Vaishnavi Yeruva.

I'm an AI engineer and researcher working at the seam between frontier research and production infrastructure. My career has run both directions across that seam: publishing peer-reviewed work in speech and machine learning (INTERSPEECH, ICANN, IEEE) out of the Indian Institute of Science, then shipping AI systems that operate at the scale of hundreds of millions of users.

Today I architect agentic LLM systems for Fortune 500 clients (multi-agent orchestration, MCP-integrated workflows, evaluation, guardrails, and observability) as a senior AI consultant with a global Big Four practice. Recent work includes re-engineering a financial-services firm's software delivery around agentic development patterns, cutting feature cycle time from one week to one day, and designing agentic root-cause-analysis systems for one of the world's largest consumer internet platforms.

Before that: machine learning for healthcare at CVS Health and Anthem, where predictive pipelines and explainable AI turned model outputs into deployed care-outreach programs; and research at IISc Bangalore, where a collaboration with GE Healthcare cut system processing time by 66%. I hold an M.S. in Artificial Intelligence from Northwestern University.

Vaish.ai is where those threads converge. Statistical engines are extraordinary, and insufficient for decisions that cannot afford to be wrong. So I'm building the operating layer around them: ARCH for causal reasoning, CORTEX for reliability under pressure, CART for continuous adversarial assurance. The prefrontal cortex for generative AI.