Swap Language
Xenophobia is sweeping over the west and with it, an increased risk of poverty or social exclusion for hundreds of millions of foreigners. A staggering 50,1% of non-EU citizens risk poverty or social exclusion in the EU, but it is extremely difficult to get a job or get included in society without understanding the local language and culture.
The Aarhus Community.
In 2017 we launched swaplanguage.com, a free, community run, AI-driven service that facilitates in-person language and cultural exchange. We are a community of 10,000 swappers who have set up 16,000 exchanges across Europe.
Franz and Omar from Syria.
Meet Franz Obermeier, our most active swapper. In 2018 he set up 101 language exchanges with immigrants from the middle east.
Our mission is to bring peace by breaking down language and cultural barriers and we do it by giving the millions of people like Franz the tech to scale their generosity globally.
Poverty and social exclusion go hand in hand, and affect billions of people worldwide.
There is one factor that affects your risk of ending up socially excluded or in poverty more than anything else: Being a foreigner.
We are well positioned to first tackle the problem in the EU and then the world. There are 22,3 mio non-EU citizens living in their EU and they are facing hard odds. Not knowing the local language and culture is the main reason that they have a 50,1% risk of experiencing social exclusion or poverty and the political trend is turning locals against them which is escalating the problem.
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So why not just learn the local language? This opens up another problem. The inefficiency of existing language learning services. Out of the 2 billion language learners in the world, 1,5 billion will give up learning to speak it. Existing solutions teach you the grammar, but not how to speak.
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To work, our platform needs locals and internationals in each city.
The optimal ratio is 50/50.
1-on-1 paid language lesson in Nepali.
Locals: 20% in the age group 25-34 and usually working in Business, IT and Education. Motivated by 1) Personal growth and 2) Career.
Foreigners: 20% in the age group 25-34 and usually working in various industries. Motivated by 1) Getting integrated and 2) Career.
The platform www.swaplanguage.com empowers native speakers to share their language and culture.
By putting in Language and location, we match the native speakers in a neighborhood that want to learn each others languages. People then meet up in-person to teach each other. 1-on-1 meetings twice a week usually results in fluency in 8-12 months.
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1-on-1 language swappers.
Each city has it's own community. Some of our 51 volunteers arrange weekly group meetings as it is easier to nudge people to meet under those circumstances. The community page provides topics for lessons and we also pair relevant native speakers with employers helping our foreign users to find work locally. This work can either be:
1) Hired in position in a company that needs their specific linguistic and cultural knowledge.
2) Teach offline language lessons, customized to the users in the local area.
Testing the marketplace for language lessons in Aarhus, DK.
We use AI to match users with both companies and language learners based on their own unique knowledge.
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Spanish-Danish exchange with a focus on engineering interests.
Summed up: Our community is driven by AI to match foreigners and companies for work as well as delivering more efficient language learning to build empathy and understanding between different cultures. Both services improves the quality of life for our users by breaking down language and cultural barriers.
- Create or advance equitable and inclusive economic growth
- Ensure all citizens can overcome barriers to civic participation and inclusion
- Growth
- New business model or process
We use AI to ENHANCE the human potential instead of replacing it.
Our innovation lies in our processes. We started by aiming to disrupt the ancient way that we learn languages: Written exercises in a classroom or on a mobile screen.
Our service is teaching you a language using the most effective method: Interaction with native speakers. We are only doing offline interactions because learning through Skype was negatively affecting the learning process. Thanks to the network effect we can deliver offline, customized language learning to any user in more than 100 languages.
Customer review of customized offline language lessons based don the users own interest.
Swap Language is a human cloud of language skills and cultural knowledge. Our strength lies in the power of the network effect. Every person joining our community improves the service exponentially for the end-consumer, by adding their own unique knowledge to our community. It is our AI's job to match it with the right users or companies.
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Group meeting in Copenhagen.
We also use AI to identify human potential for instance when we recruited 5 finish speaking salesmen for 5 fintech jobs in Copenhagen.
The power of the human cloud is not limited to language learning.
We can deliver translators to the highly fragmented translations market and that is why our AI modules are "learning" machine translation.
Not to replace the native translator, but to give them a tool to improve their performance and a marketplace for customer acquisition.
Our platform is browser based, run by a dynamic AI-algorithm that matches people based on the demand of our users and companies.
We have developed a way of determining the exact language level of a user through multiple data points. We update their level after each offline lesson they have instead of determining their level based on a single exam/test. In this specific functionality we are working on an AI-module that comes with recommendations for adjusting their learning process or suggestions on who they should meet with to improve.
