Hey there, we're KONTEXT
We are a small team creating new ways to understand how people experience their cities, because ignoring local knowledge and crowd intelligence is one of the fastest ways for place-based decisions to go wrong.
Our platform connects urban-decision makers with real-world context so they can understand, act, and succeed.
A more democratic future for cities
It is difficult, often impossible, to include every opinion and every lived experience in a single plan or decision. Cities are shared by people with different needs, histories, and priorities, so there will never be one version of a place that works for everyone.
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What we try to do instead is make sure those differences are visible. By listening to how people talk about their streets, neighbourhoods, and everyday lives, we help decision-makers find paths that work for more people, more of the time.
How we ended up here
We started with a simple idea. Cities should be planned with the people who live in them. Today, we build the technology to make that possible at scale.
Research
Long before we started building software, our Founder Lorenz explored how people relate to places, and how their knowledge often fails to make it into planning.
Putting ideas to work
Born out of award-winning research, Lorenz wanted to take things further and build something people could actually use. He began to connect Human Geography with emerging technologies that could translate tacit urban knowledge into something tangible, searchable, and actionable.
A hard lesson
The first idea was Residentlink, a digital participation platform meant to give residents a voice. It failed miserably. People did not want yet another app, and the market was far smaller than it looked on paper. What failed as a product turned out to be a useful lesson. We learned that people don't need more spaces to speak - decision-makers need better tools to listen.
Teaming up
As the ideas behind KONTEXT grew, it became clear that turning them into a real platform would require serious engineering. Lorenz began looking for a technical co-founder who could bring Human Geography into code. The search led to Chuansheng. With a background in Autonomous Systems from DTU and hands-on experience in machine learning, LLMs, NLP, and data engineering, he brought the technical depth needed to turn urban theory into something real
Building from scratch
We did not have the budget to hire an agency (for branding or coding or literally anything), and we were not willing to cut corners with vibe coding tools that did not meet the standards we set for ourselves. So we built it ourselves.
That meant Lorenz learning how to design prototypes in Figma, picking up Python, and dealing with the less glamorous parts of running a company, like figuring out what OpEx, SAM, and TAM even mean, all within a few months. It came with endless days of work, more than a few panic attacks, and plenty of uncomfortable questions about what he was doing with his life.
For Chuansheng, it meant turning a constant stream of half-formed ideas into working code, handling an endless list of requests, and steadily building the technical backbone that made KONTEXT real.
Where we are now
This is how we ended up here. We are still far from where we want to be, and there are many important milestones ahead of us.
But the direction feels right. Early users are finding value in what we are building, and even institutional investors have begun to reach out, curious about what this could become. That mix of real-world feedback and growing interest gives us the energy to keep going.
Meet the minds behind KONTEXT
We are building KONTEXT at the intersection of social science and technology, exploring how qualitative insight and computational tools can work together to make sense of urban life.
Follow our journey on social media
We started with a vision and very little else. Now, we're figuring everything out as we go. Join us on our social feeds for a backstage look at how we’re remastering qualitative methods and navigating the chaos of the startup world. We’re intentionally not active on X. It’s a political choice, and for us, a small form of protest.
Have questions?
Below you’ll find answers to the questions we’re asked most often about KONTEXT. If you'd like to go deeper, our field notes collect case studies, perspectives, and stories that together reflect how our work unfolds in practice. And if something's still unclear, just talk to us.
What is KONTEXT?
KONTEXT is an AI-powered urban intelligence platform that helps you understand how people experience cities. It lets you see the city through the eyes of its people.
You can think of KONTEXT as a form of remote sensing for qualitative data. We call it social sensing. For decades, satellites have looked down on cities and measured what is happening through quantitative data like temperature, air quality, or traffic flows. That view is powerful, no doubt, but it stops at "what" is happening. It cannot explain the "why".
