Fine-Tuned & Time-Boxed LLMs

aisot’s models are fine-tuned every quarter, in sync with fiscal periods, leveraging an encoder-based transformer specifically optimized for financial tasks such as return predictions. These sentiment factors, derived from LLMs, enrich expected return forecasts in quantitative models, offering a more accurate outlook on future performance.

To prevent hallucinations and minimize look-ahead bias, aisot uses time-boxing and integrates LLM outputs with quantitative models under strict portfolio constraints. By combining sentiment data with Bayesian frameworks, aisot ensures reliable, real-time insights that align with client-specific risk models, delivering actionable investment intelligence.