Enterprises are seeking to bring secure, scalable generative AI platforms to market faster, and this is leading major tech players such as Amazon Web Services Inc. to form new partnerships in the quest for choice, flexibility and value from autonomous technology.
Karini AI’s Nitin Wagh talks with theCUBE about scalable generative AI during the AI Cloud Leaders Summit.
An example of this can be found in the collaboration announced this week between AWS and Karini AI LLC, a provider of production grade generative AI software for enterprises. The agreement is designed to facilitate gen AI implementation across multiple enterprise segments.
“What we do is provide a no-code/low-code platform abstraction on top of the AWS infrastructure,” said Nitin Wagh (pictured), co-founder and chief executive officer of Karini. “It’s not just IT, but also line of business IT, business experts who can build, operate and manage generative AI. A lot of our customers are from marketing departments. I’m talking to lawyers. I’m talking to HR experts. We are talking to more domain experts, and they are quite essential for successful generative AI projects.”
Wagh spoke with theCUBE’s John Furrier at the theCUBE + NYSE Wired: AI + Cloud Leaders Media Week event, during an exclusive broadcast on theCUBE, News Media’s livestreaming studio. They discussed how Karini uses AWS tools to help enterprises with AI deployment.
Deploying Bedrock for scalable generative AI
Karini’s work with AWS leverages numerous tools and services from the major cloud provider. The Karini platform is deployed within a customer’s Amazon Virtual Private Cloud and users can orchestrate agentic workflows using tools such as Amazon Bedrock to build and scale generative AI applications.
“We typically start with Bedrock, you select a problem, write a prompt, write an agent,” Wagh said. “The tool ecosystem is very important; I don’t want an LLM to do knowledge graph, query execution. That is better done in Amazon Neptune. You always have outlier edge cases, and that’s when we definitely talk about fine-tuning the model. That’s where we have built the abstraction on top of [Amazon] SageMaker.”
Enterprise edge use cases are beginning to grow as Karini has deployed its generative AI solutions. The deployment of AI agents is having an impact on a multitude of businesses, according to Wagh.
“All of our projects are about business productivity transformation, and they’re mostly about business process automation,” he said. “There are some of the use cases we are doing at Swagelok Southeast Texas, which is a huge fluid parts manufacturer for oil and gas, aerospace. We are doing order-to-cash, ERP exception. Customers said it saved them a million dollars just with that multi-agentic workflow.”
The use of agents on Karini’s platform plays an important role in the company’s deployment of business solutions. In November, Karini launched Agent 2.0, which aligned the needs of complex production environments with precise task management.
“Our value proposition is very simple: You deploy Karini AI which comes with … all the quintessential elements that make up the agentic platform,” Wagh said. “Our model is we deploy in a customer’s AWS account, in their VPC, so it can be air-gapped and then we enable their business users to build their own private AI.”
Here’s the complete video interview, part of News’s and theCUBE’s coverage of theCUBE + NYSE Wired: AI + Cloud Leaders Media Week event:
Photo: News
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