Build a Live Supervisor Dashboard for AI Support Calls

Most voice AI quality checks happen after the call ends. A transcript is stored, someone reviews a small sample later, and any mistake has already reached the customer.

What if a supervisor could watch an AI support call while it was happening, send the assistant a private coaching instruction, and join the same conversation when human help was needed?

That is what the Live Support Coach Room example demonstrates. It is a TypeScript application running on Telnyx Edge Compute with:

This tutorial focuses on the architecture and the fastest way to explore it locally and on Telnyx Edge.

Try entering the same account number twice in the simulator. The room detects that the caller has repeated sensitive account information without identity verification and injects a coaching instruction telling the assistant to verify the caller's date of birth.

The same room can then dial a supervisor and join that person to the active AI conversation.

AI Assistant event stream | v AssistRelay | v CoachRoom for this conversation | | | | | +--> Call Control + WebRTC escalation | +--------------> coaching policy + injected nudge +-------------------------> supervisor dashboard WebSocket Enter fullscreen mode Exit fullscreen mode Why the event stream is a side channel The assistant's websocket_settings points to the application's /agents/assist endpoint. Telnyx opens one WebSocket for each conversation and sends events such as:

session.created conversation.item.created response.text.delta telnyx.call.answered telnyx.call.hangup session.ended Enter fullscreen mode Exit fullscreen mode This socket observes the conversation and can inject text turns, but it does not carry the call media and does not replace the model.

That distinction matters. If the coaching application becomes unavailable, the call continues. The caller does not lose audio because the monitoring surface crashed.

The conversation event stream documentation describes it as a live side channel. It is currently beta, and clients should ignore event types they do not recognize because new types may be added.

The stream also is not a guaranteed transcript archive. Events that occur while the socket is unavailable are not replayed. Use it for live supervision, and use the Conversations API after the call when you need a complete system-of-record transcript.

Configure the assistant with the deployed WebSocket URL:

curl -X POST "https://api.telnyx.com/v2/ai/assistants/ $ASSISTANT_ID " \ -H "Authorization: Bearer $TELNYX_API_KEY " \ -H "Content-Type: application/json" \ -d '{ "websocket_settings": { "enabled": true, "url": "wss://live-support-coach-room-<id>.telnyxcompute.com/agents/assist", "auth_ref": "<your-integration-secret-reference>" } }' Enter fullscreen mode Exit fullscreen mode auth_ref points to an integration secret. Telnyx resolves it and sends the value as a bearer token when opening the WebSocket.

The application mounts two Agent SDK WebSocket surfaces under /agents:

const handleAgents = mountAgents < Env > (( env ) => ({ assist: env. RELAY, " coach-room ": env. COACHROOMS, })); Enter fullscreen mode Exit fullscreen mode /agents/assist receives the assistant event stream. On session.created, the relay uses the conversation ID to locate that conversation's CoachRoom actor.

Each room owns the state for exactly one conversation:

This is a good fit for a stateful actor: the actor identity is the conversation identity, and related events are handled by the same durable instance.

A separate CoachRegistry actor tracks active and ended rooms for the dashboard picker.

wss://<function-host>/agents/coach-room/{conversation_id} Enter fullscreen mode Exit fullscreen mode When a supervisor opens a room, the dashboard receives its current state and then follows live updates. This means a supervisor joining halfway through a call can see what happened before opening the dashboard instead of starting with an empty screen.

The application also exposes regular HTTP routes:

The room watches conversation events and evaluates a deliberately small policy. When a rule fires, it sends a conversation.item.create frame back over the assistant stream.

Conceptually, the frame looks like this:

{ "type": "conversation.item.create", "item": { "type": "message", "role": "assistant", "content": [ { "type": "input_text", "text": "Verify the caller's date of birth before sharing account details." } ] } } Enter fullscreen mode Exit fullscreen mode The instruction becomes part of the live conversation context, allowing the assistant to change course without ending or restarting the call.

NUDGE_MAX_PER_CALL=3 SILENCE_SECS=90 Enter fullscreen mode Exit fullscreen mode The first prevents an overactive policy from flooding one conversation. The second schedules a check-in after extended silence. The silence watcher is cancelled when session.ended arrives.

For a production deployment, the simple rule can be replaced with policies for compliance language, authentication, escalation risk, or objection handling.

When the supervisor clicks Escalate to supervisor, the room:

The softphone answers muted and unmutes after the join succeeds. This avoids exposing setup noise to the caller.

The human joins the existing conversation as another participant rather than receiving a cold transfer. Telnyx's multi-participant call documentation covers the broader pattern for adding people to active AI calls.

The included simulator is the quickest way to understand the state flow because it does not require telephony.

git clone https://github.com/team-telnyx/telnyx-code-examples.git cd telnyx-code-examples/live-support-coach-room npm install Enter fullscreen mode Exit fullscreen mode Create your environment file:

cp.env.example.env Enter fullscreen mode Exit fullscreen mode Authenticate and prepare the Edge function:

telnyx-edge auth api-key set <your_telnyx_api_key> telnyx-edge new-func -l ts -n live-support-coach-room --from-dir. telnyx-edge types Enter fullscreen mode Exit fullscreen mode Run the smoke test:

npx tsx smoke_test.ts Enter fullscreen mode Exit fullscreen mode Deploy it:

telnyx-edge ship Enter fullscreen mode Exit fullscreen mode Then open these pages from the deployed function:

https://<function-host>/caller https://<function-host>/dashboard Enter fullscreen mode Exit fullscreen mode Start a simulated call in the caller tab. Enter an account number twice, then watch the policy flag and coaching instruction appear in the dashboard.

The simulated coaching flow works without a call, but live escalation needs the following Edge secrets:

telnyx-edge secrets add TELNYX_API_KEY "<your-key>" telnyx-edge secrets add COACH_AUTH "<integration-secret-value>" telnyx-edge secrets add CALL_CONTROL_CONNECTION_ID "<connection-id>" telnyx-edge secrets add TELNYX_NUMBER "+1555XXXXXXXX" telnyx-edge secrets add SUPERVISOR_DEVICE "+1555XXXXXXXX" Enter fullscreen mode Exit fullscreen mode Use placeholders in source control and store the real values as secrets. The browser softphone also needs a WebRTC login token supplied by the supervisor at runtime.

This sample demonstrates the architecture, but a production coach room should add:

The central design still holds: keep observability outside the media path, give each conversation a durable owner, and make human intervention a first-class call participant.

The same structure can support more than customer service coaching:

You can keep the plumbing and replace the policy inside CoachRoom with the rules that matter to your application.