Heather Shoemaker briefly considered growing her business by acquiring a beard. The beard would be artificial. So would the name, Heath, and possibly the voice, altered by software. She had already written the original code for Language IO. Now she was contemplating an engineering project whose sole purpose was to make its engineer more believable.
The idea followed an investor’s observation that an AI pitch would be easier to accept from an older man with facial hair. Shoemaker researched voice modulation, then abandoned the disguise. A funding relationship built on concealing the founder seemed an unpromising arrangement. The absurdity remained useful. It put a face, however imaginary, on the assumptions she kept encountering.
Her career had required plenty of translation already: between Spanish and English, between a customer’s problem and a computer’s instructions, between a working product and an investor’s understanding of it. The beard episode added a particularly tiresome dialect. She was expected to translate herself.
A different kind of language
Growing up in Alaska, Shoemaker thought speaking another language sounded like a superpower. There were ordinary routes to acquiring it. She studied French and Spanish, attended the University of Washington, and earned a bachelor’s degree in Latin American Studies. Her eventual company biography would list time living in Mexico and fluency in English and Spanish.
There was journalism, too. Before becoming a technology founder, she worked as a reporter. Reporting and programming can seem like distant occupations until one considers how much of both involves asking why something happened, discovering that the first explanation is incomplete, and trying again. Her working life would eventually include both ways of investigating a problem.
One turning point arrived through the car radio in Seattle. Working after college as an interpreter and bartender, she heard an NPR report about Java programming and decided to learn to code. Here was another language with practical consequences. Knowing it would let her make things happen, rather than merely describe what had happened.
She went back to school. Her formal credentials came to include a Master of Science from the University of Colorado Boulder’s College of Engineering. The combination of languages and engineering gave her a particular kind of work: helping software travel.
The problem after the launch
For roughly a decade, Shoemaker worked in internationalization engineering, helping large companies refactor source code so applications could support multiple languages. This was technical work with a very human destination. A product designed around one language had to function for people who used another.
She also became senior director of product management and globalization at eCollege, which Pearson acquired during her tenure. Her team built an online college platform that launched globally. She was learning how international products worked at the level of the code and at the level of an organization responsible for delivering them.
Yet one difficulty kept surviving the launch. Once a company had adapted its software, customers still needed help. They sent questions in their own languages. A mostly English-speaking support team had to answer them. Hiring native-speaking agents market by market was expensive and difficult to scale. The translated interface was only the beginning of the conversation.
Those conversations were also unruly. Customers used misspellings, abbreviations, slang and company-specific vocabulary. They were asking for assistance, not submitting entries to a translation competition. A system that handled polished prose could still struggle with the message that actually arrived in a support queue.
Her technical approach made room for the fact that translation engines have different strengths. Language IO could select an engine for the content being translated and apply the terminology a particular business needed. A product name, for instance, has a job to do within a conversation; treating it as ordinary vocabulary can lose the point. The company built a layer around existing translation engines to handle those requirements. That distinction helps explain why Shoemaker saw a business opportunity even when large technology companies already offered translation. The useful question was how their output would work inside a customer support conversation.
“I wrote the original code, version one of the Language I/O platform.”
Heather Shoemaker, on building the product
Language IO’s legal entity was formed in 2011. Shoemaker and co-founder Kaarina Kvaavik were initially involved in other projects, so formation and full attention arrived years apart. After Shoemaker sold her previous company, Cheyenne Technology, the pair focused on Language IO around the end of 2016 and beginning of 2017.
The partnership combined Shoemaker’s engineering and language background with Kvaavik’s experience in localization, sales and marketing. They bootstrapped the business. An early customer needed knowledge-base articles translated; later requests pushed the product toward real-time support inside the systems agents already used. Customer conversations were helping determine what the software should become.
- 01 Customer writes
In their own language - 02 Translation adapts
Model + terminology - 03 Agent responds
Inside the support system - 04 Conversation continues
Across the language gap
The beard in the pitch meeting
Writing the product gave Shoemaker a degree of independence. She could build an answer to a customer request herself. Raising money exposed her to a different set of dependencies. She needed people who understood the market, accepted her technical authority and were willing to back the business.
