Our core offer: We engage with individuals and teams in companies by assisting in their design, strategy and tactics and techniques in nurturing sustainable change implementation^© with ML/AI technology alignment.

Our belnova™ framework and connected learning design offer an evidence-based and data-informed pathway to engage with the next generation of self-directed learning and performance enhancing L&D with significant application of traditional and machine learning methods. Our agile framework is platform-agnostic and utilises multi-vendor integrative tools with co-creation and co-pilot use-cases, currently undertaking our own deep-dives in the Corporate Compliance Training and Healthcare Right-Skilling sectors. As of 2025, we pay particular attention to the digital health and healthtech sub-sector and emerging glocal behavioural change models.

Backed-up with our partners' track records, our advisory and programme expertise converges on internal digital capacity building; designing, delivering and evaluating individualised and corporate learning programmes, whilst remaining acutely mindful of promoting diversity, wellbeing and health balance.

Co-Designing Personalised Preventative Health & Precision Exercise

At an individual level, we support your 361° optimisation capabilities to live a balanced and healthier life for longer.

People Performance Advisory

At an organisational unit level, we support and add value to your team via our enhanced learning and development interventions by revalidating your learning ecosystem and digital and blended learning landscape, in order to review, refresh and recharge the way you undertake learning and better align with your people performance management. We cultivate a healthy, thriving workplace leveraged on Belnova’s health and healing ecosystem.

Bringing cost-effective and impactful learning by co-design, co-creation and co-production, our machine learning enhanced L&D elements include tools for enabling leadership skills solutions for industry 4.0, assessing practical 'Applied ML/AI' solutions and use cases via diagnostic reviews and 'learning by doing' projects. In so doing, we favour an ethical and transparent relationship model that focuses on our clients' capability building, to discover the highest-value sustainable solutions based on rigorous, in-depth and objective analysis.

Governance and Compliance Learning

As the use cases of machine learning (ML) and artificial intelligence (AI) increases significantly across industries, the need for better and consistent (e.g. transparent, fair, and safe, aiming for transparency, explainability, and fairness) governance and compliance standards become a mission-critical priority.

Despite the recent slowing trends, applied ML/AI have vast potential, ranging from enhancing manufacturing and logistics processes to providing personalised services to consumers and in healthcare solutions. Robust governance frameworks serve as the cornerstone of responsible ML/AI adoption, safeguarding return on investment, mitigate potential risks and ensuring effective, legal and ethical use.

Governance and compliance frameworks require the full participation of many stakeholders outside and inside an organisation: this requires nurturing a learning culture, which can be brought about only by an orchestrated and continuous effort. Our curated signature plans building on our bespoke evidence-informed toolkit include AI Governance Audits and Building Resilience in Changing Times advisory blocks, including core elements of Compliance and Risk Assessment.

In our solutions, we draw on global research and best practice guidelines including work undertaken in the EU (particularly Germany), Japan, Singapore and U.S.: Scanning globally, a recent 'unified framework', introduced by the EU, where the EU AI Act requires evidence showing how responsible AI principles are embedded into governance frameworks to adequately assess and mitigate AI risks. Regulators, investors and civil society are likely to intensify their scrutiny of ML & AI, amplifying the demand for transparency and trustworthiness in use case applications and emphasising the paramount importance of robust governance and compliance infrastructure.