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Frequently Asked Questions

Some of the questions we get asked most

FAQ's

These are some of the questions that we get asked most frequently. This is by no means an exhaustive list and we will be adding to it continuously, so please check back here for future updates. If there is a question that you have which has not been answered here, please feel free to get in touch with us using any of these channels and will be pleased to help in any way we can.

1. General Questions

1.1. What is Clairety?

Clairety is an Artificial Intelligence rating agency that tracks the credibility of all half a billion social media contributors, and reports it to you with a browser module that embeds our ratings directly in your social media content. Our fully automated system is completely unbiased and uses no human interaction. We identify bots, spam, harassment, extreme speech and a host of other ‘low value’ content.

1.2. What is the target audience of your product?

Clairety has a number of products planned for release in the next year, and even more in the next 2 years, each of which is designed to address the concerns of a specific demographic. First and foremost is our retail social media product which is designed for the people who are concerned about ‘fake news’ or harassment on social media and the polarizing effect of media bias online. But the very first product we’ll be releasing, our CSMF dataset, is a data product designed specifically for the quantitative cryptocurrency trading industry.

1.3. What is your goal?

Our goal is to make online conversation ‘more like real life’ by addressing the economic inefficiencies in the social media world. The ‘marketplace of ideas’ is a real marketplace. “I don’t buy it.” is a common phrase to express disbelief. By giving our users the tools to filter away content that they don’t believe, we let them translate that disbelief into fewer clicks and views for the publisher. They can literally “not buy it”, and in the process incentivize news producers to create better, more broadly credible content, and to limit the influence of ‘bad actors’ by denying them views.

1.4. How is your project connected with cryptocurrency?

Clairety will be producing a set of credibility factors specifically for the crypto world which will be designed to help traders tell which social media identities are bots, which are used for marketing, and which are truly individual users who are interested in the crypto trading industry.

It’s hard to see from the inside, but in much of the world outside the crypto community, the space still has a serious credibility issue. But a focus on our product represents an effort to address this, and to limit the effect and reach of bad actors. We come from the fiat financial world, and believe that support for a product like ours will be viewed by them as exactly what the crypto-space needs.

1.5. Do you have any support for investors? How can I contact your support team?

We support investors via different channels, so you can find our contacts at the footer of our website.

1.6. Why does [insert person here] have such a [Low/High] score?

All we look at is what people say online. They may have said other things in other formats which caused you to have a particular feeling about their credibility, but we don’t get to see those sources. In general and over time, we believe a person’s credibility can be assessed by the totality of the things they say online. If they really have extreme ideas then eventually they’ll say something about it which is equally extreme. But if enough time goes by and they fail to say something controversial, maybe the issue is that you have a more biased view, and not them. Maybe you should give them another chance.

1.7. I think [insert person here] is extremely credible, why do they have such a [Low/High] score.

For starters, see the question above. We all have our own unavoidable biases, we’re all entitled to our own view, and we’re all entitled to judge the statements of other based on that view. In the broadest terms, we tend to think the people we agree with are more credible than those we disagree with.

Our system has no view of its own so it doesn’t do that. It forms its ‘viewpoint’ from the totality of the statements of others that it reads online. You and your circle of friends may think the midpoint of a particular subject is on one place in the spectrum, but it may well be that majority of social media users feel very differently about it. To us everyone’s view matters and is treated the same.

You can think of our statistic as a reflection of that broadest view. You may find the person credible or not, but there are a whole lot of people outside your specific circle who may feel very differently about it. We treat all those opinions as valid, whatever they are.

1.8. I can draw my own conclusions about ‘Fake News’ what do I need you for?

Your conclusion of what is ‘fake’ and what is not is a reflection of your own point of view, which is exactly as it should be. You’re perfectly entitled to your view, whatever that view is. If you’re interested in how people who don’t share your viewpoint see things, ours will be better metric for ‘fake’ vs ‘real’ than your individual view will. We can show you the true consensus. And who knows… maybe you’re interested in how credible you seem to others? It’s a free product so you might as well give it a shot.

1.9. What if your rating is just ‘wrong’?

Technically all we’re doing is measuring people with a single ruler and reporting their relative differences. It doesn’t matter if the yardstick is measured in inches or meters, the relative differences will be the same. If we’re wrong, we’re wrong in the same amount and to the same degree for everyone.

