PropulsionAI Launches Fay as Enterprise AI Agents Move Beyond Chatbots to Real Business Operations

VMPL

New Delhi [India], July 21: San Francisco-headquartered PropulsionAI, Inc., founded by Indian entrepreneurs Harsh Nigam and Rohit Hazra, has launched Fay, an enterprise AI agent and workflow platform designed to help non-technical teams automate complex business operations. The launch marks the next step in the founders’ entrepreneurial journey – from building a 50-member software consultancy that delivered more than 100 digital products globally to developing enterprise AI systems through PropulsionAI, a venture accepted into and funded by UC Berkeley’s Berkeley SkyDeck startup accelerator.

Nigam and Hazra’s partnership dates back to 2008, when the two first connected over a shared interest in technology and product development. In 2016, they co-founded a software consultancy that expanded into a 50-person team and delivered more than 100 software products for customers across industries and international markets. Their experience building enterprise software exposed them to a recurring challenge: while businesses wanted to embrace automation and artificial intelligence, moving AI initiatives from pilots to production remained difficult because of fragmented workflows, integration challenges, and implementation complexity.

That experience ultimately led them to establish PropulsionAI in 2023 with a singular focus on enterprise AI. The company was later accepted and funded by Berkeley SkyDeck, UC Berkeley’s startup accelerator, providing the founders with access to Silicon Valley’s startup ecosystem while validating their vision of building practical AI infrastructure for enterprise operations.

Speaking about the launch, Harsh Nigam, Co-founder of PropulsionAI, said, “After years of building software for enterprises, we saw that teams did not just need another AI chatbot. They needed AI systems that could understand workflows, connect with business tools, and execute operational tasks reliably.”

The founders say that vision shaped the development of Fay. Rather than requiring technical teams to build complex automations through code, the platform enables business users to describe workflows in natural language. Fay’s built-in workflow builder, Architect, then helps create and configure AI agents capable of supporting functions such as customer support, finance, human resources, procurement, compliance, IT operations, revenue operations, and supply chain workflows.

Rohit Hazra, Co-founder of PropulsionAI, added, “Fay is built around the idea that enterprise AI must be practical. Our focus is to help teams move from experimentation to real deployment by combining AI agents with deterministic workflows, integrations, and enterprise-grade controls.”

Fay reflects Nigam and Hazra’s broader thesis that enterprise AI will extend well beyond conversational chatbots. They believe organisations will increasingly require AI systems that can plan, execute, integrate with existing business applications, and complete measurable operational workflows. Fay has been designed around that philosophy by combining natural-language workflow creation, Architect, autonomous AI agents, deterministic workflows, enterprise integrations, and Proof Week – a five-day implementation process that builds a working AI workflow using an organisation’s real business data.

The platform also integrates with workplace applications including Slack, Gmail, Jira, PagerDuty, and webhooks, while supporting multiple AI models such as GPT, Claude, Gemini, and open-source models. For enterprise deployments, Fay includes role-based access control (RBAC), SSO/SAML support, flexible deployment options, and security features designed for larger organisations.

As enterprises continue searching for practical ways to deploy AI across business functions, Nigam and Hazra see the launch of Fay as another milestone in their long entrepreneurial journey – from building enterprise software to developing AI infrastructure intended to help organisations automate operational workflows at scale.

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