Custom Software Development, Web App Development, Software Architecture, QA, Data Infrastructure, ETL
Amazon Web Services
Python, Javascript
MariaDB
React, AWS Lambda, Serverless,
AWS Chalice, AWS Step functions,
AWS Bedrock
SellerCentral, Rainforest,
Netsuite, Claude, & more
Netlify
Atomic is an e-commerce company that operates Amazon storefronts, each requiring specialized operational functions. Atomic’s idea was to build an AI-driven platform that could centralize and streamline all operational processes. Instead of relying on a fragmented system, Atomic set out to create an environment where AI agents act as integral team members, helping Atomic scale efficiently while making the most of its existing resources.
Amazon sellers constantly strive to grow their revenue, reduce costs, and operate more efficiently. But as they expand, operations become increasingly complex and time-consuming. Every new store adds layers of work; inventory, forecasting, customer service. Hiring a full team to manage it all is expensive, yet running without one limits growth. Therefore there was a clear need for a scalable, affordable way to handle these tasks– one that can perform specialized functions, learn over time, and operate at a fraction of the cost of human staff.
Atomic is an e-commerce company that operates Amazon storefronts, each requiring specialized operational functions. Boaz Saragossi, Head of R&D, envisioned a smarter way to manage this complexity. His idea was to build an AI-driven platform that could centralize and streamline all operational processes. Instead of relying on a fragmented system, Boaz set out to create an environment where AI agents act as integral team members, helping Atomic scale efficiently while making the most of its existing resources.
Amazon sellers constantly strive to grow their revenue, reduce costs, and operate more efficiently. But as they expand, operations become increasingly complex and time-consuming. Every new store adds layers of work; inventory, forecasting, customer service. Hiring a full team to manage it all is expensive, yet running without one limits growth. Therefore there was a clear need for a scalable, affordable way to handle these tasks– one that can perform specialized functions, learn over time, and operate at a fraction of the cost of human staff.
Beehive developed a centralized dashboard that connects with dozens of data sources, giving Atomic full visibility and control over 8 Amazon storefronts and thousands of products from a single platform. The system includes built-in AI agents designed to optimize store operations– handling tasks such as competitive analysis, demand forecasting, and performance monitoring. With automation at its core, the platform transforms what was once a fragmented and manual process into a unified, intelligent workflow.
Beehive developed a centralized dashboard that connects with dozens of data sources, giving Boaz full visibility and control over 8 Amazon storefronts and thousands of products from a single platform. The system includes built-in AI agents designed to optimize store operations– handling tasks such as competitive analysis, demand forecasting, and performance monitoring. With automation at its core, the platform transforms what was once a fragmented and manual process into a unified, intelligent workflow.
After more than 20 integrations, tasks that once required hours of manual effort are now handled by AI agents, eliminating much of the inefficiency that typically comes with operating at scale on Amazon. Atomic is experiencing significant ROI while gaining tighter control and faster execution across every store.
integrations / data sources
Therapists use the product to upload sessions
Atomic sees an opportunity to bring this innovation to the broader Amazon seller community. Currently, there are no tools that truly enable intelligent management of Amazon storefronts. With the success of their own platform, the Atomic team plans to commercialize the product, offering other sellers the same ability to streamline operations, reduce manual work, and scale more efficiently through AI-powered automation.
and lets us scale up and down our development resources as needed.”
Head of R&D
