TECHNOLOGY

The Sanistra platform integrates a distinctive combination of AI and blockchain technology.

Our prediction engine uses specialised algorithms rather than generic approaches. We develop custom language learning models (LLMs) for each asset class within our remit, training them on the specific variables that influence gold differently to art or oil differently to real estate, for example. These specialised models analyse diverse data, including trading patterns and social sentiment, to identify correlations that traditional analytical methods might miss.

Effective prediction systems depend on data quality. Our research team identifies information sources with a proven ability to predict outcomes, systematically filtering out irrelevant information that can compromise conventional models. This methodical approach to signal quality ensures that our users receive insights based on substantive factors rather than merely prominent headlines.

Our preprocessing pipeline removes anomalies and outliers that can negatively impact analytical systems. We have developed specialised cleaning protocols for each data category - for example, financial reports are processed differently to social media sentiment or supply chain disruption data. This granular methodology ensures that our models are trained using representative data rather than statistical artefacts.

Each asset-specific model undergoes comprehensive training using Transformer architectures to identify subtle relationships between seemingly unrelated variables. The fine-tuning process is ongoing - models adapt to evolving market conditions through transfer learning techniques that preserve institutional knowledge while incorporating emerging patterns.

These trained models integrate real-time data through dedicated pipelines that maintain continuous market awareness. Unlike systems that process information in batches, our models immediately update predictions when new, relevant data becomes available. This allows users to receive signals before markets have fully incorporated new information.