Aisot Raises CHF 2M to Scale AI Portfolio Intelligence

Zurich-based Aisot Technologies has built its business around that filtering problem. The ETH Zurich spin-off combines quantitative finance, machine learning and LLM-based news sentiment analysis to help asset managers, wealth managers and family offices turn large volumes of market information into portfolio decisions.

The company has now closed a CHF 2 million seed extension, backed by existing and new investors including family offices and angel investors. Felix Haldner, a former Partner at Partners Group and former President of the Swiss Funds & Asset Management Association, joined as a new investor. The financing follows Aisot’s CHF 1.8 million seed round in 2023, which was led by Haute Capital Partners.

Its AI Insights Platform supports portfolio construction, backtesting, optimization, rebalancing and monitoring. Larger asset managers can use the system to add quantitative signals to existing investment processes, while smaller firms gain access to data, AI and quant infrastructure they might otherwise have to build internally. Investment professionals can still combine those signals with their own research, constraints and conviction.

One unusual part of that machinery is Aisot’s approach to financial news. Its time-boxed LLMs are designed to use only information that would have been available at the moment a historical forecast was made. That matters in backtesting, where allowing a model to see future information can make a strategy appear more predictive than it really was. Aisot combines those sentiment factors with quantitative models and portfolio constraints.

The research engine underneath the platform spans financial time-series forecasting, sentiment analysis and volatility modelling. Aisot says its models have been trained using 400 million news articles, while its team brings expertise across AI, natural language processing and quantitative finance.

Co-founder and CEO Stefan Klauser says the company wants wealth managers in Switzerland and internationally to integrate AI into investment processes in a way that remains transparent and grounded. The company already operates through a network spanning Europe, Asia and the United States.

Aisot’s opportunity becomes more interesting as AI spreads through investment firms of very different sizes. If advanced portfolio intelligence becomes infrastructure rather than a capability reserved for firms with large quant teams, the competitive gap may shift from who can build the models to who knows how to use their signals well.