Trumid Innovation & Technology Culture

How is your team integrating AI and ML into the product development process, and what specific improvements have you seen as a result?

As a leading provider of electronic trading solutions for the capital markets, our initial efforts to deploy AI and ML focused on embedding intelligence into existing features of our trading platform. From an engineering perspective, this approach was initially challenging, as many of our systems weren’t designed with ML use cases in mind. However, more recently, we have shifted to treating AI and ML as first-class considerations right from the ideation phase of new products. This change has allowed us to focus our resources on building more effective models and creating exciting opportunities to better serve our clients and advance our products and solutions.

What strategies are you employing to ensure that your systems and processes keep up with the rapid advancements in AI and ML?

We believe that innovation comes from all areas of the company, not just those directly working on AI and ML. To foster this, we’ve made development environments available to all engineers at Trumid, where they can access the latest Gen AI models and prototype their ideas. This inclusive approach empowers everyone, from front-end engineers and DevOps team members to data engineers and ML researchers, to stay current with model advancements and quickly test their use cases without significant technical barriers.

Can you share some examples of how AI and ML has directly contributed to enhancing your product line or accelerating time to market?

One significant enhancement we’ve made is upgrading our notification system, which alerts users to time-sensitive trading opportunities. We’ve integrated an ML model that scores each opportunity as it’s identified, enabling us to filter notifications so users only receive those that are highly relevant based on their trading objectives. By increasing the success rate of notifications that users engage with, we’re able to deliver more valuable, targeted insights to our clients, ultimately enhancing their platform experience and potential trading outcomes.

What types of products or services does your engineering team build? What problem are you solving for customers?

Trumid combines deep expertise in corporate bond trading with agile technology to deliver innovative liquidity solutions for the fixed income market. One of our trading protocols, Swarms, reimagines how bond traders discover and execute opportunities — powered by high-performance interfaces designed to make the experience fast, intuitive and seamless.

Blending cutting-edge design with deep market insight, Swarms tackles one of bond trading’s biggest challenges, liquidity — finding reliable buyers and sellers in a fragmented market. 

Traditionally, traders source liquidity across venues, potentially revealing intent and driving up costs. Swarms flips that model, bringing participants together in synchronized, anonymous sessions that create fresh liquidity opportunities throughout the day.

We design lightning-fast interfaces for high-stakes environments where milliseconds and precision matter. Our goal is to eliminate friction and empower users to operate at market speed — efficiently and securely.

Tell us about a recent project where your team used AI as a tool. What was it meant to accomplish? How did you use AI to assist?

AI has become a core collaborator across our teams, powering everything from idea generation to production features. Two projects show its impact: We built Chef, an internal Slackbot designed and refined by Trumid Product Analyst Henry Hobin, to cut through the noise of our bond platform and deliver actionable insights directly to sales, with no dashboards required. AI coding assistants help turn rough ideas into prototypes in minutes, letting us iterate quickly on what works. That speed helps us push beyond the typical “good enough” nature of internal tools, fine-tuning alerts for real impact.

We've also used AI to automate manual trade workflows reducing errors and saving time. Together, these innovations show how AI accelerates creativity and helps us deliver smarter, faster tools.

What would that project have looked like if you didn’t have AI as a tool to use? 

Without AI, projects like Chef and other recent initiatives might never have happened. Parsing messy chat logs or experimenting quickly with new ideas would’ve required complex, brittle code that took weeks to build and maintain — work that often outweighed the value.

AI changed that equation. It handles unstructured language effortlessly, allowing us to prototype in hours, not weeks. Instead of debating what’s feasible, we test and learn by running small experiments, keeping what works and discarding what doesn’t.

That shift has redefined how we think about innovation. We’re no longer constrained by what’s “easy to code;” we’re guided by the experience we want to create. AI has made Trumid’s development process faster, more experimental and more human, enabling us to ship more, learn faster and turn once “nice-to-have” ideas into real, valuable tools.

What tools support your day-to-day work?

I lead the team responsible for helping clients and internal partners solve problems across the trading lifecycle, working closely with our sales, product and technology teams to develop practical solutions designed to improve the user experience and support how clients trade on the platform.

We employ a combination of AI-powered solutions that have become integral to how we operate. Claude and ChatGPT help us draft, summarize and think through complex problems quickly, while other AI tools provide a fast research layer for real-time information. Tools such as Glean help us access knowledge across the organization, making it easier to build on existing expertise rather than constantly reinventing the wheel. 

What ties it all together is how we've learned to combine these technologies effectively. Each serves a distinct purpose in supporting our clients and streamlining operations and knowing when and how to apply them has become a skill in itself. 

How does your team experiment?

We experiment by giving ourselves permission to build. When a workflow feels clunky or an operational process is consuming too much time, we don't wait for a formal project to be scoped — we prototype. Using AI tools, team members can test ideas quickly, see what works and iterate from there, while ensuring compliance with our policies, controls and regulatory requirements.

Some experiments become part of how we work permanently. Others teach us something and get shelved. The key is that the barrier to experimentation is low, creating a culture where people feel comfortable identifying a challenge and immediately asking, "what if we built something for this?" 

How does your company adapt to change?

When our team identifies workflow needs that can’t be immediately prioritized by the broader technology organization, we increasingly leverage AI tools to build them ourselves. Supported by strict data, security and engineering guardrails, we have the freedom to safely deploy these capabilities and move at a much faster pace. 

Internal applications, reconciliation tools, calendar utilities — tasks and workflows that might once have sat on a backlog for months can now be developed and deployed in days. In the process, it has reshaped our view of what it means to be resourceful. We're no longer just consumers of technology; we’re becoming builders. 

That adaptability — finding a way forward rather than waiting for a solution — has become an important part of how our team operates, fostering greater ownership, faster problem-solving and a culture of continuous innovation.