Data integrations are the superpower of AWS and Snowflake’s partnership

Data integrations are emerging as the critical link between generative artificial intelligence experimentation and real-world deployment, according to Amazon Web Services Inc. and Snowflake Inc.

The two companies have joined forces to help customers move from proof-of-concept to production. Their next focus: unlocking the power of agentic AI and automation.

Mona Chadha of AWS discusses Amazon’s partnership with Snowflake.

“We’ve seen that with generative AI, everyone’s using some component of it, whether it’s with a large language model … or creating these chatbots across different use cases,” said Mona Chadha (pictured), director of category management at AWS. “What we found is that now they’re moving away, a lot of those customers that were trying these experiments are now implementing more production.”

Chadha spoke with theCUBE’s Rebecca Knight and Dave Vellante at Snowflake Summit, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed the collaboration between Snowflake and AWS, as well as the future of automation. (* Disclosure below.)

Jointly spearheading data integrations

Although Snowflake and AWS have, at times, had overlapping capabilities, their partnership has only flourished in recent years, according to Chadha. Snowflake now has 50 different integrations across a variety of different AWS services, including SageMaker, Bedrock and Amazon Q.

“We came together really trying to solve customers foundational data challenges,” Chadha explained. “What we looked at was the integrations and having those integrations with a variety of AWS services that help augment your Snowflake experience, and specifically data, and so what we are trying to do … with Snowflake is really collaborating on augmenting generative AI.”

Snowflake and AWS’ partnership also spans across multiple independent vendors and integrators, offering customers maximum choice in what models and types of software they choose to implement. For companies looking to get a return on investment for their gen AI projects, Chadha has some advice.

“You need to be more thoughtful about what your data strategy is,” she said. “Integrate it, don’t just use data from one source. You need to also supplement that data from multiple resources to, again, ensure that veracity of that data. Then you’ve got to be responsible. You’ve got to make sure that you’re doing the right thing for your end customer.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of Snowflake Summit:

(* Disclosure: TheCUBE is a paid media partner for Snowflake Summit. Neither Snowflake Inc., the primary sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE