We started Streamline in 2022 to solve critical funding bottlenecks in the energy transition. Like other companies that defined this first wave of AI as we know it today, we also focused on leveraging LLMs for writing. And in our case, it was government proposal writing. Think grants, RFPs, etc.

We scaled that business to hundreds of customers and helped all types of organizations win $100+ million in funding. From non-profits to city governments to Deloitte, our customers used our AI products to discover, diligence, and apply for all sorts of public funding opportunities.

We sold the company earlier this year, and I've been mostly exploring 2 things since then:
- Unlocking Abundance and supply side progressivism
- Building AI agents as good as Claude Code for real-world use cases

Right now I'm building an AI-native Google Maps for GIS workflows. It allows you to ask for things like "all substations with available capacity in Texas" and generates .gpkg files to visualize on our GUI. We currently have 2 successful case studies with hard tech companies and are rolling pilots out with 5 more customers.

If this sounds interesting, please reach out.