Snowflake and SAP Partner to Unify Enterprise Data for AI at Scale
There’s a lot of enthusiasm in the market, but we stay focused on what AI can actually do for customers.
Deployed's enterprise AI reporting on snowflake.
There’s a lot of enthusiasm in the market, but we stay focused on what AI can actually do for customers.
NVIDIA, AMD, Snowflake, and Databricks are backing Uniphore to control the connective tissue that ties enterprise AI systems together
Transforming sales intelligence by turning fragmented data into actionable AI-driven insights.
By aligning with Snowflake, Palantir is extending its reach into enterprises that are already invested heavily in Snowflake’s cloud ecosystem.
“Our agents run inside the customer’s environment, giving them full control and oversight of the AI processes in real-time”
It’s not only about analytics anymore. Customers want a single platform that can handle data, models, and applications in one place.
Those folks don’t know what the hell they’re talking about.
Databricks’ is on an M&A spree as Snowflake relies on its own engineering bench
The raise comes just eight months after Databricks closed its $62 billion Series J.
Snowflake Intelligence tackles the decision-making bottleneck head-on
"When it comes to pulling data, that’s where we want to be the best.”
Snowflake just announced a slew of new agentic AI innovations.
Snowflake announced its intent to acquire Crunchy Data for approximately $250 million.
We’re building the part that makes real-time intelligence actually work.
We are being sold on the idea of running before we can walk or crawl.
Every employee should be able to ask a question and get an answer—no technical skills required, no time lost waiting.
At the end of the day, your AI is only as powerful as the data it can access.
If ClickHouse closes its next round at the targeted valuation, it will be one of the few private software firms to see a step-up since the peak of the 2021 market.
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.