In the dynamic world of finance, Valerian is not just keeping pace but setting the pace. We are pioneering the implementation of artificial intelligence (AI) and, more specifically, neural networks across our proprietary data. This innovative approach is transforming the way we underwrite and has the potential to offer clients unprecedented insight into their business data. This is a significant step towards our goal of continuous underwriting and full automation of our Intelligence-Based Funding (IBF) model.


Building the Valerian Data Lake: A Growing Repository of Information

At the core of our operations is the Valerian data lake, a growing repository of data collected from various platforms. Data lakes are crucial for the development of neural networks, as they provide the vast and diverse datasets these AI models need to learn and improve. The more comprehensive the data, the more accurately the neural network can identify patterns and make predictions.
We are in the process of expanding this data lake to include a wide range of data, such as marketing, e-commerce, customer interactions, accounting, and payments. This diverse data collection is what sets Valerian apart. Our unique proprietary data, once fully integrated into our data lake, will provide a holistic view of our clients’ businesses and their growth potential. This comprehensive data pool will not only enhance our underwriting process but also empower our clients with valuable insights derived from our advanced neural network models.


Neural Networks: Simplifying Complexity

Neural networks, a subset of AI, are designed to mimic the human brain’s ability to recognize patterns and make decisions. They consist of interconnected layers of nodes, or “neurons,” that can process and learn from data1,2. By applying comprehensive neural network models to our data, we can analyse vast amounts of information in ways that traditional methods cannot match.


Deep Data Insights for Founders

The implementation of neural networks not only enhances our underwriting process but also provides the potential for deep data insights to our clients. These insights can reveal patterns and correlations that can help founders make informed business decisions3. For instance, neural networks can model customer behaviour, purchases, and seasonality, and segment customers while analysing credit4.


A Leap Forward in Efficiency

By harnessing the power of neural networks, we are able to streamline our underwriting process, making it more efficient and responsive. This allows us to provide funding solutions faster, helping our clients seize opportunities as they arise.


Intelligence-Based Funding: A New Era

Our Intelligence-Based Funding (IBF) model is an evolution of traditional Revenue-Based Funding (RBF). It uses continuous assessment and optimal advance size, focusing on ‘economic value creation’ to ensure capital drives real business value. This approach reduces unsecured lending risk and preserves business margins, making it a smart choice for sustainable, risk-managed growth.


The Future of Valerian

As we continue to refine our use of AI and neural networks, we move closer to our goal of continuous underwriting. This process will allow us to provide dynamic, tailored funding solutions for online businesses, further enhancing our IBF model’s effectiveness.
At Valerian, we’re not just providing funding; we’re building a future where AI and data drive smarter, more efficient financial solutions. For founders looking to fuel their growth, and for investors excited by the potential of AI in finance, the ‘Neural Network at Valerian’ story is just the beginning.



  1. Harvard Business Review. (2017). The Business of Artificial Intelligence.
  2. Harvard Business Review. (2018). Most of AI’s Business Uses Will Be in Two Areas.
  3. ResearchGate. (n.d.). (PDF) Neural networks in business applications.
  4. ScienceDirect. (n.d.). Artificial neural networks in business: Two decades of research.


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This field is for validation purposes and should be left unchanged.


This field is for validation purposes and should be left unchanged.


This field is for validation purposes and should be left unchanged.