Node.js (server-side only) theme={null}
  // This runs on your backend server — never in browser code
  const response = await fetch(
    "https://api.vh3connect.io/api:kP8T1CK7/search/outcomes",
    {
      method: "POST",
      headers: { "Content-Type": "application/json" },
      body: JSON.stringify({
        company_id: process.env.VH3_COMPANY_ID,
        api_key: process.env.VH3_API_KEY,
        query_text: "boiler intermittent fault",
        limit: 5,
      }),
    }
  );

  const results = await response.json();
  console.log(results);
  ```

  ```python Python (server-side only) theme={null}
  import os
  import requests

  # Credentials come from environment variables, never hardcoded
  response = requests.post(
      "https://api.vh3connect.io/api:kP8T1CK7/search/outcomes",
      json={
          "company_id": os.environ["VH3_COMPANY_ID"],
          "api_key": os.environ["VH3_API_KEY"],
          "query_text": "boiler intermittent fault",
          "limit": 5,
      },
  )

  print(response.json())
  ```
</CodeGroup>

This finds relevant past jobs even if they were recorded as "heating system cutting out" or "CH unit tripping intermittently."

## 2. Get sentinel alerts

Check what operational risks or growth opportunities the platform has detected:

```bash theme={null}
curl -X POST "https://api.vh3connect.io/api:kP8T1CK7/sentinels/run" \
  -H "Content-Type: application/json" \
  -d '{
    "company_id": "your-company-id",
    "api_key": "your-api-key",
    "sentinel": "engineer_performance_slip"
  }'
```

## 3. Ask Connie a question

Use the conversational AI endpoint to ask operational questions in natural language:

```bash theme={null}
curl -X POST "https://api.vh3connect.io/api:kP8T1CK7/connie/chat" \
  -H "Content-Type: application/json" \
  -d '{
    "company_id": "your-company-id",
    "api_key": "your-api-key",
    "message": "Which engineers had the most repeat visits last month?",
    "session_id": "quickstart-session-1"
  }'
```

Connie responds with a data-backed answer, citing the underlying records.

## 4. List your jobs from the FMS

The VH3 API gives you direct access to your FMS data (BigChange, Joblogic, etc.):

```bash theme={null}
curl -X POST "https://api.vh3connect.io/api:YdihQNr3/jobs/list" \
  -H "X-API-Key: your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "pageNumber": 1,
    "pageSize": 20,
    "sortBy": "createdAt",
    "direction": "descending"
  }'
```

<Note>
  The FSI intelligence endpoints use `company_id` + `api_key` in the request body. The VH3 FMS endpoints use `X-Api-Key` in the header. See [Authentication](/authentication) for full details.
</Note>

## What's next?

<CardGroup cols={2}>
  <Card title="Operational discovery" icon="magnifying-glass" href="/guides/operational-discovery">
    How search, precedents, and customer knowledge work on the layer.
  </Card>

  <Card title="Search API" icon="code" href="/api-reference/search">
    Endpoint reference for search and autocomplete.
  </Card>

  <Card title="Sentinels" icon="bell" href="/api-reference/sentinels">
    Configure and query all 19 sentinel monitors.
  </Card>

  <Card title="Connie" icon="message-bot" href="/api-reference/connie">
    Conversational AI with full operational context.
  </Card>

  <Card title="Reports" icon="chart-line" href="/api-reference/reports">
    Generate and retrieve automated operational reports.
  </Card>
</CardGroup>