We recently connected with Jito Chadha and have shared our conversation below.

Jito, thanks for taking the time to share your stories with us today What’s the backstory behind how you came up with the idea for your business?

I came up with this idea out of necessity. Inside our family office portfolio, we were running complex, multi-step processes that looked more like a massive pinball machine than anything a person could manage cleanly. We had large teams, freelancers, and data pipelines that all had to connect, scale, and heal themselves. I built the n-cube module to handle those workflows and circuitry for every type of computing process, and once it was carrying serious transaction volume reliably, it was clear we were solving a real operational problem.

The turning point was seeing how people were already using public AI tools with sensitive information just to get their work done. Companies wanted the productivity of AI, but they had no safe way to apply it to their own systems and data. I knew there needed to be a platform that made an organization AI-empowered while still giving it real control over data and permissions. That idea led to the agent product, and what excited me most was the possibility of reshaping how entire organizations work by following a simple logic: the world always moves toward the most efficient way of doing anything if you give it the right tools and guardrails.

Jito, before we move on to more of these sorts of questions, can you take some time to bring our readers up to speed on you and what you do?

I came into this space by trying to keep very large, real-world operations running smoothly. Coordinating thousands of people, facilities, and services forced me to think in terms of workflows, not individual apps. That focus on structured, scalable processes is what eventually turned into Nventr.

Today, Nventr is a suite built around the n-cube workflows, the agent product, and Agent IO, which lets you build fleets of agents that behave like a specialized workforce. Engineers can use it to design and deploy pipelines, and business users can interact with those same systems through agents and voice interfaces without needing to understand the underlying infrastructure. What we solve is the gap between a company’s ambition to use AI and automation and the practical reality of permissions, reliability, and orchestration across many moving parts.

What I am most proud of is that we give people a clear way to decide where to start. I often talk about finding the lowest-hanging fruit that has the biggest impact, balancing cost, complexity, and value. That simple formula can be applied by an executive looking at an entire enterprise or by an individual contributor thinking just about their own role. We have lived that pattern inside our own portfolio for years, and now Nventr makes it available to anyone who wants to modernize how they work.

Any stories or insights that might help us understand how you’ve built such a strong reputation?

A lot of my reputation comes from how I think and talk about systems. I tend to break things down into clear formulas and cause and effect chains, whether it is how agents should be deployed, how workflows route data like a pinball machine, or how browser automation will bridge the world from human-driven interfaces to agent-friendly ones. Executives recognize their own environments in those descriptions, and it shows them that I am not speaking in abstractions.

The other part is that I have always been very direct about security and data governance. From the beginning, I have pointed out that employees are already using AI tools in uncontrolled ways, and that the real solution is not to ban them but to provide a safe, centralized way to use them. That focus on realism and protection, rather than hype, has helped build trust with the types of organizations we work with.

What’s been the most effective strategy for growing your clientele?

The most effective strategy has been to let results speak for themselves. We start by solving a concrete operational problem for a group that really feels the pain, and once the workflows and agents are running reliably, the people using them become advocates inside their own organizations. That kind of inside-out adoption is far more durable than a marketing campaign because it is based on lived experience.

Growth also comes from how quickly a single person can create leverage with Nventr. A junior analyst who normally spends weeks preparing presentations can have an agent assemble the research, data, charts, and slides in a fraction of the time. When they show that to their manager, it naturally raises the question of what else could be automated, and that curiosity drives wider rollout without needing a heavy sales push.

The next phase is opening self-sign-up so that smaller companies and individual contributors can access the same infrastructure that large enterprises use. When someone can turn on that capability instantly, without going through a long procurement cycle, you get very organic growth, because people are directly experiencing the benefit in their own work.

Contact Info:

• Website: https://nventr.ai
• Linkedin: https://www.linkedin.com/in/jito-chadha-b17661b/