From startup to enterprise, with agents

Why this conversation

Building an agent is one problem. Getting it to paying customers, finding the money to grow and running it at a cost that makes sense are others, and those are the problems San Ramani of MobilityeCommerce talks about. The host recorded with him on 23 October 2026, the second day of AGNTCon + MCPCon North America in San Jose. San walked through the four things his team does for young companies and for brands, from enterprise sales and investors to data centres and marketing, and where AI fits into all of it. The day’s other conversations are in the article on day two.

Getting startups into the enterprise

San’s team works with startups in the Bay Area, helping them scale and grow as they build agents and agentic commerce. That work is what brought him to the conference. The first thing the team offers them is go-to-market, and here it leans on its ERP background: it counts more than 6,000 customers across the world’s ERP systems, SAP, Oracle and Microsoft Dynamics among them. That experience is what lets it help new companies that build agents actually execute in an enterprise environment.

The second line of work is called Investor Connect. Once a startup has found product-market fit, the team helps it raise funding from top investors around the world, so that it can keep growing.

Power, water and local AI

The third line is the build-out of data centres, the infrastructure that AI runs on. Here the team brings investors and end users together. Enterprises that are moving to AI, San says, need secure access to power, to water and to low-cost AI, so that they can operate profitably and efficiently as they move their business onto an AI platform. The reason is cost: “Because AI is very, very expensive without you owning much of those components.” That is why, in his view, local AI has become what enterprises focus on, and it is one of the places where his team helps.

Marketing, run autonomously

The fourth line serves brands and covers their whole marketing: product placement, promotion, pricing and market access, all handled through a single channel that can do the work autonomously. The aim is speed. A brand can find out what it should make before it makes it, and whether its ideas are valid. When the product launches, it can scale and go to market through existing connections, from physical stores to online channels and social media, with long-term marketing in mind.

San frames the opportunity in terms of reach, with more than 6 billion people worldwide. “They can solve a small problem, but that is useful for 6 billion people.” If a company can reach everyone who needs what it makes as soon as possible, the time it takes to get to market shrinks.

Eighty people, worldwide

Asked how big the team is, San says about 80 people, and that the company now gets more done with 80 than it used to with more than 100. Its coverage is not limited to the Bay Area. “No, we are worldwide.” It helps companies bring both tech and physical products to market.

What occupies him now is how AI can play a role in every one of these processes. The team works with AI companies on one side and with finance and accounting companies on the other, as well as with investors, and tries to bridge the gap between them. In practice, if an investor is interested in a company, San’s team helps it put its go-to-market, financial and accounting systems in order. With those in place it can raise the money it needs to scale, and its ideas reach the market quickly and efficiently. For anyone who wants to get in touch, San points to LinkedIn.

When it comes out

The episode is edited and in the release order. Like every episode it goes out on YouTube first, then on Apple Podcasts, Spotify and Amazon Music.