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Nova AI began with the goal to push the boundaries of AI-driven coding automation. Back in early-2024, Nova AI was developing general coding agents, designed to automate software development tasks. By June 2024, our general coding agent's score on SWE-bench, the most popular general AI coding benchmark, surpassed all known scores at that time, including from Amazon & IBM.
Emma Qian, co-founder of Nova AI, spent her career at Google DeepMind, applying AI to solve complex mathematical problems. She realized that AI was generating significant hype but often failed to deliver meaningful impact in large-scale, real-world business applications. General coding agents are helpful for small or simple software engineering tasks, but fail at large scale real world engineering projects.
The missing ingredient? AI needed to move beyond broad, general models to domain-specific AI agents built for industry-specific challenges.
Alongside Sam Yang, the early Nova AI team identified a critical gap in enterprise modernization: SAP migration remained slow, manual, and reliant on consultants. Alexander Zeier, the co-inventor of SAP HANA, had seen these inefficiencies firsthand. Having worked closely with Hasso Plattner on HANA, he understood the complexities of SAP transformations and recognized AI agents as the missing automation layer.
Initially, Emma had never considered working with SAP. But as she dug deeper, she saw its immense potential. SAP was the backbone of Fortune 500 enterprises—one of the most mission-critical systems in the corporate world—yet still burdened by outdated, manual workflows.
A shared connection in enterprise AI, Paul Daugherty, introduced Emma and Alexander, and they immediately recognized an opportunity. By combining cutting-edge AI with decades of SAP domain intelligence encoded into their system, they could build AI-native automation to analyze, optimize, and modernize SAP systems end-to-end—solving a challenge that no existing AI solution had addressed.
SAP’s structured logic made it particularly suited for AI-driven automation. With enterprises facing an urgent migration wave, the timing was perfect to bring intelligent automation to one of the most foundational systems in global business.