Surety operations run on systems that were never built for the speed, connectivity, or intelligence the market now demands — and technology is now capable of delivering. That gap is exactly what Tinubu is closing, and Rahul Guha is the person driving it.
As Chief Technology Officer of Surety, Rahul brings the kind of cross-sector technical depth that's rare in this space: more than two decades building and scaling high-stakes systems at Intel, Fidelity, Microsoft, and Cisco, across software engineering, architecture, cybersecurity, and product delivery. He's seen what great looks like — and what it takes to get there. Now he's applying that experience to a platform that sits at the center of a market ready for real transformation.
Real-time data APIs. An AI-native underwriting workbench. A fully API-driven architecture that lets carriers, brokers, and agents finally work in concert. The results are already showing up, and the most significant ones are still ahead.
What’s your background? How did you get here?
Rahul: Over my career, I've moved across pretty much every area of software: development, project management, architecture, cybersecurity. If it involves software, I've done it at some point. I have very broad experience of how software should work, how teams should operate, and how to build systems that truly scale.
I started as a software developer in India and moved to the US in 1999. I spent around ten years at Intel, then moved back to India, where I worked with Microsoft and Cisco, and then started my own company, which, like 90% of startups, didn't quite go the distance. But it taught me a lot. I eventually joined Fidelity, where I spent almost 11 years. In 2017, I moved back to the US and settled in Dallas, where I still live.
You joined Tinubu in October 2025. What drew you to the company?
Rahul: I joined with a very clear sense of what the job was — to help the technology team deliver. We have a very strong team, and a big part of my role is to address structure and alignment to help them execute.
There's a recent moment I think about: we had a deployment happening in India, and here in the U.S. it was 1:30 in the morning. At least three people in the US — people who had no obligation to be up at that hour — were awake and tracking how it was going, even though it wasn’t their job. That tells you more about how our team is working together to achieve results than any metric I could give you.
People are invested, and they are aligned in caring about the outcome.
What does being a Chief Technology Officer mean to you?
I take the view that my role is everything connected to making this product succeed. That means product engineering, obviously. It also means supporting the customer success division, building the team, shaping the architecture, monitoring delivery, and making sure nothing is blocked.
I believe you shouldn't have hard walls between departments. If you hire a senior person, they will step in wherever there's a gap. I don't see the boundaries between engineering and sales and customer success as real — they all serve the same outcome.
What changes will customers soon notice?
Rahul: We're upgrading our bond ratings engine to be significantly more granular in how it captures premium calculation, rolling out a new user interface, and enhancing contract bond capabilities with more customized workflows. We're also building tools to bring bonds that currently exist outside the system into the system. We were already leaders in commercial bond management; with new enhancements to the platform, we will now have best-in-class capabilities for contract bonds as well.
We're also changing what’s happening with our data APIs — SuretyQL and TransSync. Right now, those run on nightly batch jobs. We're moving them to real-time. When a bond is issued, that data will be available in your downstream systems within seconds, not the next morning.
Connectivity is a challenge in Surety. What is Tinubu doing to address that for its customers?
Rahul: Surety has the same fundamental pillars as any insurance business: there's a data intake process, premium calculation, policy administration (what we call bond actions), underwriting. All of these things need to talk to each other, but currently, that is a pain point for the industry.
We have customers who want to use our platform with their own UI, with our APIs doing the work underneath. We have carriers whose underwriting happens in their own systems, and they want to connect to ours at specific points. The only way to support all these different, innovative ways of working is to have a solid API layer that serves all of them.
Right now, we are in the final phase of transitioning from a monolithic architecture to an API-first architecture. Think of it like Lego blocks: once you have the foundational pieces in place and properly exposed, you can assemble them in different ways depending on what a customer needs. That's the journey we're on.
Tinubu has a presence on both the carrier side and the broker/agent side. How does that impact customers?
Rahul: This is actually one of the most distinctive things about Tinubu's position in the market, and I think it's underappreciated.
We have the carrier platform, and we also have TSBA — the solution for brokers and agents. Right now, those two sides of the Surety industry are remarkably disconnected. People send PDFs. They send emails. Everything operates in silos.
We are in a unique position to change that. If we can connect both sides of the transaction — carriers and agents and brokers interacting through a seamless, holistic workflow rather than through back-and-forth documents — we make everyone's life easier. The potential efficiency gains are significant. As far as I know, no one else in this market is as well-positioned to do that as Tinubu.
What I've found since joining is that Tinubu has a very interesting and unique position in the Surety market. The more I've dug in, the more I've come to believe in the opportunity.
What role does AI play in Tinubu's product roadmap?
Two distinct things are happening with AI at Tinubu, and it's worth separating them.
The first is AI within our development process. I believe we're the first Surety tech company to have really adopted AI-driven development — what's called ADLC, or Agentic Development Life Cycle. We use it to write code, create test cases, automate testing environments, handle deployments, and triage support tickets: AI helps us understand the problem, propose a fix, and get a solution in front of a developer much faster than before. This makes our team faster and more reliable in what we deliver. We are seeing 70 to 100 percent productivity gains because of it.
The second is AI embedded in the product itself. The most significant example we're working toward is an Underwriter Workbench that is AI-native — AI brings in relevant data, performs analytics, calculates risk scores, and surfaces what an underwriter actually needs to make a decision. We're also building the ability to ingest documents using AI, so that financial statements can be read, parsed, and entered into the system automatically. And we're adding a chatbot to the new UI — not a generic assistant, but one connected to the user's own data. An underwriter will be able to ask "what bonds are up for renewal tomorrow?" or "how many bonds did we write this week?" and get a real, data-driven answer.
The longer-term vision is even more interesting. Think about the exposure problem in Surety underwriting: as a carrier, you know your own exposure to a contractor. But that contractor is likely doing work for multiple carriers simultaneously — their total exposure is spread across the market, and today you can't see it. A lot of that information is actually in the public domain. The question is whether you can pull it together intelligently and surface it in a way that's useful for underwriting decisions. That's the kind of thing AI will make possible, and it's the direction we're building toward.
