Nova Intelligence Raises $31.5M Series A to Revolutionize SAP AI Migration by 2030
- Nova Intelligence has raised $31.5 million in a Series A funding round led by Chemistry, bringing the company's total funding to more than $40 million.
- The funding comes as enterprises face a significant transition period for their core business operations.
- A primary driver for Nova Intelligence's technology is the upcoming 2030 migration deadline.
Nova Intelligence has raised $31.5 million in a Series A funding round led by Chemistry, bringing the company’s total funding to more than $40 million. The startup is developing agentic AI designed to integrate with SAP systems, targeting the complex technical challenges associated with legacy enterprise software.
The funding comes as enterprises face a significant transition period for their core business operations. An estimated 77 percent of the world’s transactions touch an SAP system at some point, making the software a critical component of global commerce and supply chain management.
A primary driver for Nova Intelligence’s technology is the upcoming 2030 migration deadline. Many organizations are currently operating on legacy SAP code that is decades old, creating technical debt and operational rigidity that complicates the move to more modern cloud-based architectures.
Addressing Legacy Enterprise Code
The prevalence of aging code within SAP environments presents a substantial barrier to digital transformation. Because these systems often handle the most sensitive and critical financial and operational data, upgrading them carries significant risk of business disruption.
Nova Intelligence is utilizing agentic AI to bridge this gap. Unlike traditional generative AI, which primarily focuses on content creation or information retrieval, agentic AI is designed to act as an autonomous agent capable of executing complex workflows and taking direct action within a software environment to achieve a specific goal.
In the context of SAP, this technology aims to automate the analysis and migration of outdated code, reducing the manual effort required by developers and consultants to move legacy systems toward the 2030 migration target.
By automating the intersection between legacy business logic and modern AI capabilities, the company intends to streamline how the world’s largest organizations manage their transactional data and underlying software infrastructure.