On August 20, 2025, Capria Ventures ran an exclusive AMA-style workshop titled “From Lab to Reality: What It Really Takes to Deploy AI” The session featured Diego Oppenheimer, an AI founder and venture partner, in conversation with Capria AI Evangelist Will Poole. Drawing on Diego’s experience building and selling an MLOps startup and now incubating the next wave of AI companies, the workshop explored how founders can leverage a startup’s core advantage: speed. Attendees left with tactical playbooks for managing API costs, unleashing developer creativity, and engineering for cost-effective AI delivery.
Key themes included
- Speed as a Moat: Why rapid iteration is a startup’s only true competitive edge.
- Zero-Cost Experimentation: How to structure innovation when the cost of prototyping is approaching zero.
- Value-Based Pricing: Why you should price the outcome, not the “AI layer.”
- Being AI Sherpas for corporate clients
The workshop attracted a global audience of founders and operators interested in scaling AI-powered products in the Global South and beyond.
Click here to see the Key Insights Document
About the Speaker
Diego Oppenheimer
AI Founder, Venture Partner, MLOps Expert
Diego Oppenheimer is a veteran entrepreneur and leader in the data and AI space. His journey began at Microsoft, where he worked on foundational products like Excel and PowerBI. In 2013, long before the recent AI hype, he founded an AI company focused on machine learning operations, which he successfully sold in 2021. Post-acquisition, he led MLOps for the acquiring company before joining a venture fund with Stanford professor Chris Ray. In his current role, Diego incubates and advises the next generation of AI-native companies, drawing on over a decade of experience moving AI from the lab into production.
How Diego helps businesses
- AI Adoption Strategy: Advises CTOs on leveraging speed and iteration to overcome the challenges of internal AI integration and scaling customer-facing solutions.
- Rapid Experimentation: Champions frameworks for unleashing developer creativity by providing per-person AI budgets and fostering a culture of permissionless innovation.
- Cost-Effective Deployment: Provides playbooks for engineering cost-effective AI delivery, managing API costs through robust testing, and implementing value-based pricing models.
Current Focus
- AI Incubation: Actively incubating a portfolio of new AI companies, guiding them from concept to funding and acquisition.
- MLOps Best Practices: Evangelizing MLOps best practices that allow small, technical teams to avoid painful scaling problems later.
- Future of AI Infrastructure: Exploring the next wave of AI infrastructure and tools that will power the next generation of applications.
