> ## 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.

# Connie

> Conversational AI assistant with full operational context

# Connie

Connie is VH3 AI's conversational assistant. She has access to the full operational context (intelligence layer, semantic search, reports, and sentinel results) and responds to questions in natural language with cited, data-backed answers.

<Card title="Connie guide" icon="message-bot" href="/guides/connie">
  Capabilities, sessions, and how Connie uses the intelligence layer.
</Card>

<Card title="Agent observability" icon="eye" href="/guides/agent-observability">
  `toolCallOutputs`, usage, and verifying provenance in production UIs.
</Card>

## POST /connie/chat

Send a message to Connie and receive a response grounded in your operational data.

**Request body:**

| Field                   | Type   | Required | Description                                    |
| ----------------------- | ------ | -------- | ---------------------------------------------- |
| `company_id`            | string | Yes      | Your tenant identifier                         |
| `api_key`               | string | Yes      | Your tenant API key                            |
| `message`               | string | Yes      | Your question or instruction                   |
| `session_id`            | string | No       | Session identifier for conversation continuity |
| `user_id`               | string | No       | Identifier for the user asking                 |
| `user_name`             | string | No       | Display name (personalises responses)          |
| `user_company_name`     | string | No       | Company name for context                       |
| `summary`               | string | No       | Prior conversation summary (for long sessions) |
| `contact_id`            | string | No       | Scope to a specific customer context           |
| `current_job_reference` | string | No       | Job currently being discussed                  |

```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 sites had the most repeat visits in the last 30 days?",
    "session_id": "session-abc-123",
    "user_name": "Sarah"
  }'
```

**Example questions Connie can answer:**

* "Which engineers are consistently late on HVAC jobs?"
* "What is the repeat failure rate at Tesco sites?"
* "Has anyone seen this fault before?" (with a description)
* "Show me the top 5 customers by job volume this quarter"
* "What happened at the Manchester site last week?"
* "Give me a performance summary for engineer John Smith"

<Info>
  Connie maintains conversation context within a session. Follow-up questions like "What about last month?" reference the previous exchange automatically. Each response can include `toolCallOutputs` (structured results per tool) and `usage` (token counts). See [Agent observability](/guides/agent-observability).
</Info>

***

## POST /connie/chat/voice

Send a voice interaction to Connie, designed for voice-first interfaces where the input is a transcribed audio message. Optimised for concise, text-to-speech-friendly responses.

**Request body:**

Same fields as `/connie/chat`.

```bash theme={null}
curl -X POST "https://api.vh3connect.io/api:kP8T1CK7/connie/chat/voice" \
  -H "Content-Type: application/json" \
  -d '{
    "company_id": "your-company-id",
    "api_key": "your-api-key",
    "message": "How many jobs did we complete yesterday?",
    "session_id": "voice-session-001"
  }'
```

***

## POST /connie/generate-summary

Generate an AI summary for a contact, useful for pre-call preparation or account review.

**Request body:**

| Field        | Type   | Required | Description            |
| ------------ | ------ | -------- | ---------------------- |
| `company_id` | string | Yes      | Your tenant identifier |
| `api_key`    | string | Yes      | Your tenant API key    |
| `contact_id` | string | Yes      | Contact to summarise   |

```bash theme={null}
curl -X POST "https://api.vh3connect.io/api:kP8T1CK7/connie/generate-summary" \
  -H "Content-Type: application/json" \
  -d '{
    "company_id": "your-company-id",
    "api_key": "your-api-key",
    "contact_id": "contact-789"
  }'
```

***

## POST /connie/history/search

Search across past conversation history.

```bash theme={null}
curl -X POST "https://api.vh3connect.io/api:kP8T1CK7/connie/history/search" \
  -H "Content-Type: application/json" \
  -d '{
    "company_id": "your-company-id",
    "api_key": "your-api-key",
    "query_text": "SLA breach discussion"
  }'
```

***

## GET /connie/sessions

List chat sessions for a company.

```bash theme={null}
curl -G "https://api.vh3connect.io/api:kP8T1CK7/connie/sessions" \
  --data-urlencode "company_id=your-company-id" \
  --data-urlencode "api_key=your-api-key"
```

***

## GET /connie/sessions/{session_id}/messages

Retrieve all messages for a specific session.

```bash theme={null}
curl -G "https://api.vh3connect.io/api:kP8T1CK7/connie/sessions/session-abc-123/messages" \
  --data-urlencode "company_id=your-company-id" \
  --data-urlencode "api_key=your-api-key"
```