R2M Solution - Company and Team

Innovation company bridging research and market in AI, AR/VR, and big data.

150+ specialists,
40% women,
25% PhD.

Involved in 100+ EU research projects and with an entire division for B2B and commercialization of products.

Giuseppe Scarpi

Project coordinator

MSC in Engineering,
Business Development manager in R2M,
leads project activities and relationship with WASABI and DIHL.
Also responsible for AVANTI (skill assessment SaaS brought to VAFER as background IP).

Marco Demutti

Technical Leader:

MSc in Engineering,
AI and AR/VR expert,
will lead and contribute to software development, model tuning, integration in the WASABI ecosystem

Jyoti Dhiman

Software developer:

Sc in Computer Science,
Experience in AI, and data science, she will contribute to the development of the tool and organize the validation.

Michela Zabaglia

Expert in communication and dissemination:

marketing, communication & dissemination specialist,
strong knowledge in content production,
communication for EU Institutions and projects,
worked for EU agencies ETF and EFSA

EXPERIMENT OVERVIEW

OVERVIEW

Goals: VAFER enhance both the onboarding and on-the-job training processes in high-tech manufacturing

How: innovative AI and voice-powered solutions with integration of OVOS and our proprietary solutions

Onboarding: leverage AI-based voice interviews to discover existing skills and personalize the onboarding

Training on-the-job: voice assistant assist trainees with hints and reminds during hands-on sessions

In general: improve overall trainee satisfaction and performance

CHALLENGES

Technological integration of OVOS and other AI technologies to obtain an effective, seamless integration
Data privacy with sensitive data like CVs and procedures
User adoption to demonstrate concrete advantages and convince of effectiveness of privacy measures
Customization and scalability for different industries
Real-time performance to ensure accurate feedback without latency is essential for practical training sessions

OBJECTIVES

Reduce onboarding by up to 15% through AI-driven skill assessments and voice interviewer to personalize onboarding.
Enhance practical training with real-time, voice-activated support on practical sessions, reducing cognitive load, errors.
Promote knowledge retention through active learning, with AI-driven interactions to encourage professional growth.
Integrate advanced technologies OVOS and other AI technologies for effective onboarding and training solution.

EXPERIMENT IMPACT

EXPECTED RESULTS (KPIs)

KPI Expected value
Reduction in average onboarding time ⇒ Up to 15% compared to the current baseline ⇒
Improvement in onboarding liking ⇒ Up to 20% measured with pre- and post-assessment
Avg error reduction during practical sessions ⇒Up to 25% compared to the current baseline
Improved training retention ⇒ Up to 15%, measured with mentor assessment

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