San Francisco, 29 September 2026 – Dodge AI, an artificial intelligence startup focused on enterprise application maintenance and modernisation, has raised $2.65 million in funding, backed by Accel and Google’s AI Futures Fund, to develop technology that helps organisations maintain and improve their business-critical software.
The funding round was led by Accel and Google’s venture initiative, with participation from New Build Venture Capital, Antler, Schema Ventures and angel investors from the SAP ecosystem.
Dodge AI is developing an AI-powered control platform designed to identify software problems, resolve incidents and manage change requests across enterprise applications such as SAP, Salesforce, Microsoft Dynamics, Oracle JD Edwards and Kinaxis.
The company is targeting a market it estimates costs enterprises more than $600 billion annually in software maintenance and operational support. Its platform aims to reduce dependence on manual troubleshooting and external consultants while preserving the institutional knowledge embedded in complex business systems.
Addressing the $600 Billion Enterprise Software Maintenance Challenge
Large organisations depend on enterprise software to manage finance, supply chains, customer relationships, inventory and other essential operations.
However, these systems require continuous maintenance long after their initial implementation. As business requirements evolve, organisations introduce customisations, additional configurations and company-specific operating rules.
Over time, these modifications can create complex software environments that are difficult to understand and maintain.
Dodge AI says the traditional approach often involves large teams of consultants and offshore technology specialists managing incidents, change requests and routine operational problems.
According to the company, some enterprise maintenance arrangements involve teams of 20 to 50 people responsible for keeping essential systems operational.
An additional challenge is that knowledge about previous fixes and customisations may be distributed across support tickets, configuration files and individual employees.
This fragmentation can increase technical debt and make businesses increasingly dependent on the specialists who understand their existing systems.
Dodge AI aims to address these challenges by using artificial intelligence to document operational knowledge and identify the underlying causes of recurring software issues.
How Dodge AI Uses Autonomous Agents to Maintain Enterprise Applications
Dodge AI’s platform operates as a control layer connecting enterprise applications, business processes, IT service management systems and legacy configurations.
It uses AI agents to analyse incidents, identify potential root causes and recommend or execute fixes across connected systems.
The platform is designed to capture the company-specific exceptions and configurations that determine how enterprise applications operate in practice.
For example, a warehouse may follow particular inventory allocation rules, while a pricing system may include exceptions for different customer groups.
These rules are essential for business continuity but may not be fully documented within standard software manuals.
Dodge AI aims to organise this information into what it describes as an exception intelligence context graph, providing AI agents with operational knowledge needed to work within complex enterprise environments.
Rebhav Bharadwaj, Co-Founder and CEO of Dodge AI, explained:
“We believe long-horizon agents can change that.”
He said the company’s objective is to help enterprises continuously improve their critical systems, resolve incidents faster and better understand the technical debt accumulated through years of software maintenance.
Dodge AI Reports 132-Fold Improvement in Inventory Planning
Dodge AI says it is already working with more than a dozen enterprises, including publicly listed companies, on incident management and process optimisation.
The platform reportedly processes hundreds of queries every hour across enterprise software environments.
The company highlighted two examples of its technology in operation.
In one case, a warehouse truck was unable to load because a Goods Receipt Note contained incorrect information. According to Dodge AI, its platform traced the issue across SAP, Kinaxis and internal warehouse software and delivered a fix within minutes.
In another deployment, a company’s inventory planning process had been running overnight because its SAP system experienced crashes when the process was executed during the morning.
Dodge AI says its intervention made the process 132 times faster, removed the need for a ten-person team to maintain that workflow and improved order allocation time by eight hours.
These results are reported by the company and describe specific customer implementations rather than independently verified performance across all deployments.
Why Enterprise AI Needs More Than Powerful Models
Dodge AI’s approach reflects a growing challenge facing organisations adopting advanced artificial intelligence.
Although large language models can generate code, analyse information and support complex reasoning, deploying them inside established enterprise environments requires detailed knowledge of business-specific rules.
A technically correct software change may still create operational problems if it ignores existing configurations, dependencies or exceptions.
Aditya Thakur, Co-Founder and CTO of Dodge AI, said:
“Frontier models are incredibly capable, but enterprise adoption still requires significant hill climbing.”
He explained that Dodge AI is focused on capturing the rules and exceptions necessary for AI systems to operate within enterprise applications while supporting ongoing maintenance.
The company believes that developing this operational context is an important step towards enabling more sophisticated automation of mission-critical software.
From Software Maintenance to Enterprise Modernisation
Beyond resolving incidents, Dodge AI sees maintenance as the foundation for broader enterprise technology transformation.
Modernisation projects can be costly and difficult because organisations must update existing applications without disrupting business operations.
Older systems may contain years of undocumented modifications, making it challenging to migrate processes or introduce new technologies safely.
By building a structured understanding of existing configurations and operational rules, Dodge AI aims to help companies prepare their systems for future changes.
Aditya Patil, Chief Operating Officer of Dodge AI, said the company wants to reduce the time organisations spend maintaining legacy technology so that teams can concentrate on larger transformation projects.
The startup’s longer-term ambition is to develop AI agents capable of proactively identifying recurring issues, improving business processes and executing approved changes across interconnected enterprise applications.
Such capabilities would require reliable safeguards, testing and human accountability before being used in sensitive production environments.
Accel Backs AI-Powered Enterprise Maintenance
The investment reflects growing interest in AI applications designed to improve the management of established enterprise software.
Rather than replacing major business applications, Dodge AI is positioning its technology as an additional intelligence layer capable of working with existing systems.
Prayank Swaroop, an investor at Accel, said:
“Application maintenance is one of the largest and least modernized categories in enterprise technology.”
He explained that Dodge AI’s approach focuses on understanding the operational context of enterprise applications before allowing AI agents to work within production systems.
For large businesses, this could offer opportunities to reduce recurring maintenance costs, improve incident resolution and support gradual modernisation.
However, the commercial value of AI-driven maintenance will depend on reliability, integration complexity, security controls and measurable improvements compared with existing support arrangements.
The Future of AI in Enterprise IT Operations
Dodge AI’s $2.65 million funding round highlights increasing investor interest in applying autonomous AI systems to the operational challenges of large organisations.
Enterprise application maintenance remains essential for businesses that rely on complex software environments to manage daily operations.
By combining incident resolution with the documentation of business-specific rules and exceptions, Dodge AI aims to create a foundation for more advanced enterprise automation.
The company plans to expand its capabilities across maintenance, system configurations and operational processes, with the longer-term goal of enabling AI agents to manage increasingly complex tasks within established enterprise applications.
For businesses evaluating AI adoption, the development illustrates a practical use case: improving the reliability and maintainability of existing technology before introducing broader automated operations.
About Dodge AI
Dodge AI is a San Francisco-based artificial intelligence startup developing a unified platform of AI agents for enterprise application maintenance and modernisation.
The company helps organisations identify root causes, resolve support tickets and improve mission-critical applications across enterprise software environments, including SAP, Salesforce, Microsoft Dynamics, Oracle JD Edwards and Kinaxis.
Its platform uses an exception intelligence context graph to capture operational knowledge and support AI-driven maintenance and modernisation.
Dodge AI is backed by Accel, Google’s AI Futures Fund and other investors.
Official website: https://www.getdodge.ai/
