Baseten will be one of the defining infrastructure companies of this era. Its Inference Cloud powers today's most advanced AI apps, and as post-training becomes inseparable from inference, they're working with app builders to create closed-loop learning systems that turn production data into compounding model improvement. We're proud to have led or co-led its $40M Series B, $75M Series C, and now its $1.5B Series F. It's Spark's second largest investment ever, behind only Anthropic. The team is special and the market still underestimates the size of the opportunity. We couldn't be more excited for what's to come.
1/ Everyone in healthcare appreciates the need to shift from reactive to preventative care, especially for patients with chronic disease. However, our clinical workforce is already stretched and systems are under financial pressure. We need technology to enable this transition.
6/ We're thrilled to lead Cadence's $100M Series C and scale this world-class care to the rest of America's chronic care patients. AI is our best chance to finally bend the cost curve, and there's no better team to bring it to market than this one. Join them!
5/ As we've seen in investments like Abridge, when AI is built and deployed responsibly, in partnership with health systems, with a deep focus on clinical and financial outcomes, the results can dwarf what was possible in the pre-LLM era.
4/ Cadence already serves more than 100K patients + saves Medicare ~$3M per week. It's clear this should scale to Ms of patients, quickly. And, as model capabilities improve, so will the impact Cadence can have. It's one of the most compelling "Applied AI" pitches we've heard.
1/ Everyone in healthcare appreciates the need to shift from reactive to preventative care, especially for patients with chronic disease. However, our clinical workforce is already stretched and systems are under financial pressure. We need technology to enable this transition.
Today, Cadence is announcing our $100M Series C, led by @SparkCapital, with participation from @ThriveCapital, @generalcatalyst, @coatuemgmt, @BCapitalGroup, Corewell Health Ventures, Memorial Hermann, and Duke Health.
Together with the leading health systems in the US, we are automating the treatment of chronic disease, delivering better outcomes to 100,000+ patients.
Our clinical AI monitors patients daily, surfaces risk early, coordinates action, and extends clinicians so they can focus on the decisions that require them. The results:
- 27% fewer hospital admissions
- $1,302 annual cost reduction per patient
- $2.7M in Medicare savings every week
- 70% relative improvement in blood pressure control
- Median alert response time of 3.5 minutes
AI is improving clinical care. This round is about scaling world-class care from 100,000 patients to millions.
I’m deeply grateful to our patients, partners, investors, and every member of the Cadence team.
We’re building the standard for how chronic disease gets treated in America.
3/ The results speak for themselves: 27% fewer hospital admissions, $1,302 annual cost reduction per patient, 70% relative improvement in blood pressure control. They've published peer-reviewed data that speaks to the efficacy of this solution:
https://t.co/29fvWfjtwz
A GPU sitting idle is expensive.
Too many AI deployments focus on compute and networking, then get delayed by transformer lead times, power constraints, or cooling limitations.
Building GPU infrastructure starts long before a chip is installed.
Our latest blog explores the core components of GPU infrastructure and what teams should consider when designing AI-ready sites:
https://t.co/aIXMl8lCPT
Today, Cadence is announcing our $100M Series C, led by @SparkCapital, with participation from @ThriveCapital, @generalcatalyst, @coatuemgmt, @BCapitalGroup, Corewell Health Ventures, Memorial Hermann, and Duke Health.
Together with the leading health systems in the US, we are automating the treatment of chronic disease, delivering better outcomes to 100,000+ patients.
Our clinical AI monitors patients daily, surfaces risk early, coordinates action, and extends clinicians so they can focus on the decisions that require them. The results:
- 27% fewer hospital admissions
- $1,302 annual cost reduction per patient
- $2.7M in Medicare savings every week
- 70% relative improvement in blood pressure control
- Median alert response time of 3.5 minutes
AI is improving clinical care. This round is about scaling world-class care from 100,000 patients to millions.
I’m deeply grateful to our patients, partners, investors, and every member of the Cadence team.
We’re building the standard for how chronic disease gets treated in America.
Took Mercury's new Command feature out for a test spin with approximately the scariest thing you can do in a bank account, asking for a wire out, and it worked on the first try.
Nice UX on upgrading from chatting-with-an-LLM interface to embedded this-is-fully-engineered flow.
.@Baseten is building the Inference Cloud, and has raised another $1.5B to invest aggressively in their capacity, infrastructure platform and research products.
Today, they serve the leading AI-native companies who want to own and improve their intelligence. These frontier customers need special-forces support and frontier scale. Baseten wins by helping these demanding, sophisticated customers do more than they could on their own, in their unique domains — embedding engineering and research capabilities, offering a truly elastic cloud, and providing tools for full-stack and complete-loop optimization.
Everything we see at @Conviction suggests we remain <1% into the wide and explosive demand for inference, and the world is still beginning to imagine the ways and volume at which we will use computational intelligence.
We are continuing to invest in the cracked, principled and maximally ambitious team at Baseten. We’ve been believers since day one — but the scale of the problem and the opportunity means it still feels like day one to us.
The GLM moment is going to be bigger than the DeepSeek moment.
Baseten has the fastest inference on the best open-weight model. >280 tps and <0.8 ttft.
We closed our Series F today at a $13B valuation.
Our inference business grew 20x in the last year. I want to explain why:
The growth comes from a shift I think is permanent: companies want to own their intelligence layer. Instead of relying exclusively on closed models, teams are post-training open models for their specific use cases. Customers like Abridge, Cursor, Decagon, Harvey, HubSpot, Lovable, Notion, OpenEvidence, and Parallel are building this way.
But post-training is still more of an art than a science. That’s why we’ve been working hands-on with customers to build specialized models that match or exceed closed models on the tasks they care about. We provide not just the weights, but also the training recipes and tooling so that they're in charge of the continual learning process.
I think more companies, both AI-natives and enterprises, will own their intelligence layer. And I’m excited to help build that future.
One (maybe the only?) thing that seems certain over the next few years is that inference is going to grow like crazy. And a huge amount of that growth is going to be powered by @baseten. Congrats @tuhinone and team!
We’re excited to announce our $1.5B Series F.
Baseten exists to help companies own their intelligence and run AI products in production with speed, reliability, and control. As we enter this next chapter, three things are clear:
1. Customers like Abridge, Clay, Cursor, Decagon, HubSpot, Lovable, Notion, and OpenEvidence are proving that AI can create transformational value across industries and workflows. They have built products where intelligence is core to the customer experience and central to the value they deliver.
2. Open models - like GLM 5.2 - are now exceptionally strong, and the quality gap with leading closed models is smaller than ever. We’re seeing more companies turn to open and specialized models for better economics, performance, and ownership over their stack. Baseten provides the fast, reliable inference layer to run those models in production across every modality.
3. Post-training is giving companies a path to turn their own data, evals, feedback, and judgment into durable technical advantage. The most sophisticated teams are already using RL and domain-specific optimization to outperform closed models on important tasks and workflows. This will become a defining capability for every company building at the application layer.
We're excited to accelerate progress to this future of owned intelligence.
Thank you to our customers for your trust and partnership. We’re grateful to be building this future with you!