EXPERIMENT OVERVIEW

OVERVIEW

When AI understands what people need: TiConAI brings voice assistance to industry and logistics

How can employees in manufacturing, logistics, or service quickly access the information they need without searching through multiple systems?

That question is at the heart of TiConAI, an experiment within the European WASABI project led by SWMS Consulting GmbH.

TiConAI explores an AI-powered voice assistant that connects directly to internal systems such as ERP, inventory management, or documentation databases.

The aim is to automate routine queries, reduce response times, and give employees faster access to reliable data so they can focus on higher-value tasks. What makes it innovative

Uses Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) to deliver accurate, context-aware answers.
Integrates with enterprise systems to provide real-time information.
Supports intuitive voice interfaces on devices such as radios or mobile apps. Target results
50% automation of routine requests
40% shorter response times
90% accuracy in data retrieval

TiConAI demonstrates how people and AI can collaborate efficiently, transforming industrial data into meaningful, immediate answers.

TiConAI: Voice Assistance for Industrial Workflows

In many industries, valuable knowledge is locked away in ERP systems, databases, and technical documentation. Finding the right information can be time-consuming, especially for employees on the shopfloor or in the field.

TiConAI is addressing this challenge as part of the European WASABI project, led by SWMS Consulting GmbH.

The project aims to create an AI-based Digital Intelligent Assistant (DIA) that understands natural language questions and provides precise, real-time answers drawn from company data sources.

EXPERIMENT IMPACT

SMARTER ACCESS TO INFORMATION

TiConAI explores how artificial intelligence and speech technology can make everyday work in industrial environments more efficient. Employees can ask questions through a mobile app, computer, or even a company radio and receive instant, accurate answers on topics such as order status, stock levels, or technical documentation.
The vision is simple: information should come to the user instead of the other way around.

HUMAN–AI COLLABORATION

The system is designed to support, not replace, human expertise. By handling repetitive and routine queries, the assistant allows employees to focus on tasks that require judgment and experience. Through integration with existing enterprise systems, responses are always based on the most up-todate data. This ensures reliable information, reduces time lost to manual searching, and encourages a new, more natural form of human–AI collaboration.

EXPECTED OUTCOMES

During the experimental phase, TiConAI aims to achieve measurable improvements in efficiency and data accessibility:

Automate around 50% of routine information requests
Reduce response times by about 40%
Deliver data with approximately 90% accuracy
Achieve high user adoption through intuitive voice interfaces

These targets reflect the project’s broader goal: to show that AI-driven assistance can improve realworld industrial workflows, not just office-based processes.

LOOKING AHEAD

TiConAI serves as a model for how voice-based AI can enhance everyday work in manufacturing, logistics, maintenance, and customer service.

By combining modern AI technologies with human expertise, the project demonstrates that artificial intelligence can be practical, safe, and genuinely helpful — a partner that makes knowledge accessible exactly when it is needed.

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