In a recent long form video interview with AGORACOM (see link at the end of this article), Fobi AI CEO Rob Anson and CTO Uddeshya Agrawal unveiled AgenticBrain, the company’s conversational agentic AI platform designed to fundamentally transform how customers interact with businesses. Rather than forcing users to navigate websites, download apps, and click through predetermined menus, AgenticBrain enables customers to simply tell a business what they want through messaging channels billions already use daily, including WhatsApp, iMessage, and Telegram. The platform represents the final piece connecting FORTRESS (sovereign enterprise AI), FIXYR (intelligent communication and orchestration), AltID 3.0 (sovereign identity and quantum secured trust), and Fobi’s planned next generation wallet into what management calls the Fobi Flywheel, an interconnected ecosystem designed to deliver multiple recurring revenue streams from single customer relationships.
AGORACOM Beyond The Mic Feature Article Issued On Behalf of Fobi AI Inc.
September 3, 2026
From Navigating Businesses to Telling Them What You Want
For over two decades, interacting with companies online has required consumers to learn how each business wants to be approached. Open the website. Download the app. Navigate through menus. Search for the right page. Fill out forms. Move through a series of predetermined steps. That model, according to Anson, is reaching the end of its useful life.
“It’s about evolution,” Anson explained. “We were introduced to the internet, and everyone built web pages where everybody taps and navigates. Then we introduced chatbots to try to accelerate some of the communication gaps. And in this case here now, this is the next evolution. When you have the integrated flywheel in action, this is all about personalization, it’s all about action, it’s all about efficiencies.”
The shift represents a fundamental reversal of the traditional online customer experience model. Instead of the customer adapting to the business’s interface, AgenticBrain enables the business to understand and respond to the customer’s natural language requests. As Anson put it: “You’ve got a direct path to action and execution now.”
Not a Chatbot—An Action Engine
Agrawal was emphatic about distinguishing AgenticBrain from the customer service chatbots that have proliferated in recent years, particularly following the rise of generative AI.
“A chatbot can only answer your question,” Agrawal stated. “It cannot get work done for you. AgenticBrain gets work done for you.”
The distinction is critical. Most chatbots are designed to provide information or route inquiries to human agents. AgenticBrain, by contrast, is engineered to understand customer requests, access a company’s existing systems through APIs (application programming interfaces, the technical bridges that allow different software systems to communicate), and complete authorized transactions autonomously.
“Can your business be talked to?” Agrawal asked. “Most companies would say no. Now, how do we make your business able to be talked to? AgenticBrain. Once you integrate with AgenticBrain, your businesses can be easily talked to.”
That capability becomes increasingly important as the digital landscape evolves. Agrawal noted that within two years, personal AI agents will likely handle routine tasks like booking flights on behalf of users. Businesses that cannot be conversationally accessed by those AI agents risk becoming irrelevant. “If a business could not be talked to, the AI won’t be interacting with it,” Agrawal warned.
Enterprise Integration Measured in Hours and Days, Not Months
One of the most striking claims in the interview centered on implementation speed. Agrawal explained that AgenticBrain can transform existing enterprise APIs into conversational interfaces in hours, not the months typically associated with major technology deployments.
The process works by recognizing that despite the apparent complexity of enterprise systems, most businesses rely on a relatively limited set of core actions. “The set of actions barely exceed 100 actions,” Agrawal explained. “All the sophistication comes in the security, comes in the speed, comes in the sandboxing of things. But if you drill them down, the actions are always less than 100.”
Using an airline as an example, Agrawal noted: “What do you do from an airline? You check whether an airline is valid or not. You check what seats are available or not, you check their price, you check their timing, you can’t even name more than 15 actions about it.”
AgenticBrain integrates with a company’s existing API documentation and system descriptions, learns how those systems work, and exposes that functionality through a conversational interface. Customers are authenticated through their phone numbers, eliminating the need for separate login credentials or complicated onboarding processes.
“Rather than a person sitting behind a computer replying you, it will be the AgenticBrain that will be replying to you,” Agrawal explained.
Anson emphasized that this rapid deployment capability represents a fundamental shift in how technology integrations are typically executed. “Traditionally would have been half a year to three-month integration cycles. Now, it’s literally hours and days.”
