Is a deep-tech company with expertise in AI and Assistive Technologies.

⇒  We are a multidisciplinary team of dedicated engineers and scientists.

Developing an AI-based voice assistant system for electronic assembly and installation tasks, specifically targeting Social Workplaces.

1. Conversational AI for Task Execution
2. step-by-step guidance

• Ensure 95% accuracy in voice command recognition and response during testing.
• Task completion time reduction of new employees – target: 20% faster assembly times compared to traditional method
• Percentage of worker satisfaction and inclusion – target: 20% improvement in satisfaction of workers.

The success of the VAFER experiment will be measured through concrete Key Performance Indicators (KPIs) tracked against the company’s current baselines. The measurable targets include a 15% reduction in onboarding time, a 20% improvement in user onboarding satisfaction (measured via pre- and post-assessment surveys), a 25% reduction in errors during practical sessions, and a 15% increase in training retention (measured via mentor assessments).

End users will benefit from a personalized, engaging training experience that drastically reduces mental burden, while stakeholders will see reduced training costs and smoother workflow integration. Environmentally, by successfully training operators to repair and remanufacture obsolete electronic components rather than discarding them, the solution directly supports sustainability and circular economy principles in the electronics lifecycle.

SYLTEC is a company that provides comprehensive engineering and technology consulting services, delivering high value-added solutions tailored to the needs of our clients.

We develop disruptive solutions that integrate advanced technology to transform key sectors such as industry, healthcare, and tourism & cultural heritage. Our mission is to generate real impact through the application of artificial intelligence, extended reality, and process automation, delivering tools that not only innovate but also provide direct value

SYLTEC, in collaboration with DIHBU, is developing an intelligent virtual assistant tailored for the manufacturing industry.
The system focuses on two key areas: agile onboarding of new operators and incident resolution.
It leverages open-source Large Language Models (Llama3, Qwen3, Gemma3…) combined with Retrieval Augmented Generation (RAG) to provide contextual and accurate guidance.
The assistant will be integrated into the OVOS platform, deployed through Docker containers, and accessed via a lightweight touch-based interface supporting both voice and text interaction.
The outcome will be a validated prototype in an industrial setting, demonstrating the efficiency of AI-driven assistance in reducing training time and supporting complex processes.

1. ≥80% accuracy in AI-generated answers (relevance, correctness, context).
2. ≤15% hallucination rate, ensuring reliability in industrial use cases.≥25% reduction in onboarding and incident resolution time, improving productivity.
3. Development of a functional prototype reaching TRL 6–7, validated in a real manufacturing plant.
4. Demonstrated replicability and scalability of the assistant for other SMEs and industrial contexts.

• Company Manager Domain Expert
• Technical Manager
• Team Leader
• IoT & Integrations
• Front End
• AI & Data Science
• Back-End

Development of voice and text based digital intelligent assistant to be integrated to an energy management system software to increase human interaction and well-being while increasing energy performance of industrial facilities.

• 30% reduction in overall energy management efforts of operational users including understanding the standards,    requirement, documentation, policy and procedures
•  Reduction in technical intervention of system users to monitor, analyse and report energy efficiency for better energy   management tasks by 25%
•  Successful integration of Intel50001 into the WASABI technology platform with DIA implementation of at least 3   different modules including monitoring, analyses and documentation.

Founded in 1986 and located in Getxo (Biscay)
Focused on the development of Business Management Software

Mission: To help business optimize their processes and leverage corporate knowledge for effective decision-making.

Integrate a voice-based assistant into CEESA’s ERP systems

Leverage NLP, speech recognition and AI to enable intuitive voice commands and intelligent decision-making across ERP modules

• Reduce manual data entry time in ERP.
• Increase efficiency of key ERP workflows.
• Improve ERP data accuracy.
• Enhance real-time data accessibility.
• Reduce time for common ERP tasks.
• Optimize ERP-driven processes.
• Increase user satisfaction with ERPs.