Artificial intelligence application development startup Kore.ai Inc. has announced the launch of a new platform called “GALE,” which makes it simple to create versatile generative AI apps using a simple, no-code, drag-and-drop interface.

Users can choose from a library of more than 30 large language models, the company said. Kore.ai is best known for its Experience Optimization or XO platform, which is used by enterprises to quickly build customized generative AI chatbots. Through its no-code user interface, unskilled workers can quickly create simple AI applications such as chatbots, product recommendation systems and virtual assistants in a safe and cost-effective way.

GALE, which stands for Generative AI and LLM Platform for Enterprises, represents the next evolution of Kore.ai’s generative AI development tools, enabling businesses to create powerful AI agents that can perform tasks on behalf of their users and be deployed and scaled rapidly, the company said. One of the key differences is the level of experimentation GALE provides. With its no-code UI and intuitive visual interface, users can test a variety of LLMs and prompts in order to work out which combinations are best for the application they have in mind.

Kore.ai founder and Chief Executive Raj Koneru said GALE is especially suited for organizations that don’t have AI specialists on their teams to create AI agents that can vastly improve the productivity of various teams. In addition, it will be useful for those organizations that struggle to find the best use cases to enhance their productivity with AI.

“GALE addresses the fragmentation and limitations within the current ecosystem,” he said. “It’s a cohesive platform integrating core AI app-building functionalities with built-in guardrails.”

“None of the hyperscalers or other gen AI app providers offer customers an end-to-end capability to experiment with a range of large or small language models to develop, deploy and manage sophisticated gen AI apps,” he added. “But GALE does.”

The GALE platform is made up of several components, including its no-code flow-builder and drag-and-drop interface, which enables users to quickly piece together various workflows, applications and AI agents. Meanwhile, the Model Hub is a library that provides access to more than 30 different LLMs, including proprietary, open-source and fine-tuned models, as well as tools for refining those models further for specific business tasks. It also has a Prompt Studio, which is a kind of playground for users to experiment with different prompts and see how their generative AI applications respond.

Users can also take advantage of various templates and out-of-the-box integrations with common business applications to automate various aspects of their business operations, including common tasks such as data entry, analysis, reporting and drafting texts.

Constellation Research Inc.’s vice president and principal analyst Andy Thurai told SiliconANGLE that Kore.ai’s GALE is an interesting and timely offering, with AI agents being all the rage nowadays.

“Enterprises are moving from the experimentation to the adoption phase of GenAI. Creating LLMs or SLMs with speed, testing, validating, deploying and tracking them are all very complicated processes now,” he said. “Especially given that agent-based AI architecture is all the rage now, enterprises are looking for platforms that offer these capacities that can be done with low code capabilities.”

“Almost all of the top hyperscalers, as well as the platform players such as IBM and Oracle, etc., are starting to offer these functions in varying degrees,” Thurai continued. “Getting customer adoption and traction might be the biggest challenge for Kore.ai, as it’s going up against all of the big guys.”

Despite this competition, Kore.ai said it has already made considerable progress. It launched GALE in beta earlier this year with more than 100 customers in industries spanning banking, healthcare, insurance and retail. They’ve used GALE to create all kinds of intelligent applications, the startup said. Examples include AI agents that can aid in research and market intelligence, manage knowledge bases, surface insights from data, and automate business workflows such as claims processing, customer order processing, inventory management and invoice generation.

Everest Group analyst Vaibhav Bansal said GALE provides everything an enterprise needs to experiment, build, deploy and scale AI agents and applications, in a single platform. As such, he believes it has the potential to become a kind of “one-stop shop” for all enterprise AI needs.

“Enterprises need an easy way to experiment,” he said. “Typical features [that enterprises need] include an AI/ML orchestration layer for efficient model management, the ability to seamlessly connect with enterprise data, a low-code interface, and an application development layer for deploying AI agents or apps.”

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