Dino LindlauAll work

Selected work at ART+COM Telekom

Telekom

The system behind the conversation.

AI platform technical concept

AI Platform

Simplified technical concept

Use-case setup

Agent context and
available actions

Configuration to orchestrator

Guide interface

Controls, state
and transcripts

To/from orchestrator · MQTT

The coordinating layer

AI orchestrator

  • Agent sessions
  • Realtime transport
  • Function-call dispatch
RTP audio

Janus audio gateway

Microphone input
Response playback

Orchestrator · WebRTC

OpenAI Realtime

Speech, responses
and function calls

Orchestrator MCP tools

Exhibition control

Configured action lists
via MQTT to displays and media

The orchestrator connects conversation to the exhibition through separate model, audio and control services. Diagram redrawn from the application structure.

About the project

An AI platform developed for Deutsche Telekom’s T Gallery. At ART+COM, I developed its core technical concept and built the realtime orchestration layer connecting configurable agents, guide conversations, and exhibition actions.

Client / project
Deutsche Telekom · T Gallery
Studio
ART+COM
My work
Technical concept & software development
My contribution
January–July 2026

Technologies used

AI platform & guide interface
  • TypeScript
  • Node.js
  • OpenAI Realtime API
  • WebRTC / Werift
  • Janus / RTP
  • MQTT
  • MCP
  • React

The setting

From a conversation
to an exhibition action.

T Gallery is Deutsche Telekom’s showroom in Bonn. The AI platform connects a guide’s conversation with the surrounding exhibition: a spoken request can invoke a configured action, such as changing the content on a separate display.

The work shown here covers technical concept, implementation, and local demonstrations. Public information establishes the showroom context, but does not confirm the release of this particular platform.

Official showroom film · Published November 2025, before the AI-platform work shown hereFilm: Deutsche Telekom · Cover photo: © DTAG

01 / Technical concept

One platform.
Different stories.

Each use case supplies its context and available actions. The orchestrator brings together the agent session, realtime speech, guide controls, and the tool services that connect to the exhibition.

My implementation

Clear boundaries,
one coordinated experience.

I established a dedicated orchestration layer and separated the agent and realtime transport from MQTT messaging. The orchestrator validates guide commands, manages sessions and audio-stream selection, and publishes state and transcripts.

I also built the bridge from the installation’s RTP audio streams into the realtime speech transport, and worked on function-call handling and tool integration. Separate MCP and exhibition-control services execute the configured actions.

An interruption should mean stop

Cancelling a model response does not remove sound already waiting to play. I changed interruption handling to cancel generation and clear buffered output together, keeping the agent’s turn-taking consistent with the audio path.

02 / Component architecture

Inside the
AI platform.

Two interfaces connect to an orchestration service and the exhibition’s shared infrastructure. Controls, live audio and action requests follow separate paths.

Platform components

Two frontends, one orchestration service and the shared services around it. The connections separate guide controls, live audio and tool-driven exhibition actions.

Frontends

Guide and operations interfaces

Guide interface

Push-to-talk, transcript and playback

Admin interface

Session controls and stream monitoring

AI Orchestrator

One Node.js backend service

Session controller

Commands, lifecycle and shared state

Agent session

Conversation, context and tool calls

Audio input adapter

Selected Janus stream and RTP input

Realtime transport

Speech, events and response audio

Exhibition services

Tool and action execution

MCP action service

Tools for configured action lists

Exhibition control

Configured displays and media

Shared infrastructure

Use-case settings

Session context and available tools

MQTT broker

Commands, state and transcripts

Janus audio gateway

Input streams and response playback

OpenAI Realtime

Speech and model responses

Read the connections
  • Controls: guide/admin interfaces exchange commands, state and transcripts with the session controller through MQTT.
  • Configuration: shared use-case settings supply session context and the available tool connections.
  • Input: interfaces connect to Janus over WebRTC. The orchestrator’s input adapter receives the selected stream, and the coordinating layers forward its RTP packets into the realtime transport.
  • Conversation: the transport exchanges speech and events with OpenAI Realtime over WebRTC. Response RTP/UDP audio goes directly back to Janus, bypassing the input adapter.
  • Actions: the local agent session calls the MCP service over HTTP. That service publishes configured action requests through MQTT to exhibition control and returns tool results. A returned result does not verify that a display or physical action has finished.
Component groups redrawn from the application structure. The four components inside AI Orchestrator belong to one backend service; model, audio and exhibition services remain separate.

03 / The guide interface

Speak. Listen.
Follow the exchange.

I also worked on the interfaces that make the platform usable: transcripts, listening feedback, and push-to-talk controls that release reliably when disabled or removed. They let a guide follow the exchange and take over.

The AI assistant interface displaying a conversation transcript with a demonstration question and response.
Reply state · Demonstration transcript
The AI assistant interface in its listening state with the push-to-talk control active.
Listening state · Push-to-talk held down

Running assistant interface · Simulated local services; no audio streamed