RevRag.AI Acquires GenStaq.ai to Strengthen Enterprise AI Agent Capabilities By integrating GenStaq's plug and play infrastructure platform, RevRag.AI will gain greater control from application layer agents to backend infrastructure.
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Bengaluru-based RevRag.AI has acquired GenStaq.ai, a modular LLMOps and workflow orchestration startup, in a move aimed at expanding its control across the generative AI stack.
The deal marks a significant step in RevRag.AI's strategy to deepen its enterprise-focused offerings and accelerate growth.
As per the official release, by integrating GenStaq's plug and play infrastructure platform, RevRag.AI will gain greater control from application layer agents to backend infrastructure, allowing it to deliver more secure, scalable, and customisable AI systems for businesses.
"The future of GenAI belongs to those who control more than just the application layer," said Ashutosh Prakash Singh, Founder and Chief Executive Officer of RevRag.AI. "By integrating GenStaq's infra capabilities, RevRag.AI is now equipped to deliver more secure, scalable, and customizable AI systems to enterprises."
GenStaq.ai was founded in 2024 by Mayan Kansal and Shivam Kaushik. The company had developed a modular LLMOps platform that included RAG pipelines, session-based APIs, and vector infrastructure, with an emphasis on production readiness for developers. RevRag.AI had previously been a client of GenStaq, which created what both sides describe as a natural alignment in technology and culture.
"Infra alone does not scale without distribution. RevRag.AI had cracked the go-to-market motion in GenAI, we had cracked the infra," said Mayan Kansal, Co-founder and Chief Executive Officer of GenStaq.ai. "This move felt like fitting two halves of the same puzzle."
As part of the acquisition, GenStaq's founding team will join RevRag.AI's core product and engineering leadership. The combined entity will now focus on scaling enterprise partnerships and advancing agentic workflows, while reinforcing its position in the evolving landscape of enterprise AI agents.
