Startup Profile
DataNXT

Introduce yourselves

Tell us in three sentences who you are

DataNXT was founded in 2024 to make powerful AI reliably and auditably deployable in production. It is a platform that brings artificial intelligence in the financial sector to a production-ready and verifiable level. With scientific excellence, we translate routine tasks into AI-supported workflows in which every statement can be fully verified. Our goal is to establish AI not as a black box but as a transparent, controllable infrastructure.

What challenge does your startup address and how did the idea for it come about?

The idea emerged from scientific work at the intersection of finance, AI, and IT. Our founding team includes researchers who deliberately chose to translate academic insights into an industrial product. The biggest challenges lay in clean document decomposition, fulfilling compliance and data-sovereignty requirements, and designing these principles to scale reliably in productive systems.

How does DataNXT work and how does AI support this project?

DataNXT functions like an intelligent operating system for financial data. It processes unstructured documents such as annual reports, investor-relations presentations, or regulatory disclosures, breaks them down using AI into coherent content segments, and enriches them with semantic and temporal context. These data are then linked in a knowledge graph that enables queries, analyses, and automated reports. Every processing step is transparent and traceable: users can always see which primary source a result is based on and how it was derived.

AI plays a dual role in this architecture: on the one hand as an enabler for semantic decomposition, classification, and relation extraction in complex texts; on the other hand as a controlled tool embedded in a system of six central control mechanisms ensuring that every analysis remains verifiable, auditable, and reproducible.

How have your previous experiences in the finance or technology sectors shaped your vision for DataNXT?

Our background in tech, NLP, and financial analysis has equipped us to design AI not as a black box but as a transparent process. Together with researchers from Groningen, Halle, and Frankfurt, we work on bringing state-of-the-art models with scientific precision into real production environments. This close link between research and industry is at the core of our product philosophy.

Can you give a concrete example of a use case?

In credit-risk reporting, DataNXT automates the extraction, aggregation, and allocation of relevant data points from annual reports and IR documents directly into a reporting template including source references, audit trails, and consistent calculations. This transforms previously manual analytical workflows into reliable, reproducible, and significantly more efficient processes.

What is your most important goal this year?

Our focus for 2025 is to implement the first proof-of-concept project with an enterprise customer and to deepen a clearly defined use case.

Let’s look into the future: where could the project be in five years?

In five years, we envision DataNXT as the leading platform for controllable AI in the financial industry and as the backbone of data-intensive business processes that structure, validate and automate qualitative information.