Skip to main content

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

Connie is VH3 AI’s conversational assistant. She has access to the full knowledge graph, semantic search, reports, and sentinel results — and responds to questions in natural language with cited, data-backed answers.

​
POST /connie/chat

Send a message to Connie and receive a response grounded in your operational data. Request body:
FieldTypeRequiredDescription
company_idstringYesYour tenant identifier
api_keystringYesYour tenant API key
messagestringYesYour question or instruction
session_idstringNoSession identifier for conversation continuity
user_idstringNoIdentifier for the user asking
user_namestringNoDisplay name (personalises responses)
user_company_namestringNoCompany name for context
summarystringNoPrior conversation summary (for long sessions)
contact_idstringNoScope to a specific customer context
current_job_referencestringNoJob currently being discussed
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”
Connie maintains conversation context within a session. Follow-up questions like “What about last month?” reference the previous exchange automatically.

​
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. 
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:
FieldTypeRequiredDescription
company_idstringYesYour tenant identifier
api_keystringYesYour tenant API key
contact_idstringYesContact to summarise
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. 
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. 
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//messages

Retrieve all messages for a specific session. 
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"