In effect, this is the whole point, and a correction for some small degree of error is built into the system. We’re never going to be 100% right on 100% of the assessments we make for 100% of the messages. Reducing that error to its mathematical minimum is our biggest priority, and to the degree we succeed, we’ll make our product better.

But all we’re really looking at is the differences between people, not the people themselves. Our AI doesn’t agree or disagree with anyone ever. All it does is try to determine how ‘extreme’ the argument for the position is, compared to the arguments that everyone else is making.

People tend to argue in ways that they themselves would find persuasive by others. What you say is very much a reflection of who you are. That’s the whole point of credibility.

1.10. How do I use your blockchain Dataset to improve my trading returns?

Our CSMF dataset is a tool for professional traders who use data and models to make assessments of the markets. Even on our very small team we have over 50 years of experience in building and developing profitable trading models at some of the premier financial institutions in the world, so we know what goes into the best of them. We know how to obtain an ‘information advantage’, and we believe we can provide one.

To professional traders who are using models,this data will be fairly intuitive. For them, a detailed description of the data and its formation process will be released along with the dataset, and future changes to our process will be tracked over time for historical comparisons and backtesting.

With that said, based on our experience in the space we are completely confident that this data can be used to obtain ‘alpha’ in the blockchain trading world, and are devoted to preserving it as a value added dataset for our supporters.

1.11. If this data is so good why don’t you just trade Blockchain yourself?

Total trading profitability is limited by liquidity. Some extremely good professional traders have made the move into Blockchain trading already, and will be making millions in the space every year. And we’ve seen evidence here in New York that in 2018, a great many more fiat financial institutions will be entering the space as well. We believe that a product like ours in that space adds a great deal to the total ecosystem by demonstrating that the market is maturing, by fighting fraud, abuse, and improving the ecosystem’s credibility overall.

But Clairety isn’t just about the blockchain world. The projected revenue from our dollar denominated social media products has the potential to be in the hundreds of millions of dollars, maybe even more. And it also holds the potential to improve the online world in many ways that can’t be quantified. We like the idea of improving the world at least as much as we like turning a profit. Doing both has an irresistible appeal.

1.12. Most blockchain traders already have their own credible ‘sources’, so why do they need your data?

As we said, Our CSMF data is a tool for professional traders using models to trade. Whatever you think the blockchain trading world is today, in a year we think it’s going to look very different. The traditional finance world has finally discovered blockchain in a big way and this is a tool much like the ones that they use in other markets. The biggest players today may not find it much use. We believe that in a year, a great many of the biggest traders will, because they will be different traders.

Automation and ‘data driven trading’ has been on a long march through the institutions of the trading world for decades. Given the extreme technical savvy of the members of the blockchain ecosystem, we believe this market is going to leapfrog most of that effort. ‘Quant’ trading is coming. And when it does, our data is exactly what they’ll be hoping to find in the space.

We’ve been buying data like this to support our own trading models in the fiat trading world for years. One of our closest advisors has been selling data and systems in the financial space both to us and to other like us, for decades. We all see it the same way.

1.13. How credible is “Donald Trump’s Twitter”?

Sooner or later everyone asks us this. Whether you love him or hate him, more than any man in public office, Donald Trump has what anyone would call “a unique way with words”. When compared to other more traditional and carefully spoken politicians he scores in the lower end of the spectrum, but he’s not the lowest by any means. And there are millions and millions of people who will be scoring lower than him from outside politics.

All told I’d say he’s about where people would expect him to be. But his score changes every time he sends out a tweet, and he sends out a lot of them. To get the whole picture you’ll have to sign up for the free product, and see for yourself.

1.14. What about the score for my [least/most] favorite news source?

What struck us most distinctly was how closely all the media producers all scored to each other. They’re all bundled up in the same tight little group CNN, right beside FoxNews, beside the WSJ, beside the NYTimes. They have a high tweet rate too so they change order fairly frequently, but they’re all about the same as each other most of the time. What that tells us is that even though they all have different views, they are all responding to the same economic incentives in terms of how they editorialize their content.

The fact of the matter is that when incentives are considered, the people who have the most to gain from the success of our product will probably be the established news media. Right now, with all information being treated as having exactly equal value, someone can come along and write a bunch of totally unsupported opinion, gain a bunch of followers, and in short order be considered on the same level as the mainstream.