Apart from that we use people browsing patterns to make more accurate matches.
We currently have an AI-module that is learning machine translation through the content created on our platform. This will have collected sufficient data once, we also begin to offer translation task for our users.
- Artificial Intelligence
- Machine Learning
- Social Networks
Our mission is to break down language and cultural barriers, in order to improve peoples' lives by through understanding. Language and cultural knowledge gives foreigners access to jobs and other societal activities and thereby are we directly reduce foreigners' risk of social exclusion and poverty. With our advanced massurement tools, we rate the student's writing, reading, listening and speaking skills after each lesson rather than after a single exam. Every time a user reaches the B2-level they have broken down a language barrier.
In the model below have we illustrated how each of our services are impacting the lives of our foreign and local users, eventually helping us to break down barriers between them. Our current data is suggesting that fluency is reached after 8-12 months if the user sets up meetings twice a week. We are still collecting data, to make sure that we will be able to prove the impact 6 months out in the future.
- Peri-Urban Residents
- Urban Residents
- Very Poor/Poor
- Low-Income
- Middle-Income
- Minorities/Previously Excluded Populations
- Refugees/Internally Displaced Persons
- Austria
- Belgium
- Denmark
- France
- Germany
- Korea South
- Netherlands
- Norway
- Sweden
- Austria
- Belgium
- Denmark
- France
- Germany
- Korea South
- Netherlands
- Norway
- Sweden
Current: 10,670 users. 4,000 active monthly users.
Year 1: 50,000 users. 30,000 active monthly users.
Year 5: 2,200,000 users. 1,500,000 active monthly users.
We currently have 10,670 users
We have around 4,000 active monthly users, and that has led to 16,630 language exchanges, where people have learned about languages and culture and made friends with locals. We currently have critical mass in 6 cities in Europe, and 10 cities by the end of 2019.
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Opening night in 4 of our communities.
50,000 users in the next year
We expect to have raised our engagement with better design and functionalities resulting in 30,000 monthly active users and 80,000 language meetings. We expect to see 18,000 language barriers broken down. Our definition of a broken down language barrier is a swapper reaching a B2-level in the CEFR-framework. We are finally seeing revenue, and this is affecting our ability to grow our community and help more people. We will have a critical mass in 20 cities in Europe, and entering Asia via Seoul.
2,200,000 users in 5 years
We will be present in a 100+ cities across 6 continents. 5 years into the future is a blur of made up numbers, but we STRIVE to reach 1,000,000 language barriers broken down. It will have improved peoples life immensely in terms of better jobs, increased cognitive abilities, reduced dementia, reduced social exclusion and poverty, new friendships, MORE ADVENTURE and reduced international conflict.
Breaking down language barriers to bring peace is what gets us out of bed 05.00 am every morning!
Market barriers: We are promoting offline interaction because we believe that it is so much more valuable to the user both from a learning-, but also a human perspective. This means that we need to create critical mass in every city we enter. We have solved this issue so far by partnering with universities that then uses our services to improve their students. In many cases our platform has replaced their manually managed language exchange program.
Financial: Our many free users have a lot of costs, that we still cannot cover fully ourselves, if we are also to develop our platform further. We will need to take investment in within 8 months. This way we will be able to reach more people in a shorter time span.
Technical: Overall architecture management needs to be world class sot hat we are not accumulating unnecessary server costs and so that we can scale both vertically and horizontally.
Market barriers: We are partnering up with universities all over Europe. In the coming 3 months we are closing a deal with 6 new universities that we are in contact with. This specific project of intercultural exchange with a focus on language is funded by the EU, but it is not yet clear if Swap Language will have access to some of those funds as well. Even so the traction from the university students is usually enough to create initial traction and critical mass for other users in the city to participate in language and cultural exchange. We will continue to partner with universities and create viral loops that helps our community grow organically and with the right type of users.
Financial: We currently looking for investment partners. We have set up meetings with venture capital companies who specifically focus on impact startups. We have meetings with Maze Decoding Impact and Ananda Impact Ventures. We are constantly looking for potential partners in order to secure an investment 8 months out.
Technical: We have hired a CTO from the conglomerate Bestseller. His corporate experience about architecture on a corporate level is helping us create a platform that is going to be able to scale to millions of users.
- For-Profit
5 full time employees.
1 part time employee.
