Dodge AI raises USD $2.65 million for enterprise maintenance

Dodge AI has raised USD $2.65 million from Accel and Google to support its work on software maintenance for large enterprise systems.

The round also included New Build Venture Capital, Antler, Schema Ventures, and angel investors from the SAP ecosystem. Dodge AI focuses on maintaining enterprise applications after deployment, particularly systems such as SAP, Salesforce, Oracle, Microsoft Dynamics, Kinaxis, and Oracle JDE.

Large companies often make thousands of internal changes to enterprise software over time, creating layers of custom rules, workarounds, and undocumented processes. When systems fail or processes break, those companies can face lengthy investigations across support tickets, configuration records, and knowledge held by staff or outside consultants.

Dodge AI is building a platform that works across these systems to identify the cause of incidents, recommend fixes, and record the logic behind individual changes. It describes this as a way to create a clearer record of how business-critical systems operate in practice.

Maintenance market

The company is targeting a longstanding part of the enterprise technology market that has typically relied on large support teams and external service providers. Businesses spend more than USD $600 billion a year keeping enterprise applications running, much of it tied to incident management, change requests, and routine operational support, according to Dodge AI.

That model often leaves companies dependent on service partners because practical knowledge about how systems work becomes scattered across consultants, ticket histories, and institutional memory rather than being captured in one place. As customisations build up over time, so does technical debt.

"For a long time, the only way to maintain enterprise systems was to add more people," said Rebhav Bharadwaj, Co-Founder and Chief Executive Officer of Dodge AI.

"We believe long-horizon agents can change that. Dodge AI gives enterprises the ability to continuously improve and heal their mission-critical systems so incidents can be resolved faster, technical debt can be understood, and the knowledge trapped inside maintenance work can become the foundation for future transformation," Bharadwaj said.

How it works

Dodge AI says its platform sits across business processes, ERP customisations, IT service management systems, and older configurations. The aim is to trace how a problem moves through multiple systems and surface the rules or exceptions that have shaped a company's setup over the years.

According to the company, that is especially important in enterprise software because many of the most important operating decisions are not contained in standard software documentation. Instead, they are embedded in local exceptions, process-specific overrides, and bespoke workflows created for individual warehouses, pricing rules, or planning cycles.

"Frontier models are incredibly capable, but enterprise adoption still requires significant hill climbing. Dodge AI captures the necessary rules and exceptions for this while self-healing your systems instead of requiring an endless transformation project," said Aditya Thakur, Co-Founder and Chief Technology Officer of Dodge AI.

Early customers

Dodge AI is already working with more than a dozen enterprise customers, half of them publicly listed companies. Its system handles hundreds of queries each hour across customer environments, giving it a growing view of recurring failures and maintenance patterns.

One example involved a warehouse where a truck could not be loaded because a Goods Receipt Note was printing incorrect information. Dodge AI said it traced the issue across SAP, Kinaxis, and internal warehouse software before delivering a fix within minutes.

In another case, a customer had been running inventory planning overnight because SAP would crash if the process ran in the morning, according to the company. Dodge AI said it updated the process, made it 132 times faster, removed the need for a 10-person maintenance team, and improved order allocation time by eight hours.

"Enterprises see what AI can do, but legacy IT keeps them stuck in maintenance mode. Within days of working with us, that burden lifts, and they can focus on the bigger picture," said Aditya Patil, Chief Operating Officer of Dodge AI.

Investors in the round said the company is addressing a large but underserved segment of enterprise technology. Maintenance of core applications has remained less visible than system replacement or broad digital transformation projects, but it continues to consume budgets and staff time at major companies.

"Application maintenance is one of the largest and least modernized categories in enterprise technology," said Prayank Swaroop, Investor at Accel.

"Dodge AI is taking on the work that keeps the world's most important systems running every day. By starting with maintenance, the team is building the context layer enterprises need before agents can safely operate in production," Swaroop said.