The WHAT: Solution
BaseModel Value Proposition
The Goal: Liberate the Full Potential of Data Science Teams
We envision a world where data science teams drive transformative business outcomes, achieve exceptional predictive accuracy, and operate at peak efficiency. To realize this vision, our solution must meet the following goals:
- Process raw behavioral data to eliminate the need for feature engineering and data pipelines.
- Scale efficiently to handle large volumes of data.
- Deliver top-notch predictive accuracy to drive optimal business decisions.
- Implement flexibly to meet diverse needs for hosting, confidentiality, and privacy.
The Solution: BaseModel – Innovation Meets World-Class Science
Our solution is an advanced product, developed over years of research by experts in AI, mathematics, and computer science. It is a private behavioral foundation model, supported by proprietary algorithms and an optimized neural network architecture, connectable and implementable in various ways.
Foundational Model for Behavioral Data
BaseModel uniquely applies to behavioral data the approach previously leveraged by ChatGPT, DALL-E 2, Stable Diffusion, and other models that have revolutionized text and image processing:
- A foundation model is initially trained on large-scale and diverse behavioral data. This training equips the model to capture diverse patterns and generalize across various behaviors and use cases.
- Subsequently, specialized downstream models are fine-tuned for diverse tasks to address specific business needs, such as propensity, churn, recommendations, and more.
This approach combines cutting-edge predictive accuracy with high cost-effectiveness, replacing the need for hundreds of specialized models trained from scratch.
Award-winning science
Our proprietary algorithms – Cleora and EMDE – simply and efficiently embed complex behavioral relationships between entities as graphs, and then convert these interactions and other supporting information into behavioral profiles. With them at hand, we have representation of entities which can be fed to a model tasked with many different objectives, eg. recommendation/ranking, classification, regression/scoring and others.
Subsequently, our optimized neural network architecture allows the foundation model and its downstream models to train at speed and scale, providing deep insights into entities and their interactions, accelerating prediction generation and enhancing accuracy.
Our science has been battle-tested in numerous competitions and challenges, competing on equal terms with – and often beating – the world's top AI powerhouses.
A private model, delivered they way you need
BaseModel allows for the creation of your own private fundamental model, tailored to your specific needs. It can connect to various data solutions, be deployed flexibly on various environments and consumed as container or native app to meet the specific needs of your organisation.
Updated 4 months ago