This post was originally posted on LinkedIn.
I spent 15+ years in B2B GTM and product before moving into VC 2 years ago. People often ask me if I miss operating, and while the FOMO is real in today’s fast-paced AI-fueled era, the thing I tell them is that I really miss a dashboard. It might sound funny but one of the hardest parts about moving from operator to investor is the loss of fast feedback loops.
As an operator, I spent a lot of time diving into reports and dashboards. Every morning: what changed, why, what do we do next? In VC, those loops take years.
And the more time I spend with teams building AI-first, the more I realize that operators today can’t afford slow feedback loops either. When you’re leading product, marketing, or engineering teams at hyper-growth companies, you don’t have that time. You need to know what’s happening in your funnel and in your product - engagement rates, drop-offs, errors, etc. - and you need those insights now.
Gone are the days of putting in a ticket for the data science team, waiting for them to query DBs (very expensive ones), and then build the report you need. Or attempting to build your own reports in legacy BI tools that aren’t user friendly nor intuitive. A new era has arrived that gives teams instant access to the health of their business.
AI-native Teams Choose Postgres
The industry built an entire analytics ecosystem assuming teams would be large and specialized. But those assumptions aren’t true anymore. We’re seeing leaner teams and more generalized roles, with emphasis being placed on curiosity and bias for action.
From a database perspective, it’s safe to say that Postgres has won. Snowflake paid $250M to acquire a Postgres company. Databricks paid $1B. And Supabase, the fastest-growing Postgres platform in the world, has gone from $765M to $5B in valuation in a single year, crossing 7 million developers and 100,000 GitHub stars in the process.
Most of the teams building on Supabase are lean, AI-native, and moving fast. But when someone asks "how many users tried the new feature?" or "what does retention look like?", the answer still requires tracking libraries, data pipelines, a warehouse, a BI tool, and an analyst to make sense of it all. By the time the report or dashboard ships, it's already stale.
This is where Dreambase comes in.
Dreambase replaces that entire stack with a single connection to your database. It’s not just another analytics tool, it’s a re-thinking of the stack. Once you connect your Supabase project and define key metrics through their AI-native semantic layer, you get production-ready dashboards and reports in seconds. No ETL, no warehouse, no data engineering required. The AI agents understand your schema and write accurate queries using your actual data.
The ‘ah ha’ moment is near instantaneous for customers. I shadowed several customer calls and saw the same reaction over and over. The sentiment was hard to ignore.
"I’m incredibly impressed by how well Dreambase just interpreted our DB, it was very cool…it intuitively understood how things stack together at a very high level.”
Why we Backed the Dream Team
Dreambase was designed from the ground up for how modern teams build. A few things stood out to us at Mercury Fund:
The founders. At this stage, it always comes down to the founders. I met Andy 4 or 5 years ago when we were both operating and have stayed in touch over the years. Andy is a driven, natural community-builder (he runs Lenny’s product meetups, a pickleball club, and is active in several builder communities) with an infectious personality. His product background gives him a customer-centric edge. He and Kyle, who spent most of his career in the data and analytics space at Teradata, MicroStrategy, and eBay, partnered up a couple of years ago. They previewed their v1 product with me a year(ish) ago, which has since been scrapped for what they’re building now. I was impressed by how quickly they pivoted. That speed of iteration is exactly what this market demands, and it’s what millions of devs (both traditional and ‘vibe coders’) need: insights so that they too can act quickly.
The market is massive, and growing quickly.
I highlighted some of the staggering stats above but even if you’re only slightly paying attention to where the market is heading, you know the number of devs building apps, products, and companies isn’t slowing down anytime soon. And if that’s true, then the need for real-time, self-serve insights is inevitable. Their wedge into Supabase is a clear example of the market’s pace: Supabase is rumored to be fundraising around a $10B valuation.
The Supabase partnership is real.
Dreambase is a featured integration in the Supabase marketplace, and several of Supabase’s execs joined this round as angel investors. When the platform itself is backing the analytics layer built on top of it, that's a pretty strong signal of conviction.
The vision extends into a broader ecosystem.
Supabase is the wedge, but Postgres is the long game. As more companies standardize on Postgres backends, Dreambase's surface area only grows. The goal is to become the AI-native decision layer for modern companies, starting with Supabase and expanding across every system a team runs on.
Austin-native.
Always a plus. 🤘
The Bigger Bet
The analytics stack has been broken for a long time. Lean teams have been duct-taping together tools that weren't built for them, paying for complexity they don't need, and still not getting fast answers. Dreambase is the first product I've seen that actually solves this for the way teams build and operate today.
This week, Dreambase announced their $3.7M Seed round. We're thrilled to be on this journey with Andy, Kyle, and the Dreambase team. If you're building on Supabase, check out their free database Report Cards at dreambase.com.
And if you're building something in this space or want to dig into the thesis, I'd love to hear from you. Drop a note below or ping me on LI.