The Competitive Imperative and Channel Partner Strategy
The discussion turned to market strategy, with Anson acknowledging that while every industry represents a potential customer, Fobi cannot pursue every opportunity directly. Instead, the company is focused on building a channel partner ecosystem that can scale AgenticBrain deployments across multiple verticals simultaneously.
“I have no interest in driving around in the white van, the Fobi van and selling this,” Anson said. “For us, our scale will come through channel partner enablement. And the response here has been exceptional, I would say, so far.”
The competitive dynamics favor rapid adoption. Once one company in a sector deploys conversational AI capabilities, competitors face immediate pressure to follow. If customers discover they can book, modify, or resolve issues through simple WhatsApp messages with one airline, for example, the friction involved in navigating a competitor’s website or app suddenly becomes a competitive disadvantage.
“Everybody’s looking to become more engaging, more interactive, providing a more streamlined user experience, understanding their customer,” Anson noted. “This is exactly where everyone is looking in terms of costs, becoming more efficient, and a point of differentiation.”
Anson also observed that market cycles that previously stretched six months to a year have compressed dramatically. “Everything’s moving so quickly, we don’t want to be left behind,” he said. “Businesses can’t afford to sit on their hands. They become irrelevant literally overnight.”
Enterprise Focus and API Requirements
When asked whether AgenticBrain is designed for small businesses or enterprises, Agrawal was direct: the platform targets organizations with existing API infrastructure.
“API is what acts as a food for AgenticBrain,” Agrawal explained. “That is what AgenticBrain feeds on, learns on, and connects with. And to be honest, we don’t really care about the small websites, because one, there is not too much of revenue, and then there is not too much of traffic or consumer there as well. So right now, our focus is solely on enterprises.”
This enterprise focus aligns with industries where customer service, booking management, authentication, and transaction completion represent significant operational costs and customer experience challenges, including travel and hospitality, financial services, telecommunications, healthcare, utilities, and government services.
The Fobi Triple Moat: Private, Native, and Closed Loop
A key question addressed in the interview concerned competitive defensibility. What prevents larger technology companies or well-funded competitors from building similar capabilities?
Agrawal pointed to what Fobi calls its Triple Moat: the company’s private infrastructure, native development approach, and closed-loop data architecture. But more fundamentally, he emphasized the integrated nature of the Fobi Flywheel itself.
“It’s a flywheel,” Agrawal stated. “AgenticBrain, what it runs on, what powers the intelligence layer, FORTRESS, what powers the authentication identification layer, AltID, what powers the consumer understanding support layer, FIXYR. Well, you want to build it? Feel free. But then you would have to invest years of intelligence, trillion of data points that Fobi has collected over all those years. I would say hours and hours of compute on which we have trained all of this, and then the vision that Rob brings, and the technical abilities that I bring, combining all of that.”
The implication is that while individual components might be replicated, the integrated, battle-tested ecosystem represents a meaningful barrier to entry.
The Flywheel in Action: An Airline Example
To illustrate how the four components of the Fobi Flywheel work together, Agrawal walked through an airline use case.
A customer could verify their identity and complete KYC (know your customer) requirements through AltID 3.0, ensuring the person is who they claim to be and confirming their physical location through satellite-verified presence. Rather than opening an app, entering passwords, and validating through multiple screens, the customer simply texts the airline’s AgenticBrain-enabled number on WhatsApp to book or modify flights.
Behind the scenes, FORTRESS provides the sovereign AI intelligence layer, enabling dynamic pricing decisions based on booking velocity, tourism trends, and other factors, all running within the airline’s controlled infrastructure rather than relying on external AI platforms. When issues arise, such as lost baggage, FIXYR handles customer support autonomously, eliminating hours-long wait times on hold.
“Based on the industry we interact with, we need to fine-tune what weightage we need to give on what product,” Agrawal noted. “For example, if we talk about a law firm, there would be a huge weightage on FORTRESS, but less weightage on the FIXYR side of things.”
The flexibility to emphasize different components based on industry needs while maintaining the integrated architecture represents a key commercial advantage.
Preparing for Agent-to-Agent Interactions
Perhaps the most forward-looking element of the interview addressed a future where personal AI agents handle routine tasks on behalf of users. Rather than individuals messaging businesses directly, their AI assistants would discover services, negotiate terms, and complete transactions autonomously.