But when there is a number like ours out there describing the quality of content, those people who can produce higher quality content will probably be the ones who benefit most. The mainstream media has huge infrastructure and resources, so once they have an incentive to produce less biased higher quality news, I think they’ll be happy (maybe even relieved) to do so.

1.15. What are the risks of the project?

All kinds of possible risks are fully described in the whitepaper in the section “Risks”.

2. Market

2.1. What will you do to become leaders in your sphere and to keep your positions?

We have a very clear idea of the economic niche we’re looking to fill and the steps necessary to make us a the standard in our space. Our US Pending Patent provides us some protection for our methodology, and our Freemium distribution model will allow us to scale our user adoption very rapidly. Our Beta release, focused on the US “Mid-term” election on November 6, 2018 provides us a truly unique marketing opportunity, and we plan to use it to great effect. The ‘Fake News’ issue will very likely be boiling over by that point, so we believe the media attention we get will be extreme.

2.2. Google Facebook and Twitter are multi-billion dollar Corporations with advanced expertise in NLP. What makes you think they won’t just do something like this themselves and cut you out?

Well our US patent gives us some protection, but our real advantage is our independence. All of the major social media platforms have been coping with very credible accusations of bias in their judgement of ‘fake news’, and this has done major damage to their brands. In technical terms, they probably can do something ‘like’ what we do, but because it comes directly from them, it’s very likely that their users simply won’t believe them when they do.

Just like Thomas Edison figured out in 1894 with Underwriter’s Labs, It makes more business sense for them to partner with us than to do it themselves. Especially since our revenue does not come from the same source as theirs, and represent no competition to them whatsoever.

2.3. Don’t you think the social media companies will see you as moving into their territory?

We certainly hope not. That’s not how we see ourselves. We want to make things better for them not worse.

In fact, because we’re totally independent from them we can give them something they can’t get for themselves. When UL was founded in 1984, Thomas Edison was running General Electric and saw what a clear advantage it gave him to have a totally independent company rating his products. We can do as much for the social media companies and the broader media industry as UL ever did for the electric industry. By identifying ‘bad actors’ to the public, we can help to eliminate them, and improve the quality of media overall, social or otherwise.

There are other ways we can make things better for social media companies too, but we’d prefer to discuss those directly with them. We can give you this commitment though. We will NEVER take any payment of any kind directly from the social media companies or their subsidiaries. That isn’t just evasive talk. Our independence from them is our highest priority. It’s the only way we can be sure that we’re doing right by them and the public at large.

2.4. What makes you think you’ll be seen as an objective source?

The roots of this system were developed and proven effective in the financial markets; an environment that instantly and ruthlessly punishes anything except absolute and total objectivity. Beyond that, we believe our results will make it very clear. In our testing, we found that we have people who score both high and low on the political left and the political right.

Even more important, there were people on both ends of the spectrum who surprised us. People who we thought of as being quite far out on the tails of the political spectrum who scored comparatively well in our testing, and people we thought of as mostly middle of the road who scored poorly.

In data science, if everything turns out exactly the way you expect, that’s likely to be an indicator of a problem called confirmation bias. That’s a difficult thing to get a handle on so we worry about it.

But when we went back and looked at the twitter feeds of the people we thought were extreme, it always turned out that online at least, their posts were moderate and thoughtful, and the inverse was true for our surprise low scorers. So whatever our initial impressions of the person in question, the system was reading what they said and assessing it appropriately.

There’s something else too. If all we did was read the news and declare a story fake or real, how would we know? The only thing we’d have to compare it to is our own viewpoint and that viewpoint contains bias. This is the same mistake all the other ‘fake news’ solutions are making. Some, thought clearly not all, are just political opposition and are doing that very thing on purpose to promote political propaganda.

The only thing we compare a score to is everyone else’s score. In that regard our system is being ‘objective’ in the only way anything ever can be. It isn’t a reflection of our views, it’s an accurate reflection of everyone’s views. You might not agree with that, but agree or not, it’s objective.

2.5. Who else is doing something like this?

Rating agencies operate in a number of industries, with the longest running and in our opinion the most successful example being Underwriter’s Labs, which has been rating the safety and reliability of electrical equipment since 1894, and now operates in 106 countries and has thousands of employees.

Thomas Edison was running GE in 1894 and saw UL’s independent rating as a means of preserving the incentives necessary for consumer confidence,while reducing the threat of government regulation. He could just as easily have decided to produce his own reporting, crowding UL out of the market, but he determined that rather than expose himself to the overt conflict of interest, he would partner with UL instead.

