These Uber alums are building an army of AI agents for the workforce

Minh Pham and JJ Ford have a knack for riding the waves of new tech.

The duo joined Uber in its early days, helping to spearhead mobile development. When CEO Travis Kalanick was ousted in 2017, Pham and Ford followed him out. Kalanick soon founded CloudKitchens—and Ford was his first call. Ford’s first call? Pham.

After five years at CloudKitchens, they were ready for the next frontier. Over the years, they’d built a battle-tested engineering team that successfully tackled both the mobile surge at Uber and the infrastructure demands at CloudKitchens. They also had a hunch: While many startups were focused on building single-use AI agents, Pham and Ford saw the future in orchestrating many agents to work together. In 2023, they founded the California-based company Invisible.

“How do you build a system that allows one person to manage thousands of agents?” Ford asks, noting that he and Pham used their enterprise experience to develop a solution that’s different from any they’ve seen in the market previously.

Inside Invisible

Most AI agents today handle single tasks—ordering food, booking travel—without human input. Pham compares them to “task assistants.” But Invisible’s product stacks these agents, enabling them to tackle multiple tasks in parallel.

“We want to turn AI agents into an elastic, reliable, and scalable workforce for a company,” Pham says. “Most companies think of using a single agent from Anthropic or OpenAI. We think of it as an orchestration platform for multiple agents, acting like how you have a team of humans doing work.”

Invisible’s system is hierarchical. A top-level agent breaks down a task, delegates subtasks to lower-level agents, and coordinates the process. “What we found is, when you have a hierarchy of agents like that, the sum is much larger than what a single agent could do,” Pham says.

Three months ago, Invisible launched A3, short for Action Agent API. While they declined to share revenue, Pham and Ford confirmed a $7 million fundraising round last year. Their customers, Pham says, include large-scale companies like mortgage brokers and solar providers.

“We’re already running pilots and engaging in active discussions with dozens of Fortune-scale enterprises eager to deploy A3 and streamline their most critical workflows,” Minh says.

Stacking a workforce

A3 operates on a company’s existing standard operating procedures. Uber, for instance, has hundreds of thousands of playbooks. Once A3 is trained on these, a company can scale its agent workforce up or down as needed.

Pham cites the example of “Know Your Customer” checks—an expensive compliance requirement in fintech. The work involves compiling detailed reports to verify legitimacy and creditworthiness, often through manual research. “We were able to go in and completely automate this process within days of working with the company,” Pham says.

Invisible is priced like a workforce, too. Unlike competitors that use a subscription model, Invisible charges 10 cents per action. According to Pham, that usually adds up to about $12 per hour—roughly the cost of a human worker—and could decrease as AI costs drop.

“We want to think of it as a workforce, and we have to come up with a whole new pricing model to match that,” Pham says. Ford adds that per-action pricing makes it easy for companies to “easily come online, stand up a workforce, make it elastic, and then pull it down.”

The implications of an AI agent workforce are far-reaching—and potentially disruptive. Still, the founders emphasize the upside. A3, Ford says, “allows employees to climb the value chain of what they’re delivering to the company.”

For better or worse, the agents are coming. And Invisible is betting they’ll be most powerful when stacked.

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