Jo Gallagher: Welcome to Trader TV. Your insight into institutional trading. I'm Jo Gallagher, and I'm joined by Katie Savignano and Isabel Carman at LTX to discuss the growing functionality of AI tools on the fixed income desk and where they've been applied to real world use cases.

Katie Savignano: Hi, Jo. It's great to be here.

Isabel Carman: Thanks for having us.

Jo Gallagher: So to start us off, what is the appetite for AI Tools on the buy- side desk?

Katie Savignano: AI's been on everyone's mind since the launch of ChatGPT. And for us, especially since launching BondGPT two years ago, we've been hearing a lot of questions from clients around how to approach AI in trading. A big theme is the buy versus build conversation. We've seen clients use scarce resources to build entire AI task forces to develop proofs of concept, test APIs and look for ways to integrate AI into their stack. But firms are realizing how complex it is to build something from scratch, you know, especially aggregating the right data and fitting it cleanly into existing workflows.

Isabel Carman: In our conversations with clients, AI has shifted from a curiosity to a serious priority. But the challenge is separating hype from real utility. And honestly, this is why the response to BondGPT has been so strong. Clients conceive right away that it's not just another chat bot. It's trained specifically on corporate bond data and built to think exactly how traders and PMs do, how they ask questions and consume information. It also already understands bond market jargon and trading conventions, which makes adoption really simple. With BondGPT+, clients can actually bring their own data into the mix, combining our models and compliance infrastructure with their proprietary data. This gives clients a way to move quickly without sacrificing control. And instead of building from scratch, they can just plug into a secure, flexible system that can be completely tailored to their needs and connect via API or our UI.

Katie Savignano: And that's all backed by our patented multi agent architecture where multiple AI models are collaborating and even challenging each other to produce more accurate and well-rounded answers. This all helps clients see BondGPT as both a secure and scalable way to bring AI into their business without the risk or resource strain of building from the ground.

Jo Gallagher: Some see AI systems as black boxes. So why use AI, like BondGPT, over traditional tools?

Isabel Carman: Yeah, well, skepticism is totally fair, and honestly, it's healthy. AI is evolving very quickly, so firms are right to ask tough questions. That's exactly why we built BondGPT with responsible AI principles from day one. We put in strong guard rails around data security, compliance, and accuracy, which, as a Broadridge, company are non negotiables and client data is never used to train any of our models or outside of its intended workflow. Unlike some AI tools, BondGPT is not a black box. So it actually explains to users how it got to each answer through our step by step patented show your work feature. We've also reduced the AI's ability to think generatively, which prevents hallucinations and keeps results grounded in real data. And lastly, because it's built on Broadridge infrastructure, client data is protected at every step. It's this combination that's really driving adoption. And let's not forget. There was a time when people were hesitant to even use calculators on the trading floor. Now, of course, we've gone way past that. We think AI is going in the same direction towards broader acceptance across trading. So firms that lean in early and responsibly are going to have a major edge.

Jo Gallagher: So how can AI be effectively integrated into trader workflows?

Katie Savignano: One age old problem is clients can't find the extra screen space or spend even 5 minutes on another application. So we built Bond GPT Intelligence. Now, BondGPT intelligence is about meaning traders where they are, instead of asking them to learn a new tool or jump into a separate system, we're embedding AI directly into the workflows they already rely on, like their watch list, trade blotter, and trade ticket. What makes this different than existing AI workflows is how proactive this is. As a trader navigates platform, BondGPT Intelligence is anticipating what they might need next, whether that's bid ask context, recent trade data, similar bonds, or insights from ICE and Trace. It brings forth that information in real time, right when it's most relevant in the form of seamless and platform prompts. So instead of disrupting the workflow, we're enhancing it. Traders don't have to go back and forth between systems, so they can make faster, more confident decisions, which is a huge step forward with integrating AI into the daily trading process.

Jo Gallagher: So what's next? How do you intend to build up BondGPT’s functionality further?

Isabel Carman: Well, like Katie said, we're continuing to expand BondGPT’s reach across the platform, we're layering in new datasets, refining the models responses, and further deepening the integration into the trading workflow. We're also hyper focused on client feedback and learning how traders are actually using the system, so what's working, what's not, and how we can better support them. It's this kind of input that's really going to keep Bond GPT ahead of the curve, not just adapting to the market, but really shaping where it's going.

Katie Savignano: And we're seeing a ton of momentum around BondGPT+. The version of BondGPT where clients bring proprietary data into the experience, and we're expanding into new fixed income asset classes. This is all with the goal of making AI an embedded part of the entire investment life cycle.

Jo Gallagher: I'd like to thank Katie and Isabel for their insight, and of course, you for watching. To catch your other shows, including Trader TV this week every Monday at 6:45 A.M. UK Time. Go to Tradertv.net.