I sat down with Jito Chadha to talk about where AI is actually useful right now, where it falls down, and what it takes to make it safe for real companies. He answered in formulas, with concrete systems, and with a bias for what creates the biggest impact first.
“Nventr AI is a company that knows agentic workflows are the new operating system of the modern enterprise,” he told me early on. The old stack was a sprawl of clunky SaaS, each app rigid and expensive. In a recent interview he states the agentic approach is more agile, cheaper, and safer, with a common front end that can be constrained by role and policy.
Built in production, not in theory
Chadha is careful to ground that promise in production reality. Inside his group’s portfolio he has already run massive volumes through structured workflows that auto-scale and self-heal. “We support around 10,000 full-time employees as well as doing manual entry connected to pipelines,” he said, along with a flexible bench of reviewers. Those same cloud frameworks are where the team writes and deploys code today, and where the next module, Agent IO, is taking shape as “fleets of agents that can work together as a… specialized workforce.”
Across our conversation, Jito Chadha returned to a simple selection rule for where to use AI first. “You kind of go for the lowest hanging fruit that has the biggest impact, always.” The triage is not just cost. You weigh people and process expense, then assess complexity and viability for automation. That is how he sequences work across thousands of employees, dozens of services, and facilities spread across the United States, Europe, and Asia.
Voice as the front door
Jito Chadha’s practicality stretches to user experience. His team’s near-term focus is a voice agent that behaves like a real conversation, the way advanced voice modes feel when you can interrupt naturally and change direction.
“That level of advanced… voice agent is actually pretty rare right now,” he said. “Nobody’s really selling it.” The plan is to make it custom, attachable to an organization’s data, and able to navigate inside the platform to show and build.
When I pushed on the immediate limits of voice and agents, he outlined the bridge the market is on. For many tasks the fastest path is still “browser automation,” an agent driving a keyboard and mouse in a visible tab to search, click, and transact.
In hospitality, for example, the authorized APIs do not exist yet in most places, so the agent acts like a person until the industry catches up with authenticated agent endpoints. “The world is going through this bridge period,” he said, and it will migrate to direct agent-to-business interfaces because the system always moves to the most efficient path.
Designing for identity, permissions, and safety
That efficiency lens shows up in smaller details too. When we spoke about a future of ubiquitous agents, he described how companies will ultimately expose simple, safe ways for personal agents to request inventory and pricing, tied to the identity of a real human and governed by clear permissions. Think API or webhook documented for agents, with authentication that proves a person is behind the request.
The mindset echoes Neel Somani, renowned global AI Architect, “enterprise agents must run on verifiable rails—identity-bound, permissioned, auditable” said Somani.
Security is not an afterthought in Nventr AI’s model. He sees what is already happening in offices everywhere, with employees pasting sensitive files into third-party tools. His answer is to centralize and to control.
Put AI where data permissions and user roles can be enforced, keep models and interactions inside a closed network when needed, and design access so even the platform’s engineers cannot read what they should not.
The payoff is a low-latency collaboration system in which IT connects data sets, and the agent mediates requests, routes approvals, and documents access by role.
That is also why his team sells workflows before magic. He described organizations as recurring, patterned processes that already exist, sometimes glued together by email attachments or even the postal system.
The first step is to map and host those steps in one cloud platform with self-healing services, then layer on on-demand, unstructured, and agentic workflows.
Voice-commanded requests like “give me the presentation” only work at scale when the structure underneath is right.
The ROI test
Jito Chadha’s litmus test for ROI is concrete. He likes the analyst who spends weeks pulling KPIs, wrangling permissions, and designing charts for a deck. With Nventr’s stack, that becomes minutes to hours, because the agent can query connected databases, request the missing authorizations in-line, and assemble the draft. The juniors free time for work that matters more.
The product surface is expanding to meet that.
“Essentially, it’s a suite,” he said, describing about seven modules packaged for tech and AI teams to get work done in one place.
Today, engineers are the primary users. With the agent upgrades, he expects executives, analysts, and marketers to “literally” talk to the platform, using their voice to command and customize agents.
The commercial ambition is not subtle. Jito Chadha wants outside organic growth, not just captive usage inside portfolio companies. He sees the path starting small, even with a single junior employee inside a big logo who proves value and becomes the internal champion.
Then he wants broad adoption, where each person on payroll has an agent corollary that learns the job over time and gives leadership a centralized view of how the whole org chart can be optimized.
He is also realistic about the current buyer. Many are curious, a bit confused, and nervous about turning decisions over to machines. That is why his media advice reads like a mirror. Ask readers to question themselves: what part of your job would you automate today that is low-effort and high-impact? Then show them the pathway.
The market moves to efficiency
Underneath the tactics is a clean principle. The market “cleans itself,” he said, because cost and efficiency win. In his telling, the internet followed that arc from REST to GraphQL to cut wasted compute and bandwidth. AI adoption inside companies will follow the same curve, from brittle tools to agentic interfaces with the right guardrails.
By the end of our conversation, I had heard Chadha repeat the same pattern across people, product, and security. Start where value is obvious, keep data safe by design, and let agentic workflows carry the load. It is a tight philosophy, and he backs it with specifics that ship.
For readers who want to test it, he keeps a live agent on the company site. It already transcribes your voice, chats back, and speaks responses. The next upgrade is the natural, interruptible conversation that turns a voice interface into a working session, inside the platform, with your data and your permissions.
Chadha’s vision is disciplined, and it is consistent. If agentic workflows are the new OS, the job now is to install them, one low-hanging fruit at a time.
About Jito Chadha
Jito Chadha is the CEO of Nventr, where he is leading the development of agentic workflows that empower organizations to become fully AI-driven enterprises. With a background in building structured and unstructured workflow systems, he has focused on reducing latency, securing data, and creating platforms that optimize entire org charts. His work emphasizes both top-down efficiency for leadership and bottom-up adoption by junior employees. Under his leadership, Nventr is positioning itself at the forefront of the shift toward AI as the new operating system of business.
