Design the enterprise platform from the ground up as a modular system harnessing the power of Machine Learning and other advanced technologies to eliminate silos and ensure a seamless user experience.
Founded in 2018 within the ING Bank APAC Innovation Lab incubator, Stemly is a pioneering data science platform. Its array of cutting-edge products enables companies to refine strategies and optimize both costs and resources through the application of Machine Learning and other sophisticated technologies. Stemly has garnered notable accolades, including recognition as one of Tech in Asia’s “50 rising startups in Singapore” in July 2021 and inclusion in Forbes Asia’s “100 To Watch 2023” in August 2023.
The initial stages of our development focused on mastering complex demand planning and forecasting methodologies, thorough research, and competitive analysis. At that time, the market was dominated by a few major players reliant on outdated Windows-based and traditional web applications, characterized by cumbersome onboarding processes that required significant customer success efforts. Our ambition was to revolutionize this scenario by introducing a next-generation user experience reminiscent of consumer apps.
Our foremost objective was to validate our product with a select cohort of enterprise clients, continually refining the user experience. The team’s unyielding commitment aimed at establishing Stemly as an independent entity, separate from ING Bank’s APAC innovation labs. This commitment to enhancing both our brand and our offerings was crucial. Our efforts culminated successfully with a significant funding round in June 2021, raising $2.5 million USD from prestigious investors including EDB New Ventures, ING Ventures, Elev8.VC, HH VC Investments, and FutureLabs.
Enterprise-level supply chain platforms are significantly outdated, lacking the modern features and flexibility required to meet today’s rapidly changing business environments and technological advancements.
Decision-making platforms, historically dominated by established entities such as SAP, Oracle, and o9, have long provided demand planning and forecasting services. Despite their pedigree, these platforms frequently present complexities that can stifle innovation.
Stemly seized a clear opportunity: to offer a modern SaaS platform that not only ensures an outstanding user experience but also maintains high predictive accuracy—a specific requirement voiced by customers.
The aim is to develop an advanced enterprise-grade SaaS platform for forecasting and optimization, aiming to establish new benchmarks in user-friendliness and speed, while also achieving unparalleled accuracy in prediction.
Each team member had a different concept of how the platform should be organized, and there was frequent confusion over terminology. To address this misalignment promptly from a design standpoint, the design team created a term dictionary to establish clear definitions for industry-specific terminology, which is crucial in data science platforms.
We then outlined the platform’s structure by benchmarking against top-tier SaaS platforms and adapting those insights to our needs. The framework of organizations, workspaces, and modules proved most effective for us.