ZortifyLabs

Looking for groundbreaking, human-centered technology? Look no further than ZortifyLabs, where a team of interdisciplinary experts bridges theory and practice to create innovative, accessible, and ethical technologies that empower human decision-making.

Pioneering the intersection of Science, Technology, and Human-Centered Design

Zortify Labs embodies the human element behind our constantly evolving suite of technologies and services. The core mission of the Labs team is to bridge theoretical innovation with practical application in the fields of psychology, computer science, and human-centered design.

As Zortify’s internal R&D hub, Labs champions interdisciplinary research and the development of ethical new technologies internally and alongside industry and academic partners. The Labs team comprises researchers, data scientists, psychologists, and designers, many of whom have an extensive scientific background and have published in top-tier research journals.

It’s no surprise that complexity excites us, but central to the Labs philosophy is making new technologies accessible to non-expert audiences. Developing usable, ethical, and explainable technologies builds trust and empowers human decision-making in an increasingly complex world.

Our Whitepapers
31.05.2023 Identifying the Correlation Between Language Distance and Cross-Lingual Transfer in a Multilingual Representation Space Prior research has investigated the impact of various linguistic features on cross-lingual transfer performance. In this study, we investigate the manner in which this effect can be mapped into the representation space. While past studies have focused on the impact on cross-lingual alignment in multilingual language models during fine-tuning, this study examines the absolute evolution of the respective language representation spaces produced by MLLMs. We place a specific emphasis on the role of linguistic characteristics and investigate their inter-correlation with the impact on representation spaces and cross-lingual transfer performance. Additionally, this paper provides preliminary evidence of how these findings can be leveraged.
10.05.2023 Invest in people: Why AI can be an added value in the selection process of early-stage entrepreneurs for funding Investors face the challenge of finding the right investments, and while financial reports and growth markets are important, the personalities of the founding team and employees are also critical. Investors need to evaluate soft skills such as leadership, communication, optimism, resilience, self-efficacy, and agility as they play a critical role in a company’s success. In this context, AI can help investors identify the soft skills of founders and teams. This whitepaper presents the use case of Uncap, a fintech company that has used Zortify personality assessment to measure entrepreneurial capital and disruptive potential when selecting early-stage entre-preneurs for funding in Africa.
10.05.2023 Comparison of the Psychological Capital of Founders and Their Employed Top Management This study examines the difference of Psychological Capital (PsyCap) of founders in comparison to their employed top managers in young companies. We use the PCQ (Psychological Capital Questionnaire) developed and tested by Luthans and colleagues to do so. Results were concluded on the basis of 36 responses from founders from Germany and Chile from 27 different young companies and the same number of answers from their respective employed top managers. A t-test for independent samples shows a significantly higher level in three of the four states of PsyCap among founders: self-efficacy, resilience and optimism. Hope is the only state in which founders don’t exhibit a significantly higher level than their employed top managers. Overall, PsyCap of founders is higher than their employees’.
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Natural Language Processing
Natural Language Processing
Natural Language Processing (NLP) is transforming the world of technology, enabling us to automate tasks, gain valuable insights from vast amounts of data, and communicate with machines in a natural, intuitive way. From chatbots to voice assistants, NLP has revolutionized how we interact with technology, making it possible for machines to interpret human language and respond intelligently.
Discover how we use NLP
Explainable AI

Explainable AI, or XAI, is an emerging field that seeks to create more transparent artificial intelligence systems. This transparency is crucial in building trust in AI and ensuring that decisions made by these systems are ethical, fair, and responsible. While there are challenges to developing XAI, researchers and policymakers are actively working to address them. At Zortify, the team is committed to the development of ethical and sustainable technology, with a focus on XAI. Their expertise in the field of explainability is leveraged to improve their products and push the field forward.

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Explainable AI
EU AI ACT
The EU AI ACT is a proposed legal framework for the development and use of artificial intelligence in the European Union. It aims to create a harmonized legal framework for AI development and use, using a risk-based approach. The regulation sets specific requirements and restrictions for each risk level, such as transparency and documentation requirements for high-risk systems. The EU AI ACT aims to protect fundamental rights and values while promoting innovation and economic growth. The regulation is currently in the legislative process and has a target to be approved and in force by 2024. Companies and organizations are recommended to begin preparing for the EU AI ACT by conducting risk assessments and adopting ethical and trustworthy AI practices.
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