Discover 26 funding sources for Machine Learning startups: VC funds, accelerators, and free resources.
The machine learning sector has 26 active funding sources globally, with funding trends showing steady growth with increased focus on sustainable business models.
Competition level is moderately competitive, making it moderately competitive with good opportunities for quality startups in this space.
Multi-location
seed stage focus
Multi-location
series-a stage focus
Multi-location
series-a stage focus
Multi-location
seed stage focus
Multi-location
seed stage focus
Multi-location
series-a stage focus
Multi-location
series-b stage focus
Multi-location
series-a stage focus
Multi-location
series-b stage focus
Multi-location
seed stage focus
Multi-location
seed stage focus
Remote + On-site
Remote + On-site
Remote + On-site
Remote + On-site
Remote + On-site
Remote + On-site
Machine Learning startup funding is moderately competitive, with 11 active VC funds and 6 accelerator programs globally. The average check size is $4.2M, requiring strong differentiation and traction.
Machine Learning investors typically prioritize strong technical team with domain expertise and clear market validation and traction metrics, along with strong technical teams and clear market validation. Domain expertise in machine learningis often crucial for gaining investor confidence.
Yes! Most successful Machine Learning startups apply to multiple funding sources. Start with free resources to reduce costs, apply to relevant accelerators for mentorship and initial funding, then approach VCs for larger rounds. Having multiple options creates leverage in negotiations.
Last updated: 8/18/2025 | Data aggregated from VC databases, accelerator programs, and startup resources |About our methodology