Our goal is to build a cloud native suite of quantitative and qualitative investment research tools that at least 10x the productivity of investors and analysts, across asset classes, using state of the art models and technology.

By automating the investment research process, our Investment Research Technology products will allow investors and analysts to focus on proprietary value add and client engagement. Most importantly we aim to free up valuable time to allow investors and analysts to do what they do best.

Some areas of focus will include:

• Fundamental analysis via Machine Learning*

• Big data analytics

• AI agents to collect, visualise and analyse data

• The automation of financial analysis*

• Forecasting corporate earnings

• The automation of technical analysis

• Sentiment analysis

• Sustainability analysis*

• The automation of forensic accounting

• Relative value idea generation

• Forecasting economic variables*

Current stage

We have carried out preliminary research on all focus areas listed above. Those marked with an asterisk above are under current development with minimum viable products (MVP) reached in certain areas of fundamental analysis via machine learning and the automation of financial analysis. Here we are using APIs to collect open source data and using python libraries have built tools that make predictions on the value of certain types of assets. We also have a MVP that conducts financial statement analysis on an automated basis.

Next stage

While we continue development of automation of analysis and using machine learning to make predictions, our next step is to package these into AI agents. We are also planning to further test and create AI agents using large language models to speed up qualitative research processes.