Although we’re the first to attempt this in the social media space, it’s a well established economic niche.And with a decade of experience with the technology in the financial markets, we believe that both we and our technology are up to the challenge.

The Bond rating agencies are another example of a rating agency already well established in another industry. But the fact that they are paid by the people who sell the bonds they rate has hampered their independence, and has led to some fairly spectacular failures on their part, like the 2008 Mortgage crisis.

Though we are hoping for inevitable partnership with the major social media companies and are already beginning a dialog with them to that end, we don’t intend to take any money from them. In this way we’ll be more like UL than the Bond Rating agencies, and be in a position to preserve our independence, while the social media companies will have the ability to obtain data from us which will help them maintain their own revenue through their own channels as viewer patterns of the media content evolve.

2.6. Who are your most important partners?

At this stage we’re still in development. But several of the editors at the Wall Street Journa have agreed to participate in our Beta and to help us design our products to meet the needs that they have as a provider of media content. Credibility means everything to the WSJ, so we’re very pleased to be engaged with them.

Inevitably we’ll be looking to establish partnerships with the Social Media platforms, and we’ve already begun those conversations. These are private conversations so we can’t reveal too many details, but we’ve been led to believe that if we can meet certain benchmarks for user adoption, there will be an opportunity for the kind of discussions we’re hoping for. A partnership with one of the large social media providers would cement our position as the leader in this space.

Since the social media platforms have an obvious conflict of interest in trying to be both ‘an open platform for user generated content’ and the ‘speech police’ at the same time, we believe that a product like ours from an independent partner will represent a way for them to return to their core business. There are many examples of this in other industries.

3. Product

3.1. Have you analyzed the market? Are you sure your project will be in high demand?

Our products address the concept of ‘fake news’, bias, and political polarization on social media, which is one of the largest cultural issues of the last 50 years. To say that the demand for our product is unprecedented, probably understates the issue. Hundreds of millions of people are discussing this topic every single day. There have been riots in the US caused by it.

Treating the ‘marketplace of ideas’ as an actual marketplace where the readers decide the real value of information being offered by filtering away what they don’t want to see, represents a totally unique solution to this problem that empowers the consumers to make the ultimate decision of what is real and fake by denying clicks to low value content.

The total media market is well documented from a broad number of sources as representing hundreds of billions in revenue per year, and we believe our products monetize that very effectively.

3.2. In what way is your platform unique?

Our platform analyses ‘fake news’ in the only way that can ever be truly ‘objective’. Unlike 100% of the competitive efforts attempting to address ‘fake news’, at no point do we ever compare our results to our own views of what is real or fake. The only comparison we ever make is the views of a contributor, to the views of everyone else.

All other efforts to address ‘fake news’ have been people trying to position themselves as the arbiters of what is true and what isn’t. They ‘read the news’ (either manually or with an AI) and then publish what they think is ‘the truth’.

We don’t do that. We read everything from the top rated media sources all the way down to the person who rarely posts on Facebook. Our ‘truth’ is the consensus of what all those people say it is, not what we say. Because we treat ‘true of fake’ as a degree rather than a black or white issue, we can reflect all the complicated nuance that is a normal and natural part of life. We make online conversations more like ‘real life’ by incorporating a concept that we all use every day - credibility.

We also represent the only large scale effort to market a product to each of the 500 million users of Social Media. Our market is therefore much larger than any other proposed solution. We don’t create content, or sell content, all we do is tell people what is safe, and what is reliable.

3.3. What are your current achievements?

We have a US Pending Patent, and currently have a working prototype analyzing Twitter data for our primary Crypto-Trading product. At the moment it’s examining only a small subset of the amount of data we’ll need for a ‘full production’ product but we still find the result compelling enough to release it to token holders at the end of our TGE. We also have products designed for the retail space, the B2B space for advertisers, and Premium retail products for users, corporations, for parents, and for corporate HR departments.

We have a clear development plan and schedule which shows our Beta release sometime after Q3, 2018, as far ahead of the US Election in November as we can manage.

Our marketing plan for early user adoption is in place, and given all the attention that ‘fake news’ is receiving, we believe it’s going to produce truly explosive results.