8 Advisory board members.
51 volunteer ambassadors.
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3 volunteer ambassadors in Copenhagen, DK.
4 Board members.
The founder who got the idea was Allan Hermansen. He just could not find effective ways to learn about the Spanish until he started meeting with Spanish speakers.
Hitchhiking to open new communities.
Allan recruited his longtime friend and study partner Nichlas Walsted who was running his marketing company and then sold it to join Allan.
Together the founders invested $45 000 to build the platform, grow the team and scaled the service to more than 10 000 users, 6 employees and 51 volunteers. The drive comes from a lust for adventure and curiosity that has led them to hitchhike more than 20 000 kilometers (5 000 kilometers with Swap language) around the world and opened their homes to 141 foreigners.
Gent community.
The founders recruited Marcin Gadomski for the role of CTO from the conglomerate Bestseller. Marcin could very much relate to our mission as he is a part of the polish population in Denmark who are experiencing social exclusion due to destructive stereotypes.
Management.
To help make this come true we have Agnieszka, Edvinas and Lukas developing.
Jonas our investor is our latest addition. He has an e-commerce business selling formula to Scandinavia and China.
We are 6 language learning programming super stars. We have corporate and startup experience to make this a reality. We have felt the pain, and we are using our service to master our fifth language each. And last but not least, we have a drive to execute our mission to break down barriers!
Aarhus University, Copenhagen University, Aalborg University, University of Southern Denmark, Danish Techinical University: They are using our software to improve the language level of their students and teaching international students the local language and customs.
Lærdansk: We partner with one of the largest government funded language schools in Denmark. They acknowledged their inability to teach people to speak the language and used our meetings for their students to practice.
2021.ai: Our developers are experienced with AI, but we are partnering with AI specialist to propel both ourselves and our product forward!
Our number one priority was to keep our service free for the end-user and that has posed some challenges in becoming financially stable.
We have two streams of income: B2B: Businesses who enter new markets are having a hard time finding native speakers who both have the linguistic abilities, cultural understanding and business experience for full-time positions. Businesses sometimes spend months searching. We match businesses and our users and charge 310 USD per user they hire.
Spiir, Viabill and Nordic API gateway are some of our customers, two of which said it was the fastet recruitment process they had experience. For Spiir we found 16 Finnish speaking candidates in 14 of which they hired 5.
This brings immense value for businesses who are getting candidates that are hard to find, and for our users who get a chance to find employment which often is hard for foreigners.
C2C: 39% of our users have asked to be able to ocasionally pay, rather than teach your own language in return as it is very time-consuming. We are enabling this feature in August 2019.
At the age of 30, the average person will have spent 5 years communication in their own language. This is probably our most practice skillset. The sharing economy is not very inclusive as you need access to expensive assets as cars or property. But this feature is including everyone who are passionate about teaching.
B2B: We have tested the business model by taking on recruitment tasks for 4 companies. They have hired 18 of our users and we have turned USD 5,500 in the process. We will launch this feature to the rest of the communities September 2019.
C2C: We ran a beta test in the town of Aarhus. In the two-month period 5% of our users converted to the paying for lessons on average 2,4 times. We turned USD 13.000. Opening up for this feature in the the 6 cities that we have critical mass will as our user base grows become sustainable, and we can implement more features to support their learning process. We launch this is feature to the rest of our community August 2019.
Common for both models is that it is a market linkage model where we charge a fee for linking different parties.
We have seen that both models work locally. Now we will open it to the rest of our user base and then scale it to Europe, Asia and then the rest of the world.
The only reason that we have gotten where we are is thanks to critical feedback on every aspect of our business.
The way we see it, in terms of critical feedback there is no one who can better take us to the next level than the solvers, alumni, students and staff from MIT.
We are looking for funding from people who believe in our mission to break down language and cultural barriers worldwide. If the funding environment remains obsessed with setting milestones only for the financial growth of startups, future generations will keep suffering. When we read about MIT Solve we realized that there is an strong community that shares our values and we wanted to be a part of it.
Last but not least, we have engaged in partnerships that help university students, by giving them access to our network, but we are not taking advantage of the vast academic knowledge that our partners hold. With MIT Solve we want to create a plan for how to use the full potential of partnering with universities.
- Business model
- Funding and revenue model
- Talent or board members
- Other
We have already touched this briefly, but we are looking for academic partnerships.
