Whitepaper

Basel, Switzerland – October 6, 2026 –
This whitepaper explores why reliable AI in Life Sciences increasingly depends on context, evidence and relationships, and how semantic and graph technologies can help organisations make AI-supported decisions more traceable and defensible.

Barcelona, Spain – April 22, 2026 –
In this whitepaper, we examine the gap between fast AI-assisted coding and governed software delivery, showing how Spec-Driven Development gives teams a clearer way to define behaviour, structure implementation, and improve traceability and reviewability.

Basel, Switzerland – February 10, 2026 –
In this whitepaper, we explore the AI divide and how Knowledge Management protects capability by preserving reasoning, context, and decision logic, so AI use supports the learning journey instead of accelerating forgetting.

Basel, Switzerland – January 14, 2026 –
In this whitepaper, we examine why metadata standards remain fragmented in pre-clinical research and how metadata repositories, governance, and cultural adoption can create more consistent, reusable, and reliable data.

Basel, Switzerland – December 18, 2025 –
In this whitepaper, we explore how the FAIR Principles evolved, why their meaning became diluted, and why semantics, metadata, and persistent identifiers are essential for creating machine actionable, interoperable data in the AI era.

Basel, Switzerland – November 18, 2025 –
In this whitepaper, we show how the reuse of Individual Human Data can become compliant and scalable, reducing the friction of consent checks, inconsistent formats, and fragmented systems, and enabling researchers to request, receive, and use clinical data more efficiently.

Basel, Switzerland – September 16, 2025 –
In this whitepaper, we explore how the psychology of knowledge management shapes decision-making in Life Sciences—addressing biases like overconfidence and automation bias, and highlighting remedies that enable safer, faster learning and more reliable outcomes.

Basel, Switzerland – July 16, 2025 –
In this whitepaper, we examine how genuine, data-centric transformation is key for Life Sciences and Biotech organizations to overcome digital complexity—unlocking scalable value from decades of siloed data and ensuring competitiveness in an AI-driven future.

Basel, Switzerland – June 2, 2025 –
In this whitepaper, we explore how a risk-first approach enables Life Sciences organisations to overcome the POC bottleneck—shifting AI from isolated pilots to compliant, scalable deployment.