3.4. What about the price for your product?

Our basic retail product will be totally free to users which we expect will foster early user adoption. Registered users will then have the option of a monthly subscription for premium services. Basic service provides access to the credibility scores of others, and the ability to sort and filter low value content from user’s social media experience while the premium tools will be designed to assist those interested in increasing or maintaining their own online credibility.

3.5. Do you have any premium functions?

Free retail users of our browser module will have the option of making use of our premium suite of tools for a low monthly subscription fee. Our Premium product explicitly identifies bots, lets you track credibility history over time, and has a suite of tools designed to let you understand the changing value of social media content on a real time basis. If you’re interested in who to believe and who to ignore and why, our Premium product gives you all you need to know to make an informed decision.

It also provides you with the tools to manage your own credibility in the social media space with things like retweet warnings and coaching tools. This is critical for journalists, politicians, people who work in the Media and PR space, and those who work with and follow them online. In some industries like finance, credibility is already an absolutely critical issue. But as we deploy our tools for employer HR departments, it will become much more critical to a great many others.

3.6. What have you done by this time?

At present Clairety has a working prototype which is reading Twitter content and rating and ranking the results. The proceeds of the token sale will be used to build this prototype into a scalable version, to complete the various user interfaces, and to implement the data distribution on a “Web- Scale.” Other proceeds will be used to hire the necessary development, marketing and operation staff so that this service can be delivered and supported on a wide scale.

3.7. When will the full version of the product be ready?

The ‘full retail’ version of the software will not be ready until some time after the third quarter of 2018. But since the CSMF (crypto-trading) data represents a smaller dataset, an ‘alpha’ version of that dataset for use by professional quantitative traders in the Crypto-world will be available immediately upon the completion of the TGE. This is an ‘alpha’ release so the data will be meaningfully improved by the time our retail product is ready for release. But we believe there is a high enough information content in the data to justify its release to our supporters immediately, even in its present state.

3.8. What if I want to know if a specific news story is ‘Fake’?

Fake according to who? Very little media content is totally fictional. Most ‘fake news’ accusations are actually about the gap between the viewpoint of the publisher and the viewpoint of the reader. Far left people call right leaning news ‘fake’ and far right people call left leaning news ‘fake’. What we do is map the degree of ‘bias’ in either direction, so we give you an idea of how many people probably think a news story is fake overall.

To borrow a term from data science, the degree of bias in an author’s outlook is fairly ‘stable’, which means it’s persistent over time. No one in media writes a story popular with Rachel Maddow fans on Monday and another that’s popular with Alex Jones fans on Tuesday. Because it’s closely tied with their psychology and the values they hold most dear, people generally lean one way or another. What we give you is a statistic which tells you how hard they’re leaning now, not which direction they’re leaning.

It also came as a happy surprise to us that bots and spam accounts that are designed to ‘make you think’ a certain way, lean the hardest of all. In one sense this is what we expected, but we were surprised to see how obvious it was in our results.

3.9. How do you know something is a Bot?

For all their attention in the social media space, most bots aren’t very sophisticated. Most of them are fairly simple programs which repeat stories in multiple mutually exclusive media bubbles in order to garner more clicks. Some don’t even go that far and only exist to boost the ‘follower’ or friend count of a specific social media user, giving an illusion of greater popularity.

Since our system has no biases and is reading everything, we aren’t limited by a bubble. So it’s fairly easy for us to tell who is producing original content and who isn’t.

3.10. What if I don’t want to be scored by you?

We’re interested in improving the quality of the public ‘marketplace of ideas’. If you don’t want to be rated by us, then don’t make your comments publicly. Everyone is entitled to their opinion on everything and we respect that absolutely, whatever the opinion is. But if you make your comment publicly, then the public is entitled to review them and draw their own conclusions about you based on what you say. We’re no different.

4. Work of AI

4.1. How does it ‘actually’ work?

It’s no joke. We have an artificial intelligence system that reads public social media comments and ranks the author based on a US patent pending algorithm for determining ‘credibility’. It’s not our view of what’s ‘true’, it’s a reflection of what everyone views as ‘true’. A system with the same basic logic has been profitably running for years in the financial markets.

Rather than declaring ourselves the masters of what is or isn’t ‘fake news’, we tell you about the average credibility of the people reporting the news to you, and let you decide what you think is ‘fake’. In effect we are distributing the decision making about fake news to each and every social media user, all by letting you know about the reputation of the person making the statement.

