The methodology for the IA40 is based on Madrona's experience investing in founders and engaging with researchers involved in AI and Machine Learning for over a decade, and inspired by a research and survey methodology developed by Wing.vc. This list was compiled by and voted on by experts in the space: investors who are funding the next generation of intelligent application companies, technology companies, and a leading investment bank.
In 2024, we received over 380 private company nominations from over 70 venture investors at 54 top-tier venture capital and corporate investment firms. Each judge had the opportunity to nominate companies for consideration in each category. The Madrona team vetted the companies to ensure they met the definition of intelligent applications.
After we collected the nominations, we asked the same venture capital investors to vote on their top 5 companies in each category (early, mid, late, and enabler). Each venture capital investor was limited to voting for only 2 of their portfolio companies.
We tabulated the votes from investors by category and leveraged PitchBook’s “Venture Exit Predictor Tool.” Their model considers and weighs many data points, including the average deal size of each round, number of employees, and number of investors. We weighted the venture community votes and PitchBook’s Venture Exit Predictor Opportunity Score to produce a final composite score that resulted in the 40 winners and 5 rising star enablers.
We define application intelligence as the process of using machine learning models embedded in applications that use both historical and real-time data to build a continuous learning system. These learning systems solve a business problem in a contextually relevant way — better than before, and typically deliver rich information and insights that are either applied automatically or leveraged by end users to make superior decisions.
Intelligent applications are: