Iterate.ai Powers the Low-Code Success Behind Pampered Chef’s New Table Platform

Table, a first-of-its-kind interactive digital platform for virtual cooking parties, used Iterate.ai’s Interplay® low-code solution to continuously develop and rapidly deploy iterative improvements

Iterate.ai, whose innovation ecosystem enables customers to build production-ready low-code applications up to 17x faster than traditional programming, today announced that Pampered Chef has successfully developed and deployed its pioneering Table virtual party experience for micro-communities by using Interplay, Iterate.ai’s AI-powered low-code platform.

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A leader in the direct selling industry, Pampered Chef launched Table to enable its consultants to host virtual cooking parties and deliver unique customizable content tailored to improve consumers’ mealtime journeys. With Table, consultants can build micro-communities and engage with consumers by combining pre-programmed modular content tools with new content to create unique and authentic social experiences. Table features an immersive virtual kitchen experience where consumers can learn about cooking products and recipes. Consultants can also share images, videos, product catalogues, recipes, interactive games, and quizzes through a customizable content feed. Consumers have their own options for personalizing the Table content they see based on their interests.

Developed and deployed using Iterate.ai’s Interplay low-code platform, Table advanced from a proof-of-concept to a minimum viable prototype in just six months, and then to a full-scale platform six months later. Interplay provides a comprehensive drag-and-drop low-code environment for rapid application development, iteration and large-scale deployment. The platform features 475 pre-built modules that enable organizations to rapidly leverage AI/ML, IoT, blockchain, data, and API capabilities. Interplay’s architecture and interface empower both experienced coders and non-coders to easily and intuitively connect modules, and build and test complete applications quickly and safely. Interplay regularly enables application development at a pace 17x faster than teams relying on standard code-writing development models.

Launched in September 2021, Table hosted 100,000 guests and consultants within 5,000 micro-communities in just its first few weeks. Throughout Table’s development, Pampered Chef’s team actively listened to and crowdsourced iterative improvements suggested by consultants running micro-communities on the platform. Using Interplay as a low-code strategy allowed for this highly scalable approach to development consisting of 180+ web APIs and 17 third-party integrations, making it possible to build and deploy features based on modular components, rapidly test them with real consultants and consumers, and proceed in improving and scaling the Table experience in a data-driven manner.

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Quotes

“The pace at which we were able to develop the Table platform was incredible, and I attribute that to our low-code strategy enabled by Iterate.ai and Interplay,” said Shiv Dutt, Vice President of Experience Innovation at Pampered Chef. “With low-code, we can swiftly build out iterations of our solutions, put them to the test, iterate on what works and switch out what doesn’t. This approach empowers us to treat our consultants as product managers, incorporating their feedback to quickly deliver the features they demand. Our customer-centric approach to product development combined with the Interplay platform will enable us to continue to test, learn and improve the platform with speed.”

“Pampered Chef’s Table platform demonstrates the incredible pace with which organizations can develop and go to market with innovative solutions by employing a low-code strategy,” said Brian Sathianathan, Chief Technology Officer/Co-Founder at Iterate.ai. “Businesses that leverage low-code correctly can simply run circles around competitors when it comes to testing new features and responding to customers’ needs. We’re proud of what Pampered Chef has accomplished with Table in such a short time, and anticipate further impressive achievements as the platform continues to scale and iterate.”

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