4.2. How does AI estimate the value of information?

Our AI does not skew its view of information the way a human would. Having no internal views of its own, it looks only at how the arguments are offered, the kind and nature of the supporting evidence, and as its single point of comparison, uses the viewpoints of the other users of social media. It does this through a detailed syntactic analysis of syllogisms and a combination of categorical and range based testing. We believe that this is the ‘only’ way that an AI can be truly objective in its assessments.

4.3. How does it work internally?

Our AI reads individual messages in the form of tweets, comments, posts, and other social media content, and uses our US patent pending model for determining the individual message credibility. One useful analogy for this process is to think of it as a description of the practical utility of the information being offered. By comparing each message to a series of vectors for the examination of commonly used rhetorical syllogisms, and taking into account, past, present or future tense, active vs. passive voice, whether a statement is predominantly objective or subjective, the nature of the statement subject and examining its context within the conversation, our AI builds an aggregate score for that message which is the AIs prediction of the message veracity.

5. Security

5.1. How can I be sure that you are not a scam?

The executives at Clairety have a long and established track record in the Financial services industry and have profitably managed hundreds of millions of dollars at some of the premier financial institutions on the planet. Their complete work histories are available to all via linkedIn in their bios. They are no ‘unknowns’ in the New York financial community. Clairety’s operations aren’t being built in some obscure location but in New York city, arguably one of the most heavily and carefully regulated financial jurisdictions on the planet, and have been in place for nearly a year - before the ICO boom. The total raise is also capped at a relatively low number that will be sufficient to execute the stated business plan. All of these facts should be looked upon as adding legitimacy to the plan.

5.2. How can you protect your data and product?

To protect the integrity of our product for our customers, we will be encrypting data access via the ETH protocol so that users can be assured that the data they embed in their analysis is the result of our system output and has not been tampered with by hackers. In the interest of full and open disclosure, we will be using a public blockchain for the storage of the encryption and the token will serve as the method of encryption.

5.3. Do you plan to use any KYC verification?

Yes, we respect local laws and use KYC for investors’ verification.

5.4. Can it be hacked?

The short answer is that since we’re using split-key encryption to protect our data, we don’t think so no. We confess that our data is very likely to be a potential target, but that’s the whole point of including a blockchain specific access methodology. If you trust ETH, then you should be able to trust our data integrity.

5.5. Will other people know I’m using it?

Nope. And that goes for all our products. Only you and we will ever know where you set your filters, when you use our system or if you’re using it at all. We won’t even tell the Social Mediasocial media providers. We’re still going to read your public comments whether you sign up with us or not. But if you want to ‘opt out’ of that, then make all your comments in private.

5.6. What if the person’s social media content is ‘private’?

We don’t read ‘private’ social media comments and never will.

6. ICO

6.1. Will you have a pre-sale?

Clairety’s token pre-sale is designed with a clear and transparent structure and will be conducted over the course of eight weeks as a private placement of securities under the US Securities Act of 1933 (the “Act”) and Regulations D and S promulgated thereunder, as more particularly described in the section “Legal & Disclaimers.”

6.2. How are you planning to use your funds?

This event is expected to provide the company with the budgetary needs for approximately 30 months of runway with a full development, marketing, sales, and management effort. Since we believe this will be enough time to demonstrate the viability of our business approach, we are capping our raise at its stated level.

6.3. How did you distinguish your budget?

We believe that our budget is reflective of the costs associated with working in our location, and aligned in accordance to our milestone and business development plan. We also believe that a successful TGE raise will allow us to not only successfully complete the software development, but also increase the speed at which the solution will be available to meet the needs in our secondary and tertiary markets.

6.4. What is your roadmap?

You can get acquaint with our roadmap in the whitepaper.

6.5. What happens if you collect more than you need?

Our token issuance has a hard cap. We intend to close the sale as soon as we reach this threshold. Owing to the variable rate at which we expect participation from salespeople and bounty participants, we have over-allocated our tokens in order to provide for a maximum possible payout to these parties. We do not expect to use all of these tokens and those that remain at the close of the sale will be burnt.

6.6. How much money do you want to raise during ICO? What is your hard and soft cap?

We’ve set a minimum of 2 million US and a Maximum of 11 Million. That will give us enough cash to pay the costs of our TGE and fund our development and operation for about 30 months. We feel this will be enough to demonstrate the efficacy of our products, establish ourselves in the marketplace, and provide enough revenue and market share to position us for our next stage of growth.

