Profluent Adds 106 Million in Financing Led by Altimeter and Bezos Expeditions
Profluent is building on its claim that scaling laws, the principle that model performance improves predictably with more data and compute apply to protein design.
Deployed's enterprise AI reporting on llm.
Profluent is building on its claim that scaling laws, the principle that model performance improves predictably with more data and compute apply to protein design.
AirOps frames its mission in direct terms: to help teams become “first to know and first to grow.”
With $50M Series A funding, WisdomAI is transforming how enterprises analyze structured and unstructured data with AI.
Video has always been the toughest format for AI which is messy, dense, and hard to index.
Zendesk's 2025 AI Suite launch introduces autonomous agents and human-centric tools that streamline customer support for nearly 20,000 users.
Our goal with Tinker is to give researchers and developers the ability to experiment without worrying about the infrastructure. They can explore model behaviors, test hypotheses, and refine data efficiently.
OpenAI and Anthropic exposed vulnerabilities in each other’s models while governments move to build independent evaluators
The simple way to think about it is that we’re bringing the power of LLMs to group chats
We suspected it was going to be big, but we had no idea it would be this big.
Nobody comes to us and says, we want to build a new ERP.’ But this is one of the largest categories in software. And no one was disrupting it.
We see a real opportunity to step on the gas and be as aggressive as possible.
Adobe’s enterprise/subscription first approach has been alienating solo creatives
Just days after launching Clark, its AI-native platform for internal app development, the company was announced as the lead partner for Databricks Apps at the 2025 Data + AI Summit.
We’re building the part that makes real-time intelligence actually work.
Now we get to scale that with the metadata foundation that enterprise workflows demand.
It’s not about reinventing work—it’s about making it more intelligent and more efficient.
AI is always wrong for one of two reasons. Either the model is wrong or the question is unclear. We address both.
There's just so many facets of our business that are touched by AI, and it still feels like we're in the early innings here.
A lot of folks went out and bought GPU capacity or model licenses without thinking about where that’s going to create value.
Machine learning models are only as good as the data they learn from.