Symphony Secures Prestigious A-Team Award for AI Innovation in Trader Workflow

Symphony, the communications and markets technology company, has been awarded ‘Best AI-Enabled App for Trader Workflow Management’ at the 2025 AI in Capital Markets Awards. This accolade recognises Symphony’s innovative application of artificial intelligence to streamline and enhance the complex daily workflows of traders.

In an exclusive interview with TradingTech Insight, Michael Lynch, Chief Operating Officer at Symphony, discusses the significance of this award and the transformative impact of the company’s AI solutions.

TTI: Congratulations on Symphony winning the award for Best AI Solution for Trader Workflow Management at our AI in Capital Markets Awards! What does this specific recognition mean to the team and for Symphony’s position as an innovator in the industry?

ML: Thank you. Awards like this are always incredibly important. They are recognition of the hard work and focus of the Symphony team. That, coupled with the even more important customer recognition and feedback that we’re helping them solve real problems, is a real validation.

Symphony, since its founding, has always had an open API at its core; we’ve always stood for this. I think this award recognises the evolution we’ve been through over the last couple of years, turning that open API and platform philosophy into solutions that can extend into how our customers are using AI to transform the market.

TTI: Could you give us an overview of the award-winning solution? How does it specifically leverage AI to transform a trader’s daily workflow, moving beyond simple communication to create actionable intelligence from unstructured data?

ML: Here at Symphony, we have a multi-pronged approach to AI with a number of streams. Two of those streams are the most relevant when we talk about trader workflow. The first is what we’re doing around our platform and transforming it into an AI enabler. As you know, Symphony, the messaging platform, has always supported inter-firm communication with inbuilt controls around data loss protection, info barriers, et cetera. What we’re now building into that are more and more tools for users to use those same controls to deploy their agents on that platform. If you think about an agent as a type of user, you can now apply the same controls that you would to a human conversation to an agentic conversation. That has really empowered customers and partners to have a trusted environment in which they can expose those agents to their employees and, excitingly, to their counterparties.

The other key part of our strategy that is very relevant in the trader space is what we’re doing with trader voice analytics. This is where, given our Cloud9 product and our ability to deliver a modern approach to trader voice, we can now add the ability to understand the incredibly complex conversations that happen over our product all day, every day. We can turn those into structured insights that can then be fed into a CRM, a trading system, or a compliance system, and really help our customers make better, faster decisions, not just for themselves, but across the whole desk. It harnesses the intelligence of opportunity across a desk by turning voice data into a usable data set.

TTI: Trader workflows are often fragmented, involving multiple systems and a high volume of communications. What are the key pain points – such as information overload, operational risk, or missed opportunities – that your AI solution is designed to solve for traders and their firms?

ML: The challenge of fragmented, disconnected systems is very real. A lot of the opportunity identification and data synthesis today happens in the trader’s brain. The system does some of it, and increasingly more, but there’s still a lot that depends on a human making a connection across multiple disparate systems and data sets.

Where we are focused with our agent strategy, and where we’re seeing more of our customers leverage AI, is taking the intelligence that is somewhere in a system that they can’t find or don’t know how to access, and exposing that in the right place, at the right time, based on the right prompt. As you think about a move towards autonomous agents, and what you can do in terms of surfacing opportunities or risk situations to a trader, being able to understand that system A has data that connects to system B and being able to expose that to the trader in a way that is understandable and actionable, is a transformative opportunity. A lot of this comes down to desktop real estate and not having enough space on your eighth screen! So, being able to deliver that in a messaging window that you’re already using for other use cases is incredibly powerful.

TTI: Trust and control are paramount when AI is used to interpret trade-related communications. Could you elaborate on the technology underpinning your solution and the measures you have in place to ensure the security and compliance of the data used and the workflows it automates?

ML: Absolutely. Symphony, having grown up in the financial markets, is secure and compliant by design. Whether that’s end-to-end encryption, where our customers own their own encryption keys, our info barriers that help enforce internal regulatory walls, data loss prevention, or malware control, all of these tools have been historically applied to human and bot interaction. We have applied those to agentic flows, which means that our customers can apply the same sort of rules to their agents that they have for human conversation, or apply specific rules that are more or less restrictive based on the use case.

To highlight this specifically, there’s a lot of talk around the difference between a bot and an agent. The key word for me is autonomy. An agent has to have a level of autonomy that a bot today doesn’t. I ask a bot a question, it gives me the answer. An agent takes that a couple of levels further in terms of solving problems for their human or doing flows that have no human involvement. The challenge here is that in a world where we have regulatory controls, autonomy is a scary word. So what we provide allows our customers to deliver autonomy, but with the guardrails that come with the type of security and compliance controls that we have. You have autonomy within that box. As the technology becomes more sophisticated and as our customers become more confident, that box can expand, contract, or change shape, but you can still experiment and really deliver autonomy.

TTI: Can you share some insights into the direct impact this solution has on your clients? What tangible benefits are trading desks experiencing in terms of efficiency gains, reduced operational risk, improved compliance, or even enhanced trading performance?

ML: The number one benefit that we’re already seeing from our customers that have deployed agents with us is the incredible time they are saving by getting the intelligence and information they need faster. Being able to interrogate an agent within a Symphony window to locate a data set or answer a question, for which today they are going into a data system or trading system and doing multiple clicks and queries to find that specific piece of information, is saving a significant amount of time in their trading day. That’s the feedback we’re getting.

This is very much about finding ways to make those kinds of queries for difficult-to-find information – which is often in legacy systems that probably aren’t winning any UI awards anytime soon – much faster. It helps their traders move quickly when the markets are moving quickly. So that’s what we are hearing already in terms of the benefits that our customers are seeing.

TTI: Looking ahead 12-18 months, what do you see as the next major evolution for AI in trader collaboration and workflow management? How is Symphony planning to enhance its offerings to meet those future demands and further evolve the “intelligent desktop”?

ML: I often think about the hype cycle: the initial peak of elevated expectations, and then the trough where it’s like, “Oh man, none of this worked. I thought this was all going to be faster.” Then you move into the steady state of incremental progress towards the real end point, which was never as high as you were hoping at the beginning, but it’s significant.

To me, we are just on that upward slope. I think the trough was probably 2024, where everyone was doing POCs and realised this is much harder than they thought. Everyone had 20 POCs, and now I think most firms have found the three to five that are saying, “Hey, this is going to deliver real value.” We’re now on a path of rapid, incremental innovation toward what those can do to not just make a great demo, but actually deliver tangible, financial benefits to our customers, whether that’s time saved or money made. I think that’s where we are in the market.

And that’s exciting to me, because a lot of this is now around really listening to customers and fine-tuning the product set that you have out there. You have the base, and you need to make sure you’re really solving for that exact right use case that is transformative for your customers. I think that’s going to be the next year or so. Obviously, the broader AI space is going to continue to evolve by leaps and bounds with each new evolution. And all of us as technology providers servicing this market will evolve and capture those and deliver them to our customers.

TTI: Thank you, Michael.