CoreOps.AI Raises $3.5 Million to Modernise Enterprise Legacy Systems

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Enterprise software startup CoreOps.AI has raised $3.5 million in a pre-Series A round led by Siana Capital Management, with participation from Kettlebrough, Aroa Venture Partners, and several individual investors. The funding marks a strong vote of confidence in the company’s AI-first approach to digital transformation for large enterprises.

Transforming Legacy Systems Through AI
Founded in 2024 by Rajesh Janey, Ankur Sharma, Rajnish Gupta, and Rajiv Srivastava, CoreOps.AI builds a platform that helps enterprises modernise legacy software, consolidate fragmented data systems, and automate operations at scale.

The platform currently supports over 20 enterprise use cases across manufacturing, financial services, retail, and healthcare sectors where outdated systems traditionally slow down digital initiatives.

A Platform-First Alternative to Consulting-Led Transformation
CoreOps.AI differentiates itself by offering automation-driven, platform-based upgrades rather than lengthy consulting-led projects. Its solution enables organisations to integrate data, reduce operational bottlenecks, and execute transformation cycles without the overhead of multi-year service engagements.

The startup positions this model as a more scalable path to digital transformation particularly for large enterprises seeking speed, consistency, and measurable cost savings.

Funding to Fuel Engineering and Enterprise Expansion
The newly raised capital will be used to expand engineering teams, accelerate product development, and scale deployments for enterprise customers globally. The company plans to deepen investments in AI orchestration, data unification, and workflow-driven automation that can be rapidly deployed across complex enterprise environments.

Closing Perspective

As enterprises move away from slow consulting-heavy transformations, CoreOps.AI is positioning itself as a high-leverage, AI-powered platform for modernisation offering faster deployment, lower costs, and scalable automation across legacy-heavy industries.

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