KONTEXT looks at the city from within. It focuses on qualitative data captured in language. Satellites are great, but they can't show why people are angry about a street redesign, or why they love Long Street and ignore Short Street. Those answers live in language, opinions, and everyday experiences.
Although we would love to take credit for being magical, and for turning all that qualitative data into something useful by saying something cool like “Aberto!”, the reality is a lot less glamorous. If you’re looking for magic, you’ll have to head to Hogwarts.
At KONTEXT, we work with more earthly tools. We know a thing or two about people and place, large language models, autonomous systems, sentiment analysis, and trend detection. What comes back from that work are clear, readable summaries of what currently bugs people in your city, surfaced as trends, emerging patterns, risks, and opportunities.
Who is KONTEXT for?
KONTEXT is built for people who make decisions about cities and places, and who need to understand how those places are actually experienced.
That includes people working in governments and municipalities, urban planning and architecture, transport and mobility, real estate and asset management, tourism and destination management, retail, hospitality, and events. It also includes less "obvious" professions such as journalists, who try to make sense of what is happening in cities and why.
What all of our clients have in common is not a specific job description or industry, but questions: How do people really feel about this place? What works, what doesn’t, and where are tensions or opportunities starting to form? And why?
What kind of data does KONTEXT use?
KONTEXT works exclusively with information that people already share publicly and voluntarily. This includes public posts and comments on social platforms, online reviews, forum discussions, news articles, blogs, and public visual content such as image captions.
We do not access private data, personal messages, or paywalled content. Everything the system analyzes is part of the open digital layer of the city. When we speak of a "source", we simply refer to a platform or data feed KONTEXT listens to. This can include social platforms like Reddit or Bluesky, review sites, forums, and news or RSS feeds. Depending on your plan, KONTEXT listens to a different number of sources, typically 3, 6, or 10 or more.
What does ethical urban intelligence mean to us?
Lorenz, our founder, is a Human Geographer at heart and a Social scientist by training. That background comes with a habit of looking beyond immediate results and considering how systems affect people and society more broadly. For that reason, ethics at KONTEXT are not an afterthought. They have shaped how we design, build, and operate the platform from the very beginning. We apply the same rigor to ethical questions as we do to technical architecture.
Our approach is grounded in four foundational principles. The system is subject to continuous audit. Accountable human oversight is always required. We work exclusively with publicly available data and do not rely on unethical or illegal data scraping practices. And we focus on aggregated patterns rather than individuals, automatically removing personal identifiers along the way.
Our goal is insight into places, not monitoring of people. This distinction matters.
Can I choose what KONTEXT tracks?
Yes. You have full control over what KONTEXT tracks and analyzes. When you get started, KONTEXT asks you to select your industry. Based on that choice, the platform suggests a set of topics that are commonly relevant for your field, but you can also enter your unique topic that is not covered by our suggestions. You can change, add, or remove topics at any time. As soon as you do, KONTEXT updates the analysis accordingly, so your insights always reflect your current focus. There is no need to set up a new project or start from scratch.
What makes KONTEXT different from traditional qualitative data collection methods?
Since you’re exploring KONTEXT, we’ll skip the basics of why qualitative insight matters for good decision-making. We’ll assume that part is already clear.The conversations happening online describe how places and spaces are actually experienced, without prompts, filters, or participation barriers. Compared to traditional methods, combining qualitative insight with computational data analysis techniques allows us to work faster, at greater scale, and with broader representation, using significantly fewer resources.
Traditional qualitative methods such as surveys, interviews, workshops, and focus groups are valuable (and we do not attempt to replace them but rather to complement them), but they come with clear limits. They take time to organize, are expensive to run at scale, and usually capture feedback from a small and often unrepresentative group. By the time results are compiled, they often reflect the a snapshot from the past rather than what is happening now. Because KONTEXT analyzes massive social data stream continuously and at scale, it provides a live, place-based picture of sentiment, patterns, risks, and opportunities across cities and neighborhoods. Insights update as conversations change, making them more timely and more representative than one-off studies.