Shamrock Raises $5 Mn to Become the Checkpoint Before Enterprise AI Goes Live

Enterprises are racing to put AI agents into critical workflows, but Shamrock AI believes adoption will stall if companies cannot independently verify whether those agents actually behave as expected. The Shillong-headquartered startup has raised $5 million, or roughly ₹47 crore, in seed funding to build an assurance layer for enterprise AI.

The round was led by Endiya Partners with participation from Capria Ventures, marking Shamrock’s first institutional financing. The capital will go toward product development, hiring and expanding its go-to-market operations. Shamrock wants to reach around 15 Fortune 500-scale customers by the end of next year, with annual contract values starting near $200,000 and potentially exceeding $2 million.

Founded in 2026 by Sarat Addanki, Michael Gallagher and Anuraag Nallapati, Shamrock is building what it calls an agentic assurance platform. At its core is an Enterprise Business Knowledge Graph that connects processes, systems, data and configurations, giving AI agents context about how a company actually operates before they are trusted with critical work.

The startup is initially targeting areas where mistakes can become expensive quickly. One early focus is automating testing and validation during major enterprise software transformations such as SAP S/4HANA migrations. Endiya Partners notes that companies can spend hundreds of millions of dollars on such transformations, with a significant portion going toward testing and validation that is still heavily dependent on manual expertise.

Shamrock already serves multiple Fortune 500 customers, including a Fortune 100 AI hardware manufacturer and a Fortune 100 healthcare company. Its client-facing teams will be concentrated in the US, while 70–80% of its workforce is expected to remain in India.

The bigger opportunity is emerging alongside the AI-agent boom itself. As companies move from experimenting with agents to letting them touch revenue, operations and enterprise systems, Shamrock is betting that the layer checking what those agents do could become just as important as the agents themselves.