This is the single most dramatic re-acceleration I've ever seen. So excited that Z and Ro are finally sharing the story.
This team has been absolutely, exceptionally gritty in their execution around one of the most important health care innovations in history (GLP-1s)
@rexsalisbury There’s a slow company that has re-accelerated like nothing I’ve ever seen before in my career. Basically never better on it happening
Can’t wait to share more about
@TheEthanDing My point was just that it was indicative of how they’re positioning the company. Obviously true that their revenue is mostly labs but clearly they want the forward story to be enterprise
@uninsightful Yes and yes. I just meant it’s the story they’re trying to tell which is ultimately a future indicator (if only aspirationally)
I’m sure the revenue chart today is the inverse
We raised our $750 million Series D at a $20 billion valuation from @benchmark, @generalcatalyst, @nvidia, @salesforce, and @zoom.
@mercor scaled from $1M to $3B in run-rate revenue in 27 months, the fastest in history to $3B.
For 2 years, we've organized human intelligence to build evals and training data for every frontier lab.
The labs are the leading indicator for AI startups, then the Fortune 500.
Our growth has accelerated over the past 6 months as enterprises start evaluating and training their own models. For many, owning their intelligence is existential.
@uninsightful Yes and yes. I just meant it’s the story they’re trying to tell which is ultimately a future indicator (if only aspirationally)
I’m sure the revenue chart today is the inverse
Today’s data market is immature: no units, no prices, valued only at sale.
Value is in moving up the chain by transforming data and getting closer to customer value, not selling raw data.
The current regime won’t last, but the market will. More people will train more models forever.
Long term it splits: a synthetic Walmart of tokens and a scarce market for novelty.
Novelty never runs out, both because the diffusion timeline is incredibly long and because deploying AI creates new edge cases. The firm becomes a task factory.
As data gets priced, it enters the capital structure and data allocation becomes a core CEO decision.
What does it take to push frontier models forward?
@latentspacepod's first deep dive with an AI data company. Our team walked through our own datasets, life sciences, finance and safety, step by step.
Worth your time if you care about progress and alignment of AI.