skritswap: replace jargon with everyday language

Any information, at any reading level. 

Unlock answers, act on knowledge.

Problem:

According to the US government, 48% of American adults experience low-literacy. The CBC also reported that 49% of Canadian adults are below the desired literacy rate. The U.S. Department of Transportation defined low-literacy as “the difficulty using certin reading, writing, and computational skills considered necessary for functioning in everyday life.” This means people who experience low literacy can read, but not well enough to fill out a job application or read a children’s book.

The economic impact of low literacy issue is staggering. According to ProLiteracy, $230 billion in excess healthcare costs can be linked to low adult literacy. Moreover, low literacy costs the U.S. at least $225 billion each year in non-productivity in the workforce, crime, and loss of tax revenue due to unemployment.

Solution:

skritswap uses artificial intelligence to change the complexity of documents. Imagine Google Translate but instead of different languages, skritswap adapts information to different reading levels. This enables anyone to understand anything.  

Swapping documents to plain language improves clarity thereby increasing efficiency and saving money. It can also be an opportunity for everyone to participate in the knowledge economy and gain mastery of industry-specific jargon.

Change the World:

Every day billions of people turn to the internet to find answers to their questions. Yet, at least half struggle to understand the information they find. skritswap unlocks answers so people can act on knowledge. People will be able to read at their desired comfort level with the click of a button.

But skritswap is not just about meeting people at their most comfortable reading level. It is also about enabling people to build strong literacy skills through experiential learning. Over time skritswap will gradually increase the reading level of topics users consistently read.

Using experiential learning to increase population literacy rates would lead to huge economic growth. According to TD, increasing the literacy rate just 1% in Canada within one year would lead to a ripple effect of $32 billion in economic growth.

From a business perspective when half of people may be struggling to truly understand product communications, this often leads to a break down in trust between customers and businesses. Selling the same products, in the same way, to clients with different individual literacy levels is like having a clothing store with only one size for everyone.

Working with skritswap to personalize product information with varied complexitiy levels results in shorter service-delivery times and increased trust because customers will be able to grasp industry jargon. 

skritswap is a new technology that looks at language and understanding information in entirely new ways. Where society currently offers information in a one-size-fits-most method or tailor it very narrowly to one very specific audience, skritswap enables anyone to adapt any information to any reading level. Imagine mortgages in grade three readability instead of legalese. There are a couple of organizations who offer children's curriculum at multiple reading levels, there are no solutions for adults or seniors. We specifically focus in banking and insurance, soon to be moving into healthcare. These are areas we all engage with across our lifetime.

Only with recent advances in Natural Language Processing and Machine Learning is skritswap's solution possible. 

1. Fine tune the unit economics of specific use cases in insurance with form letters for claim denials

2. Increase the proportion of machine auto-swapping compared to human-in-the-loop elements.

3. Close over $1,000,000 in sales

4. Submit 3-4 patents

Reach half of all 3 billion internet users worldwide. Expand from English and French to include Japanese, Mandarin, Cantonese, Hebrew, German, and Spanish. Include geographic colloquialisms.

We currently deploy through B2B clients to reach our communities of interest. Our clients are inbound finding out about skritswap through the media or pitch competitions. 

This fall when we launch one of our paid pilots we will serve a few hundred young adults in Northern Ontario.

We will serve over 100,000 people within the next year and increase exponentially to 100 million people within the next three years.

CEO, Melissa Kargiannakis – has secured investors in Toronto and Silicon Valley as well as closed one of the biggest banks in Canada as a paying pilot client.

CTO, Darren Redfern – has decades of industry experience writing natural language processing and machine learning algorithms; which is particularly perfect for our low-data situation as we continue to build out the dataset for AI training.

Full Stack Developer – Chris Pagnutti – has consistently delivered 2-4 months ahead of schedule on various product deadlines.

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skritswap will sell our technology to change the reading level of anything in a SaaS model. The first product we have rolled out is a tool where humans can swap complex docs to simpler plain language. The platform has some machine auto-swap capacity and tracks human’s work to train our AI and increase the proportion that the machine does.

We are selling this platform to Plain Language Experts (of which there are approximately 350 worldwide so we will secure market ownership). Banks and insurance companies also want to buy this platform for their work. So we are already selling an interim product on a B2B SaaS model—which is highly scalable.

We also have opportunities to work with channel partners (i.e. in marketing) as we grow to scale faster.

I am applying because of the network benefits and associated prestige. Coming from a small town in Northern Ontario Canada, it has been a journey to gain support and investment from Toronto as well as Silicon Valley; MIT Solve would be another level of support and gravitas.

 Solve can help advance skritswap’s work through:

1. Mentorship with the Brain Trusts
2. Needs Assessment to focus in on the product-market-fit for such a universally applicable technology.
3. Exposure in the media, speaking at the Solve conference, and through partners like the World Economic Forum, Fast Company, and Forbes 30 Under 30.

1. Go-to-Market Strategy: in its final state, skritswap has a universally applicable technology. In the early days as we build and train the AI, being sure we enter the right markets in the right order is critical to our success and sustainability.
2. Networks: Solve can continue to bolster relationships with leaders in key fields (AI, ML, adult literacy, plain language, etc.)
3. Sustainability: the grants will help extend our runway and the profile-raising media opportunities will enable us to secure the necessary investment to continue on.