Jenny is co-founder of Evenly an AI orchestration platform that makes communication accessible across every customer touchpoint, in real time, in 120 languages. She holds an MBA and a background in psychology and marketing. Her last corporate role was at HSBC, where she served as Head of Marketing for Greece and subsequently as Senior International Marketing Manager, with responsibility for markets including Greece, Kazakhstan, and Armenia, actively contributing to the bank's expansion in complex and emerging environments. Today, through Evenly, she combines technology and business strategy to build solutions with real commercial and social impact, redefining how communication becomes accessible to everyone. We met with Jenny and talked about her career journey and her work with Evenly. Here's what she told us. 

Tell us a bit about Evenly — how did the idea come about, and what made you realize there was a market need for your solutions?

In March 2020, Athens went into lockdown. A close family member of my co-founder, Panos Konstantinidis, is hard of hearing, and has been relying on lip reading to complete what her ears could not catch. When masks went up, that part of her communication stopped working, and we started looking at how many people were quietly in a similar position.

The number was much larger than the disability statistics suggest. Around one billion people globally live with a condition that affects communication, but the more interesting figure for any business sits next to it. Hundreds of millions of customers, in any given European market, do not speak the local language fluently, are navigating an unfamiliar context, or are simply trying to complete a transaction under conditions the original service was not designed for. The migrant filling out a banking form, the tourist at the airport, the patient understanding a diagnosis, the customer reading a contract in their second language. Every one of them is economically active, and every one of them is conducting business with organisations that lose the interaction halfway through.

What we saw was a new layer of customer experience taking shape. The next era of CX is not faster service or prettier interfaces. It is the ability to be understood, by any customer, in any language, through any sense. That layer did not exist, and we set out to build it.

What sets you apart from the competition? What specific value do you deliver to your customers and partners? 

The decision that shaped Evenly was made in 2020, when artificial intelligence was still finding its commercial shape. The prevailing wisdom at the time was that serious innovation meant training your own model from scratch. We disagreed, and the disagreement turned out to be the most consequential call we ever made.

It was already visible, even then, that the field was about to enter a long cycle in which every few months a new player would set a new state of the art for speech, translation, reasoning, or voice synthesis. Designing a monolithic system inside that environment seemed to us a way of locking customers to whoever happened to be best on a given Tuesday and behind by Wednesday. So we built Evenly as an orchestration layer instead, a modular pipeline in which every component can be swapped for whatever performs best, costs least, or meets a specific regulatory requirement at a given moment. When a provider has an issue or is no longer the best option, we route around it without the customer ever seeing the seam. When a new model improves on a particular language, or on specialised vocabulary like legal or financial, we integrate it within days. Our customers operate at the frontier of the technology without carrying the volatility of it.

The approach was contested for several years. Today, every CIO of a regulated institution in Europe is rebuilding their architecture to escape single vendor dependence. 

Around the architecture sit the layers that turn it into production infrastructure. Compliance aligned with WCAG 2.2 AAA, GDPR, the AI Act, and the European Accessibility Act. Routing intelligence accumulated across regulated sectors. Depth in 100+ languages. Training the systems with terminologies.  A deployment model that runs in the cloud or as an air gapped appliance, for institutions where data cannot leave the building. That combination is the reason Eurobank, Athens International Airport, AADE, PPC (DEH), Affidea, Credia Bank, the Delphi Economic Forum and other big players chose Evenly over both incumbents and newer alternatives.

What has been your biggest challenge so far?

The hardest work has been moving accessibility out of the compliance/legal or PR department and into the operating conversation. For two decades this category was treated as a line item designed to avoid a fine, or for CSR reasons, with no one in the room asking whether the customer who could not hear the agent ever bought the product, or whether the visitor who closed the tab because the form did not work for them came back. The loss was invisible because no one was measuring it.

Our job has been to make that loss visible, and to express it in the language leadership uses. Addressable market that the organization is not reaching, conversion that drops at the point of friction, retention that erodes inside segments no one has named, brand equity that quietly thins among the people who feel unseen by the brand. Once that picture is on the table, accessibility stops being a compliance topic and starts being a customer experience decision with a number attached.

What are the most important lessons you've learned along the way? 

Three, and they did not arrive in the order I expected.

The first is that the strength of a company's “why” determines how much “what” it can survive. A genuine reason for the company to exist is the only thing that holds the team together through the stretches no one is romantic about, and it is the only filter that consistently produces the right decisions when the easier option is on the table. Everything else can be replaced. The why cannot.

The second is that enterprise customers buy a worldview before they buy a product. Every important contract we have closed began in a conversation where the room understood why this technology has to exist, well before anyone opened the compliance or pricing page. Features are validation, references are reassurance, but the actual sale happens earlier, in the moment a serious institution decides that the company on the other side of the table is solving something they themselves believe matters.

The third, which we are still learning to use fully, is that building infrastructure of global ambition from Greece is an underestimated advantage. Multilingual reality is part of ordinary life here, woven through tourism, migration, the diaspora, and the daily traffic between languages. Add EU regulatory clarity and an engineering talent pool that costs a fraction of London or Berlin without the depth gap, and the geography starts to read as a structural asset rather than a constraint. 

AI is at the core of your offering. As the technology advances, where do you see the biggest impact on your value proposition? And how can AI actively support greater inclusion — both inside organizations and in the markets they serve?

Artificial intelligence has changed the economics of inclusion more profoundly than any policy intervention of the past thirty years. Solutions that until recently required specialist teams, bespoke integration, and budgets only the largest organizations could approve are now deployable in a hospital, a tax authority, or a medium sized company in a matter of days. The constraint that used to define this market has moved from cost to ambition.

There is a quieter shift underneath that one, which I think will matter more in the long run. The artificial intelligence systems that will define the next decade are the ones trained on real, multilingual, human interaction across regulated sectors, anonymized at source and ethically governed. That kind of real-life data does not exist in scraped web corpora. It exists inside operational platforms running every day across banks, public services, healthcare, and live events. Evenly sits on precisely that kind of data, generated continuously in multiple languages, with the regulatory architecture to use it responsibly. The global AI ecosystem will need this, and Greece, sitting at the linguistic crossroads of Europe with a clear EU regulatory framework, is unusually well placed to contribute to it.

Where this leads, in the end, is straightforward. The day will come when failing to understand a customer because of language or ability will look as out of place as a building without a ramp at the entrance. We intend to be one of the reasons that day arrives sooner.