Predictive ML in Research & Data
10 companies using predictive ml technology in the research & data sector. Traditional ML algorithms for classification, regression, and scoring models
Directory
Companies by Funding
DataRobot
AutoML platform for finance
C3.ai
AI applications for enterprises
H2O.ai
AI/ML platform for finance
Keyway
AI-powered real estate investment manager
Plan A
AI decarbonization platform
Normative
AI-powered carbon accounting
Keye
AI for private equity due diligence
Auquan
AI agents for financial research workflows
Related
Other AI Technologies in Research & Data
Related
Predictive ML in Other Segments
Frequently Asked Questions
How is Predictive ML used in research & data?
Traditional ML algorithms for classification, regression, and scoring models In the research & data sector, Predictive ML is applied by 10 companies tracked by AIFI Map, with $1.9B in combined funding. Leading companies include DataRobot (AutoML platform for finance); C3.ai (AI applications for enterprises); H2O.ai (AI/ML platform for finance).
Which research & data companies use Predictive ML?
The AIFI directory tracks 10 research & data companies using Predictive ML, with a combined $1.9B in funding. DataRobot, C3.ai, H2O.ai, Keyway, Plan A, and 3 more. (Source: AIFI Map directory.)
What is the most funded Predictive ML research & data company?
DataRobot is the most funded company using Predictive ML in research & data, with $1.0B raised. AutoML platform for finance Followed by C3.ai ($481M).
How does Predictive ML compare to other AI technologies in research & data?
In the Research & Data segment, Predictive ML ranks #3 out of 8 AI technologies by adoption, with 10 companies and $1.9B in combined funding. The most widely adopted technologies in research & data are Data Platform (29 companies, $19.1B funded); LLM / NLP (19 companies, $105.5B funded); Predictive ML (10 companies, $1.9B funded). While Predictive ML focuses on traditional ml algorithms for classification, regression, and scoring models, alternative approaches include Data Platform, which data aggregation and enrichment platforms with minimal ml, and LLM / NLP, which large language models for nlp, chat, document understanding, and text generation.