Competitors were attracting investment. Organic growth had been possible, but the pace of the market was changing. Staying self-funded now carried its own risk: other companies could expand faster and take the customers Language IO wanted to serve. Venture capital became a practical decision rather than an inevitable badge of arrival.
Some investors questioned how difficult her code would be to reproduce. Another described women founders as more trainable. The beard remark belonged to this collection of revealing comments. Each diverted attention from the ordinary questions a business needed answered: what customers wanted, how the product worked, and what growth would require.
Eventually she found investors whose experience shortened the explanation. Boston investor Bob Davoli, of Gutbrain Ventures, understood the enterprise software opportunity and the distinction between Language IO’s work and a general-purpose translation service. The conversation could proceed to the business itself. After enough unhelpful meetings, that was a considerable improvement.
Language IO announced a $5 million funding round in March 2021 and another $6.5 million in January 2022. An $8 million Series A1 followed in 2023. The investments came with hiring and development attached. They changed the resources available to the team and the pace at which its founders could expand the business.
An address that opened a door
Wyoming played a direct part in that financing story. At a tech boot camp graduation party in Cheyenne, Shoemaker was approached by Jerad Stack of Breakthrough 307. He knew she had a software startup in the state. His angel group was interested in investing. For once, the founder did not have to begin by persuading someone to notice her.
The location made her visible within a smaller business community looking for ways to diversify its economy. A software company selling beyond Wyoming offered something local investors wanted to encourage. The encounter helped produce a $500,000 angel investment and a route toward further backing.
State support became more substantial in 2023. The Wyoming Venture Capital Fund made its first investment in Language IO and was the largest investor in the company’s $8 million round, which was led by Joint Effects. Headquarters had become more than an address at the bottom of a document.
Language IO is formed.
The founders shift their full attention to it.
A $5 million round funds expansion.
An $8 million round includes WYVC’s first investment.
Shoemaker has spoken about the benefits of building in Cheyenne while hiring a distributed team. She values the local workforce and the freedom to recruit beyond it. Modern collaboration tools make the arrangement practical. The familiar instruction to move toward the technology industry’s established centers held less appeal than building where she wanted to live.
“Wyoming allows you to do things a little differently.”
Heather Shoemaker
Who gets understood next?
As the business expanded, her own job changed. The person who could write the first version had to make room for specialists in sales, finance and product. She has described learning to let talented hires do their work. Technical competence had made the company possible; keeping every decision with its first programmer would make growth harder.
Recognition followed. Inc. included her on its 2024 Female Founders list. In 2026, she appeared on Forbes’ 50 Over 50: Innovation list. She greeted that later distinction on LinkedIn with a joke about losing the ability to pretend she was 29. The acceptance speech, mercifully, fit into a post.
Her interest in whose perspective counts now extends into AI itself. In February 2026 she wrote about addressing the Texas Women’s Leadership Conference in Austin. Her teenage daughter had helped advise on her outfit. Shoemaker arrived with concerns about how her discussion of gender and cultural bias in AI would land.
The account is revealing because she also examines her own assumptions about the audience. Conversations after the panel, followed by messages from attendees, complicated her first impression. For someone building technology to help people understand one another, it was a useful reminder that the listener deserves a second look.
In May 2026, she announced the integration of Google Gemini and DeepL NextGen into Language IO’s translation engine. Her emphasis included context, terminology and brand voice, alongside the company’s commitments about customer data. The underlying problem remained recognizable: a person needs help, and the words have to carry the right meaning.
The route from Alaska to a Wyoming software company had supplied Shoemaker with several ways to approach that problem. Languages taught her to cross between meanings. Engineering gave her a way to build the crossing. Fundraising taught her how stubbornly people can misread the person standing in front of them. She kept her name, left the beard unworn, and carried on with the company.