6.7. Can you raise your business even with a smaller budget which you plan?

We probably could, but it would take much longer and we’d miss the enormous opportunity represented by the US election. We originally planned to build the company with 2 traditional VC rounds, one for development and another for marketing and promotion. But raising money in the crypto space allows us to combine those two efforts and get to a full marketing effort much sooner. The timing opportunity represented by being the only ‘truly objective’ solution to fake news, is simply too great to pass up.

People are literally rioting in the streets in the US over this issue, and by the election who knows where it will be. Getting them a real solution that works for everyone as soon as possible, is not a trivial issue.

6.8. Are you going to use bounty program? What are its terms?

Yes, you can find information on the website.

7. Token

7.1. What is a Clairety Token?

Clairety’s RELY tokens are based on the Ethereum protocol and are ERC20 compliant. This is expected to facilitate the listing of RELY tokens on cryptocurrency exchanges (subject to applicable holding periods – see “Legal & Disclaimers” section of our Whitepaper) and subject to compliance with relevant securities laws, tokens can be bought and sold on existing cryptocurrency exchanges and stored in Ethereum-compatible wallets.

The Reliance tokens are solely a means of payment for Clairety’s services, and do not and will not at any time represent an equity interest or other claim on the company’s assets. The Reliance tokens will not have any voting or other rights relating to the management of the company.

7.2. How can I buy your token?

You can buy Rely tokens on our website. Currencies which are accepted during Token Sale are BTC, ETH, LTC, BCH, USDT, USD, EUR

7.3. Can I buy a fraction of your token?

No. The token price was set at a low value nominal value to eliminate the need for this.

7.4. When will your tokens be distributed?

Immediately after the close of our ICO.

7.5. Will your token be listed on any exchanges?

Yes. Conversations with Exchanges are ongoing, and we will announce the listings when they are confirmed.

7.6. What is the total supply of RELY tokens? Will there be an additional issue of tokens?

At present we plan no additional issue of tokens after the close of the ICO.

7.7. What is the minimum purchase during pre-sale/ ICO?

$5,000

8. Legacy

8.1. Where is your company registered? Is your activity legal?

Clairety AI Ltd, a company limited by shares is incorporated under the laws of the British Virgin Islands. We have an operating company which is a Delaware C corporation, based in the US, with principle operations in New York City.

8.2. What is the address of your office?

Our address in New York City is currently 60 East 9th Street, New York, New York but since we plan a great deal of hiring, we plan to move to a larger, more flexible space at 25 Broadway, as soon as possible, likely before the end of the TGE.

8.3. What countries do you plan to embrace? Will there be any restrictions?

Our offering is regulated under US law, specifically US SEC regulation S and regulation D. This restricts our offering in the US to investors who can demonstrate ‘accredited’ status, and prohibits us from engaging in any activity in countries currently under US economic embargo, specifically Belarus, Cuba, Eritrea, Iran, North Korea, Syria, and Venezuela.

8.4. Do you think social media is going to be regulated?

We hope not. We prefer free and open, especially when it comes to online speech. But there is reason to suspect it might be.

In June 2017, The US Supreme Court ruled on a case called Packingham v. North Carolina where Justice Kennedy described social media as “a part of the public square”. That had no specific force of law, but it immediately inspired several lawsuits trying to restrict the government and social media companies from ‘banning’ individuals. That’s a long way from banning speech, but it’s along that road. And we can see how it might get there from here.

We think it’s a bad idea to let the government get further involved in the restriction of speech, and we think it’s an even worse business idea for the social media platforms to take this role on themselves. But we have a way for people to get the protection they feel they need from online harassment and other nuisances, without resorting to more regulation of what people say.

To us, more speech is the solution to bad speech, but only if people can tell the difference between good and bad speech. We view the right to speak your opinion as an individual right. But we view the right to ignore an individual’s opinion as just as important.

Not all ideas are equal. And we aim to give people the information they need to be able to tell the difference between what’s worth their time and what isn’t.

9. Team

9.1. Who are your team members?

For complete bios of Executive managers, please see our whitepaper or website.

9.2. Who are your advisors?

For a complete advisor list please see our website or whitepaper.

We're Hiring - view our list of available positions

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We're located in New York City