Matt Hammond’s Post

How did State Street boost employee productivity 25x, cut labor costs 50% and accelerate success with AI? Snowflake. “We've pivoted our Snowflake-powered data platform into an AI platform that helps clients make investment decisions that are led by both data and AI.” — Aman T., CTO Snowflake makes it easy to execute your data strategy and fast-track your AI strategy. We eliminate silos, creating data gravity that pulls teams and use cases together. We eliminate work, thanks to our fully-managed service and powerful automations. We eliminate risk, with universal governance that applies your policies consistently. From there, use AI in seconds. Snowflake Cortex AI for fully-managed LLMs that require no setup or ongoing maintenance. Snowflake ML functions for impact use cases OTTB, like forecasting and anomaly detection. MLOps without the ops burden. GenAI applications with fully-managed GPUs. Superior total cost (TCO). That’s Snowflake. Learn more about the outstanding team at State Street and their journey to success with AI:

AI features are great. But can they scale? Snowflake’s can -- with unmatched power, ease-of-use and cost-efficiency across use cases. It starts with our revolutionary architecture: optimized storage and elastic multi-cluster compute. Store any data, structured, unstructured and semi structured — at any volume and velocity. Run any workload, from self-service analytics to simplified MLOps and GenAI apps. The same engine that put Snowflake on the map for data warehousing runs SQL, Python, Java and Scala — and outperforms Spark and managed Spark. For compute-intensive workloads, simply use Snowpark Container Services for fully-managed GPUs. Snowflake Cortex AI is baked into our architecture, giving you fully-managed LLMs from Snowflake, Mistral AI, Meta and others with superior cost-efficiency. No fragmented toolset to stitch together. No scrambling to make legacy tech open and efficient. No bloated R&D budget that passes that cost onto customers. Just Snowflake. Learn more in this outstanding webinar on July 30, on how to build AI assistants and chatbots with Snowflake Cortex AI, for easy, efficient and trusted AI at any scale:

Why GenAI? Unprecedented productivity. Sounds a lot like Snowflake. Snowflake eliminates the need to manage your infrastructure, platform, storage and compute — activating your teams to activate your data. That impacts every workload. With Snowflake, “it just works” — from simple data sharing and data warehousing to innovative AI and ML. No more wasteful compute, storage and labor cost. Instead, elevated teams and skillsets. That’s Snowflake. Learn more about Snowflake Cortex AI, our serverless suite of LLMs and no-code AI development, in this outstanding hands-on workshop in July.

“Snowflake is expensive.” How? Snowflake compute is the most efficient in the industry. (That’s what put us on the map for data warehousing). That same engine also runs data engineering and AI workloads — in SQL, Python, Java and Scala. We outperform Spark and managed Spark across workloads. (It’s not close). - 4.6x faster runtimes - 34% reduced cost - 50% less ops burden Snowflake’s fully-managed service also handles provisioning, scaling and suspending our compute. Meaning: less wasteful spend. Same goes for GPUs, for compute-intensive workloads. (See: Snowpark container services). We could do this all day. Snowflake even saves customers money just from ongoing performance enhancements. We measure how much faster and cheaper we’re running, with the Snowflake Performance Index. How much faster? 27% since August 2022. Meaning: Snowflake customers get an additional 13% in savings every year on average. If you’re hearing that Snowflake is expensive, it might make sense to consider the source. If you talk to Snowflake customers, they’ll tell you a different story. Just ask IGS Energy, who saved 75% for AI and ML by leaving Databricks for Snowflake.

Chatted with a CIO who thought his organization was “about a year away from being ready for AI.” Doesn’t have to be that way. Snowflake makes it easy for you to get to the cloud, create a single governance and security layer and activate your teams to activate your data. Snowflake Cortex AI, for ready-to-use LLMs and ML functions for citizen data science. Snowpark ML, for MLOps without the ops burden. Snowpark container services, for compute-intensive GenAI with fully-managed GPUs. What you don’t need to waste your energy on with Snowflake: infrastructure, platform, compute and storage maintenance. “It just works.” Check out this developer guide on how to create enterprise Call Center Analytics in Snowflake using OpenAI Whisper, Snowflake Cortex LLMs, Snowpark container services and Streamlit. Takes only 35 minutes.

“It just works”