Language is the tool that enables us to communicate with other people and even the only tool that enables us describe our own world. Without it we would never have learned anything or connected with other people. Because it is so deeply rooted in the brain, it is also hard to explain. We would very much like to be connected with researchers who are experts within the field of language learning methods.
We would like to partner with institutions in North America, Europe and Asia that are both experts in technology and modern languages. The cultural context of language learning is different in North America and Asia, we could benefit immensely by getting help to understand the local culture as well as getting help to develop our technology. Lastly, by gaining access to student networks our solution would be more valuable to local language learners as more languages and skill sets would be available.
Potential partners could be: MIT, University of Standford, University of Yonsei etc.
Academically we would like help from the universities to effectively measure the impact that we have on our communities around the world as well as help to create more effective language learning processes.
We will always use AI to extend the human potential - never replacing it.
We will use the prize to hire or partner with external partners to help us improve our solution as well as educate our development team in order to solve the following challenges that we discovered on implementing AI:
- Our data structure was no longer static. This has been a challenge for us to handle, but we are striving to make the AI both flexible and easy to manage.
- The difficulty of filtering the data for the right users is increasingly challenging as we grow in user numbers.
- The on-going training of AI-modules take both time and require that we spend a lot of time educating our development team.
- We have developed AI-modules that will be able to assist our users with machine translation in the future, but we need to deliver more modules now that will come in handy in the future as data collection takes time.
With the prize we will ensure that our tech is easy to manage, ready for international scale, well-trained and functioning and able to help our users to combat poverty and social exclusion through linguistic and cultural learning.
Our global communities offer both to up-skill foreginers who do not otherwise have the option of learning languages and culture or getting to know locals. Learning the local language and culture helps them break out of social exclusion. We will use the prize to:
- Improve the way that our users get access to jobs.
- Improve our tech in a manner that accelerates the language learning process for our users, especially foreigners.
- Develop an educational program and material for our volunteers to better spot and assist users that are particularly vulnerable.
- Maintain and develop new AI modules that spot our users needs, and then deliver the appropriate services.
We will use the prize to innovate on the way that we upskill our users, build more empathy between people from different cultures, combat xenophobia with understanding and match vulnerable users with job opportunities.
By also upskilling locals in language and cultural knowledge we are building more empathy between them and foreigners positively affecting the foreigners chances of breaking out of social exclusion and poverty.
Our community improves our users' quality of life by breaking down language and cultural barriers worldwide.
We do focus on helping refugees as a part of our main focus to foreigners in general. The swappers in our community offer their cultural and linguistic knowledge to improve the chances for the refugees to integrate themselves into a new society.
Our most active user, Franz Obermeier, is one of the users that teach their own language and culture without demanding a specific language in return. In 2018 he had 101 language meetings with refugees and students from the middle east. We implemented this feature specifically to help refugees. Often the languages of the refugees were not in high demand when we only matched users through the "a language for a language"-method. So by allowing generous users who just wanted to share their own language and culture asking for nothing in return we could scale their generosity and help those who needed our service the most: refugees.
We will utilize the price of making more effective matches for refugees, and continue working on specifically matching refugees with companies that are looking for their unique cultural and professional skills.
We will improve our free service and implement community generated language learning material to support their learning process. And we will do an active effort to reach the refugees who are afraid to meet up with locals.
We will use the money to break down barriers between refugees and locals to combat xenophobia - effectively improving the quality of life for both groups.
There are 2 billion language learners in the world. Out of them 1,5 billion will never learn to speak.
The problem is that we for centuries have learned languages by solving written exercises without putting speaking into practice. Even today we utilize enabling technologies like VR and AI to AVOID speaking with native speakers. Language apps use AI to simulate written conversations, but the only problem is - the brain learns languages (also syntax, grammar and vocabulary) the same way it learned it's native language: Verbal interaction with native speakers. That is the reason why our service that focus on offline interaction with native speakers has been implemented on 11 universities.
Competitive differentiation and market size for language learning in EU and Asia.
We will use the prize to use AI to extend the human potential when it comes to language learning. We will do it by customized content, to keep the learner engaged while learning, specifically teaching them linguistic and cultural knowledge relevant to them. Our processes utilize native speakers as native language teachers and will disrupt the industry by delivering a faster language learning process and scale with almost zero marginal costs, outperforming traditional services and apps.
We will use the prize to build AI-modules to learn machine translation, giving our community a tool to perform translation expanding into yet another community driven language service of translation.
We strengthen our communities by using enabling technologies in order to disrupt the ineffective language service industry and break down language and cultural barriers.
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