I'm a UX researcher working on B2B and technical products: API platforms, developer portals, and the teams who have to explain them.
Two recent projects from B2B and developer-tools work.
Discovery sprint
A one-week discovery sprint with account managers at an energy company. The findings shaped an AI-assisted content workflow that is now live on the client's developer portal.
View case study
Framework design
A framework for measuring developer portal maturity, tested on 30+ client portals and partly automated to cut assessment time from 7 hours to 1.
View case study
Móni has a remarkable ability to challenge assumptions constructively and bring new perspective to any product discussions and dilemmas to help decision making.
Pronovix Team
What sets Mónika apart is her thoughtful approach to research. She asks the right questions, designs rigorous studies, and communicates findings clearly to both technical and non-technical stakeholders.
Pronovix Team
Discovery sprint
Account managers already understood their clients. What they lacked was the confidence and language to connect technical capabilities to business value. A one-week discovery sprint showed what was getting in the way.
The company had invested heavily in its API ecosystem, but these products rarely surfaced in customer conversations. While account managers excelled at understanding client needs, they often lacked the confidence and language to introduce technical solutions. API discussions typically happened only after customers asked for them, so the company relied on a small group of technical specialists.
We set out to help account managers link technical capabilities to the business outcomes their clients care about.
My role
As the UX researcher, I planned a mixed-methods study that fit a five-day sprint, trained the designers to run interviews alongside me so the whole team heard customers firsthand, and mentored one designer through their first sessions.
We had five days to understand the problem, shape a concept, and test it with users. We kept everything in a shared Miro board, so research and design decisions developed side by side.
Clustered observations as interviews happened, so the team worked from the same evidence all week.
Found two mental models: relationship-focused account managers and systems-focused specialists.
Turned findings into "How might we" questions and prioritised them together.
Sketched concepts, mapped flows, and tested the prototype in five usability sessions.
Research informed both the content strategy and the AI workflow: account managers described the customer challenge and selected the APIs used, AI generated a draft focused on business outcomes, and users refined it before publishing. The workflow reduced the effort of documenting success stories while keeping the language aligned with how customers understand value.
The workflow bridges the two mindsets we found: account managers start from the customer's challenge, the technical detail comes in through the APIs they select, and AI translates it into business language they can review before sharing. Each story also comes in two formats, one for each mindset: a one-pager with the benefits for relationship-focused account managers, and a process map for systems-focused specialists.
The workflow was built and is live on the client's developer portal. The site admin and product owner use it to create business-focused documentation, turning technical API details into content written in customer terms.
Instead of training account managers on technical detail, the team invested in customer-ready content they could rely on, and validated it with users before development began.
We started by assuming the barrier was knowledge. Research showed it was confidence.
Confidence came from seeing the content, being able to review it, and trusting that what reached customers was accurate and relevant.
"Last week I started watching the interview recordings. They are super interesting!"
Energy Enterprise Client
"I think it's good that we are engaging. I appreciate the effort to bring all this information together into one place."
Energy Enterprise Client
Enterprise clients had invested heavily in developer portals but had no way to know if they were working, or what to build next.
Framework design
Enterprise clients had invested heavily in developer portals but had no way to know if they were working, or what to build next.
Enterprise clients had invested heavily in developer portals but had no reliable way to evaluate their effectiveness or prioritise improvements. Existing assessments focused on interface quality, not overall portal maturity.
Internally, every evaluation relied on expert judgement, making assessments difficult to compare or scale.
We needed a framework that connected UX, technical capability and business value into one measurable definition of portal maturity.
My role
As the UX researcher, I designed the evaluation framework and validated it on more than 30 client portals.
Before defining portal maturity, I reviewed existing models and interviewed developers using enterprise portals.
Interviews showed that developers experience a portal as more than a website. Documentation, APIs, onboarding, governance and business goals all shape it, so organisations can choose which dimensions matter for their portal.
Reviewed existing maturity models, interviewed developers, and synthesised patterns through card sorting.
Built an evaluation framework informed by research and real-world portal use.
Tested and refined the framework on 30+ client portals.
Created executive-ready data visualisations alongside detailed engineering views for different stakeholders.
Designed an AI-assisted workflow using NotebookLM and Gemini that cut assessment time from 7 hours to 1 per portal while keeping scores consistent.
Our clients' audiences ranged from management to product teams, so I defined two ways to visualise the same results.
A high-level view for management, showing maturity across six stages at a glance.
A more granular view for product owners and product managers, breaking each stage into individual criteria.
Instead of producing static UX audits, the assessment produced recommendations based on the dimensions each organisation chose.
Using NotebookLM and Gemini, I designed an AI-assisted workflow that automated analysis, scoring, and reporting. Manual review remained an essential step to ensure recommendations were accurate and trustworthy.
One example: we assessed the developer portal of the energy company from case study 1. They went with the focus we recommended, improving how their users make decisions.
Not every part of a developer portal matters equally to every organisation.
So instead of scoring every portal against the same checklist, organisations could choose the dimensions most relevant to their goals, and the assessment focused on those.
Account managers already understood their clients. What they lacked was the confidence and language to connect technical capabilities to business value. A one-week discovery sprint showed what was getting in the way.
I'm open to UX research roles and projects in B2B and technical products.