How AI can support financial investment teams: Q&A with Rogo co-Founder and CEO Gabriel Stengel

Key Highlights

• Citi Ventures' investment in Rogo underscores the shift of AI from an experimental tool to essential infrastructure for global financial services.
• Rogo automates financial modeling, research and other complex workflows for finance professionals.
• Rogo embeds AI directly into existing workflows and leverages former bankers and investors to build its products for the industry's real-world needs.

Financial professionals are inundated with vast amounts of unstructured data from myriad first party and third-party sources, whether it be investment banking, private capital or asset and wealth management. These teams are looking to leverage AI to cut down on time, increase the depth of their analyses and tackle more opportunities safely and responsibly.

Rogo is creating a new category of AI-native tools to solve this problem. Their products aim to automate many of the tasks buy and sell side financial teams face. The company's platform functions as an agentic partner that can build financial models, synthesize research and generate formatted deliverables, freeing up client professionals to spend more time on judgment, mentoring and business development. Citi Ventures' investment in Rogo builds on our thesis that AI in financial services has indeed shifted from experimentation to essential infrastructure, alongside continued safe implementation and compliance. This strategic investment round reflects a shared conviction that Rogo is the leading platform in the category with more than 50,000 professions across 350+ firms using the product today.

Citi Ventures is proud to be on this journey with Rogo. To provide further insight into Citi Ventures' investment, and learn more about Rogo, we sat down with co-founder and CEO, Gabriel Stengel.

Learning faster

Nick: There has been a lot of talk about FDEs (Forward Deployed Engineers), you all use FDBs (Forward Deployed Bankers). What does this unlock for your customers and Rogo as a business?

Gabriel: At Rogo, we have forward deployed bankers and investors. These are teams of professionals who have sat in the seats our users sit in, so they can sit across the table from a managing director, understand how she sources deals, and build agents that meet that firm's standards and best practices. They also own change management, which at institutions this regulated and this complex is never a one-time project. Models change and the way work gets done shifts every few months, so retraining and re-enabling people is a continuous job. For customers, this is the difference between software that they have access to and software that they use. For Rogo, it means we learn faster than anyone else about what these firms need next.

Productivity gains

Nick: Rogo is deployed across some of the largest banks in the world. Could you walk us through some of the productivity gains that you all are seeing? For junior or senior bankers? How do you think this will change over time?

Gabriel: I think this is one of the most interesting moments to be in finance. Junior bankers are already reallocating time from manual work toward the parts of the job that are more intellectually stimulating, which means they're getting to advise their seniors and their clients earlier in their careers. For senior bankers, the unlock is different. They can put twenty years of deal history and experience to work in real time. We've heard from managing directors that they use Rogo to build new presentation pages with Felix from a plane seat, and walk into a client meeting with sharper ideas than they could have before. Over time, as producing the work gets easier, the premium shifts to whether you can bring novel ideas and whether you can serve more clients, better.

Meeting customers where they are

Nick: Rogo has a web-application interface, agents, integrations with Microsoft suite (Excel, PowerPoint), and Felix's email interface. How important is it to meet your customers where they are? Which interface(s) do you anticipate will be most used in the future?

Gabriel: It's foundational for us, because a single interface doesn't work inside institutions this large. Within the same bank you'll find people who live in the Rogo application, people who want to hand Felix a task over email, and people who never want to leave Excel or PowerPoint and just want the intelligence embedded where they already work. Our job is to make Felix present in whichever of those places makes sense for the task.

As for which interface will be most used, I expect the embedded surfaces and the agentic ones to grow fastest, because that's where Rogo can take on whole workflows rather than just answer a question. But the honest answer is that it will vary by role, and we're building for all of them.

Rogo's product releases

Nick: What are some of the latest releases on Rogo's platform that you are excited about?

Gabriel:Two things. The first is Deal Room, which gives humans and agents a dedicated space to work a live deal together. It integrates with virtual data rooms like Intralinks and Datasite, so a team can query across the entire data room, produce client-ready materials, management trackers, and meeting prep, and write everything back to their CRM without leaving Rogo. The goal is to let deal makers get from data to decision as quickly as possible.

The second is Intelligence, which gives anyone at the firm a 360-degree view of their deals, clients, and relationships. An AI platform is only as good as the context you give it, and for most banks that context is scattered across systems and inboxes. We recently acquired Arvo, the only regulatory-compliant AI note-taker approved and deployed inside Wall Street's largest firms. Arvo is a natural extension of Intelligence. Meetings are where some of the highest-value information in finance is created, yet almost none of it makes its way back into the systems where deal teams actually work. Pulling all this context together into actionable data agents can act on is a massive unlock for our clients.

Looking ahead

Nick: Looking ahead, where do you want to take the entire platform? Moving to adjacent financial services sectors (PE/VC) or move to adjacent software categories?

Gabriel: We started in investment banking, but we're now deployed everywhere where financial analysis demands accuracy, auditability, and security: private equity and credit, wealth and asset management, equity research, corporate and commercial banking, and the finance and strategy teams inside corporations. Each of these verticals requires deep customer empathy and a nuanced understanding of how that specific group works, which is why we don't think you can build for finance at arm's length.

Our focus is on making the deal-making experience as efficient, streamlined, and agent-native as possible. A deal touches a dozen systems, and Felix needs to work across all of them, because the workflow doesn't stop at the edge of any one tool.

Building at the application layer

Nick: There are split opinions about the durability of AI companies building at the application layer. What do you think are the key benefits to customers and strategically how do you think about providing lasting value above the model layer?

Gabriel: Value is accruing to the application layer and domain-specific harnesses because there is a massive gap between raw model intelligence and actually driving change inside an enterprise. Closing that gap means connecting a firm's fragmented data, building for the peculiarities of each institution, deploying with the observability and governance regulators expect, and driving the adoption that turns a capability into an outcome.

Financial institutions demand the highest quality at the most efficient price, and no single model delivers both for every task. Because Rogo is model-agnostic, we route each workflow to the model that performs best for it, and as the labs compete, those gains flow straight to our customers. That matters because we are in the business of delivering outcomes, not selling tokens. Our incentives are aligned with our clients', which keeps us focused on solving their biggest priorities rather than maximizing consumption.

The product surface area in finance is much more expansive than a chat interface. We're excited about the form factors that human-agent and agent-agent collaboration in finance will take, but it's hard to predict those from the outside. Building the experiences our customers need before they've asked for them requires living inside the industry.

Role of VC in AI adoption

Nick: What role is venture capital playing among financial services enterprises to further AI adoption?

Gabriel: When a bank's venture arm invests in a platform, it signals internally that the institution intends to build with that platform rather than watch from the sidelines. It also gives us a partner who can pull the right decision makers together in one room to move progress and adoption forward.

We now have nine global banks on our cap table, and the practical effect is a tight feedback loop between the people building the product and the people who will live in it. That loop is how meaningful AI adoption happens in this industry.

For more information, email Nick Sands at [email protected].

To learn more about Citi Ventures and our portfolio, click here.