Your data is your edge, but only if your AI is built on it. Rent a generic model and so can your competitor. The companies with an edge are deploying custom models that they own and improve over time.
Our co-founder @rhythmrg recently stopped by @southpkcommons to share how companies are owning their intelligence with Applied Compute.
@cognition@Lux_Capital@generalcatalyst@8vc One of the most brilliant teams Lux has continued to invest more to fuel them in every round possible!
Thank you @ScottWu46 for your talent magnetism as a founder leader and for the bar of brilliance and momentum you’ve set for @cognition !
1/ We’ve raised over $1B at a $26B valuation, led by @Lux_Capital, @generalcatalyst, and @8vc.
Our enterprise usage has grown >10x since the start of this year, and our run-rate revenue grew to $492 M.
We launched Devin two years ago as the first AI software engineer. Since then, cloud agents have gone from niche to mainstream, and today they are the fastest growing way to create software.
behind the scenes at AC, featuring what we now call the pinapple shirt
excited to share some of the work @raymondmfeng and I have done, RMSD has proved super valuable in our customer engagements!
Today we're announcing our Series C funding: $355M at a $4.65B valuation, led by some great investors @generalcatalyst and @Redpoint.
We've had insane growth in the last year, but we're still very early. So proud of the team and what we have built so far!
Huge congrats to @bernhardsson@akshat_b and the whole @modal team!
In an age where so many teams are moving to own their own models, Modal provides powerful primitives we use for training and serving models at scale.
Frontier models set the floor. Specialized models raise the ceiling.
With Modal, @AppliedCompute is training custom agent workforces for companies like DoorDash, Mercor, and Cognition.
Exactly! The winning strategy is not betting on who has the best model this month. It is building the deployment layer where intelligence actually compounds.
That means serving the best possible agent tokens on durable infrastructure: route to any model, train your own when it makes sense, and own the context, harness, environment and interfaces around the agent.
Applied Compute is building this customer-first deployment layer. We help customers build intelligent systems where the value compounds on their side.
The real power of forward deployed engineering has always been putting strong technical people directly alongside the operators who own the outcome. That proximity forces the work to solve the actual problem instead of some sanitized version of it.
In the AI era this principle has become even more valuable. Agents can now sit inside real workflows and improve from actual decisions, which means the highest-leverage work is extracting the tacit knowledge that lives with subject matter experts, building evaluations that reflect how things actually break, and closing the production feedback loop so agents get better from real outcomes.
For the better part of 4 years, I’ve considered myself reasonably early to emerging sub-themes in AI and Robotics.
Every time I begin researching a new one, I encounter promising private companies and, without fail, @GavinSBaker or @wolfejosh are already investors in them.
Harvey is a great example of a company carving out a strong competitive position by building proprietary intelligence
We had a great experience teaming up with them to support their new Legal Agent Benchmark with post-training and eval methodology
Thanks @gabepereyra for visiting during our team all-hands today to break down what proprietary intelligence looks like in law!
seeing all the old house photos really brings me back. lots of fun memories and late night gym sessions... wish I took more pictures but all I have is us trying to recreate the cognition logo with dumbbells
We started the company knowing that, despite remarkable progress on public frontier models, there was a frontier that had not yet been explored. The destination was clear (finding ways to leverage data, internal processes, and knowledge built up over many decades to produce systems that get better over time), but we didn't have the infrastructure to get there. The "private frontier" belief has played out more now, as the winners of this era will get there by honing their internal intelligence every day.
We are building across the stack at AC! Enterprise agents should work like your employees do - getting better over time by learning from experience!
All of this starts with building durable infrastructure for cloud agents. Context Engine is just the start!