New features leveraging AI and LLMs establish Panoply as the easiest end-to-end analytics platform for SMEs to obtain critical business insights without complicated code

SQream, the scalable data analytics company built for massive data stores and AI/ML workloads, announced today that its low-code ELT and analytics platform Panoply, is launching an AI Flex Connector helper which leverages generative AI to streamline the path to business intelligence. This tool will make it even easier for users to collect all of their business data – from CRMs, user applications, and other tools – into one single source, and further minimize the technical requirements to generate quick data insights.

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While there are multiple ingestion tools already on the market, these tools are often limited in terms of which data sources can connect with them. Released in April 2023, Panoply’s Flex Connector has enabled greater platform flexibility by supporting connections to any RestAPI or GraphQL data source. The Flex Connector currently requires users or the Panoply Customer Success team to sift through multiple API documents to find the configuration that meets their needs, but the new Flex Connector AI helper takes these capabilities to the next level by removing this manual process and instead relying on generative AI to complete the required research. This will enable users to skip the majority of the steps previously required and provide a working configuration that analysts will then customize with minimal information (authentication details, domain names, dates etc.).

“We’re excited about the future of AI in data and how it can make data in general even simpler to use and more accessible for non-technical users,” said Ittai Bareket, GM of SQream Americas and Panoply. “With our upcoming AI focused product enhancements, we’re looking to automate and outsource the more technical and time consuming aspects of gaining insights from your data.”

The new feature is prompted by Open AI LLM models, which are deployed on Microsoft Azure and enable applications built on top of the LangChain framework, allowing users to switch between models in the future. The user provides two parameters to prompt the tool to scan the web for the most up-to-date API documentation of the selected service, and within it all the requirements needed to extract the selected resource.

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