AgenticBrain is explicitly designed for that future. When a personal AI agent needs to book a flight, a business without conversational AI infrastructure forces that agent to visually parse web pages, identify interface elements, and simulate clicks, a process Agrawal described as slow, expensive in terms of computational tokens, and inefficient.
“While it books your flight, your flight will already take off,” Agrawal said, only half joking.
With AgenticBrain, agent-to-agent communication becomes streamlined. “One agent communicates with other agent,” Agrawal explained. “Your agent talks to the AgenticBrain of an airline in a language they both understand. They talk with each other, they sort a plan, and your agent tells that, hey, boom, this works.”
Agrawal noted that AI researchers are already experimenting with specialized languages for agent-to-agent communication, suggesting the shift from human-to-business to agent-to-business interactions may arrive faster than many anticipate.
Revenue Model Centered on Licensing
When asked about revenue models, Anson confirmed that while AgenticBrain could support enterprise licensing, usage-based scaling, or closed-loop performance fees, the company’s primary focus is on annual licensing agreements.
“Ultimately, at the end of the day, we like to get to licensing,” Anson stated. “Licensing, we see, will be the biggest path to scale, most definitely. A lot of the conversations right now around what does an annual license look like? That’s really where we’re trying to get to.”
Anson also hinted at significant cost advantages in Fobi’s underlying architecture. “Uddesh has really architected something to be very disruptive in that market. I don’t think anyone will be able to compete on price,” he said. “We’ll have huge margin gaps built into it that we’ll be able to aggressively adjust as needed.”
This combination of rapid deployment, enterprise-grade capabilities, and competitive pricing is designed to make AgenticBrain an accessible entry point for organizations seeking to implement AI strategies without massive infrastructure investments.
Demo Coming After Labor Day
For investors eager to see the Fobi Flywheel in action, Agrawal confirmed that a comprehensive demo is in development and expected to be released shortly after Labor Day.
“We are working really hard on that to create a demo that explains how the entire flywheel integrates, and we are looking at a timeline after the Labor Day, very near after the Labor Day,” Agrawal said. “And we are super excited to show this to our investors and the whole world, what we have been building and what we are capable of, and how we solve the AI strategy for any company in this world.”
Selling Simplicity: One Ecosystem, Multiple Revenue Streams
Anson addressed the question of whether selling an integrated flywheel of four interconnected products is more complex than selling a single standalone solution. His answer emphasized future-proofing and unified vendor relationships.
“The key there is really about future-proof,” Anson explained. “We’re providing the gateway to transform standardized business practice of today to now tomorrow and future’s evolution here. People would rather deal with one than four. We provide the new standard of technology integration, but we provide all the comfort of future-proof readiness.”
The a la carte approach allows customers to start with one component and expand across the flywheel as needs evolve, while each additional product deployment creates new recurring revenue opportunities for Fobi without requiring entirely new customer acquisition efforts.
Investor Takeaway
AgenticBrain represents the conversational interface layer connecting FORTRESS, FIXYR, AltID 3.0, and Fobi’s planned next generation wallet into a cohesive ecosystem. The platform’s ability to integrate with existing enterprise APIs in hours or days, rather than months, positions it as an accessible entry point for organizations under pressure to deploy AI strategies quickly.
The shift from navigating businesses to conversing with them addresses a genuine friction point in customer experience while preparing enterprise infrastructure for a future where autonomous AI agents transact on behalf of users. For Fobi, AgenticBrain expands addressable markets while creating multiple paths to recurring revenue through licensing, deployment fees, and usage-based models.
With a channel partner strategy designed to scale deployments across industries simultaneously, competitive pricing enabled by proprietary architecture, and a demo expected shortly after Labor Day, management is positioning AgenticBrain as both a standalone product and the connective tissue that makes the broader Fobi Flywheel commercially viable.
As Anson concluded: “This is built to scale. Everything you’ve seen that we’ve come to market with traditionally would have been half a year to three-month integration cycles. Now, it’s literally hours and days. This is the power of the roadmap Uddeshya built here. The beauty about what I love here is this is an easy sell.”
TO WATCH THE FULL VIDEO GO TO: https://www.youtube.com/playlist?list=PLfL457LW0vdKRzZ61NXeYFyshLOXxNJO2
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Agoracom owns shares in Fobi AI from a previous client relationship.
Last modified: September 3, 2026
