Partnerships, Customers, and M&As

If a Mergers and Acquisitions (M&A) event was to occur, what would happen to token holders?

In the case of an M&A event or strategic investment by one of our customers, or outside companies or investors, the VXV utility token will be the most valuable asset they acquire related to this company. This is if we allow any M&A in the first place of course. This is how we have financially engineered, structured and positioned Vectorspace AI.

VXV will be transacted in terms of all buyouts before the close of any M&A event, particularly an acquisition. We will allow anything else to happen but for all VXV to be transacted before a close for the following reasons:

  1. This is critical for the current structure and design of the revenue model to work (which we have put a lot of thought into).

  2. Critical for the core team that has been with the company for the last 18 years through thick and thin.

  3. Critical for other investors

  4. Critical for all stakeholders

Considering the potential of an acquisition by S&P Global or a similar suitor, what is stopping the acquirer from scalping out the tech and moving on with it, leaving the VXV token useless? In other words, token necessity can create frictions on the corporate side for potential clients (limited liquidity, custody issues, etc.).

This is 100% impossible. The VXV token is integrated into the entire process of data provenance. There is no excising the VXV token from the model.

If the Vectorspace AI team is focused on interaction and cooperation with multi-million-dollar companies, then why gather ordinary crypto investors? What will the main application of these products be for these companies or for investors?

We are not focused on interactions with multi-million-dollar companies, rather billion- and trillion-dollar companies. This also includes trader bases interested in trading VXV. The definition of IR (Investor relations) answers this as well. Both companies and investors have access to datasets which are used to generate Smart Baskets.

Will VXV still be needed and remain valuable if the traditional market gets hit with a bear market?

We are hedged in more ways than one. We are offering, e.g.:

  1. Short Smart Baskets of traditional where some will be hedged with options or long on the SPYs.

  2. We will have an entire offering of Long Smart Baskets of crypto.

  3. Long crypto, short traditional hybrid Smart Baskets.

  4. Datasets are customized to whatever the client wants.

  5. We will be additionally hedged by initially offering datasets in the Life Science industry.

  6. Any other industry.

It Is good to be in AI.

How will VXV prioritize data access among users, keeping in mind that alpha could be fully exploited by the first mover thus rendering the data moot?

There are unlimited ways a dataset can be created and unlimited ways one can construct a Smart Basket from a particular dataset. We have been in the business of datasets for a very long time. This means that other companies are attracted to what we do because it gives them an edge and a way to attract more customers to their platforms. They rely on us to do this.

Signal to noise extraction especially in NLP/NLU is about the variety of data sources, the data engineering pipeline and how you calculate scores for feature attributes within vectors in addition to many different ways you can calculate distance between vectors.

Most alpha is extracted from the data engineering pipeline in combination with trade execution methods. Data engineers know exactly how to “create clusters” and do all the different kinds of things to extract value from a dataset.

How many datasets is Vectorspace AI able to provide?

Billions. How many events, topics or categories are there in the world? Multiply that figure by how many ‘contexts’ exist in the world. Now, multiply that figure by how many ‘row types’ you can think of, e.g., cryptos, stocks, genes, proteins, chemicals, antiviral compounds, diseases, therapeutics, phytochemicals, plant compounds, etc.

Who are the competitors of Vectorspace AI?

In the crypto market, there are none. In the traditional, our closest competitors are Motif Investing (however, they do it like Pandora does music, manually), Palantir, Blackrock, Rencap, and Google.

We do not have competitors yet that provide NLU correlation matrix datasets used to generate clusters from unsupervised data using vector space methods.

What places Vectorspace AI ahead of its competitors?

  • First to market;

  • Algorithmic calculations;

  • Strategy wrapped around technology;

  • Knowledge expertise in the public markets;

  • Decades of experience in data science (previously known as data/knowledge/text mining and epigraphy) and data engineering.

The VXV approach for those platforms is unique in the industry for dataset exposure in several ways. These trade secrets also double as our moats and barrier to entry along with a hedge.

There will be tons of competition in the future but the dataset industry is so large that there are tons of different dataset types. Our datasets are advanced and focus on NLU which is one of the most valuable niches. We will then be expanding into datasets of all types including the ones you find on The most important thing to keep in mind is that every industry now benefits from data, ML/AI/NLP/NLU. We will be moving into every industry vertical possible.

Who are Vectorspace AI’s current partners/collaborators?

CERN – European Organization for Nuclear Research: It is an academic collaboration based on datasets related to particle physics. We intend to apply what we learn in that area in an inter-disciplinary way to biosciences datasets. CERN’s Website:

CloudQuant: CloudQuant helps its customers around the world to boost their investment performance by providing valuable Alternative Data. Our partnership with CloudQuant aims to connect Vectorspace AI to more than 400 thousand investors. We’re working together to provide their customers with novel datasets that reveal hidden relationships between global equity products. “FinTech Innovators Partner to Turn NLP into Dollars”

Elastic: Elastic utilizes our datasets to showcase what can be done with the Elastic stack. “Generating and visualizing alpha with Vectorspace AI datasets and Canvas”

LCX – The Liechtenstein Cryptoassets Exchange: The goal of the partnership is to build Smart Baskets for LCX Terminal to enable customized and unique trading opportunities across multiple cryptocurrencies across multiple exchanges, such as Liquid, Kraken, Coinbase Pro, Kucoin or Okex. “Partnering with Vectorspace AI to leverage Artificial Intelligence for crypto trading”

Microsoft: “COVID-19 Drug Repurposing Datasets Now Available in Collaboration with Vectorspace AI, Amazon & Microsoft”–microsoft-301030507.html

Neudata: Neudata is a company dedicated to finding alpha-generating alternative data for investment professionals. They’re connecting data vendors like Vectorspace AI to hedge funds, investment firms, family offices and retail investors. In March 2021 we’re going to participate in their “Getting Started in Alternative Data” event, where we’ll present our services to investors worldwide. Neudata’s Website:

S&P Global: S&P Global is the world’s largest financial information provider and they are looking to companies Vectorspace AI to transform their data, raw crude oil, into datasets. Its primary areas of business are financial information and analytics. It is the parent company of S&P Global Ratings, S&P Global Market Intelligence, and S&P Global Platts, CRISIL, and is the majority owner of the S&P Dow Jones Indices joint venture. We are working with S&P Global to distribute our Smart Basket signals in addition to our datasets. S&P Global’s Website:

Trustology: It is a UK based FinTech company focused on providing high-end, insured custodial wallet solutions to secure and manage crypto assets in real-time, today announced its partnership with Vectorspace AI to make it safer, faster and easier for token purchasers to send, receive and hold its VXV tokens using TrustVault. “Trustology Partners with Crypto Token Issuer Vectorspace AI” Some of the potential partnerships/collaborations that have been in the works during the last months: S&P Global, Neudata, CloudQuant, Microsoft, Bloomberg, GNC.

How do the collaborations with Microsoft, and S&P Global work?

For Microsoft, it is different than with Bloomberg or S&P Global. Microsoft has a different customer base and culture. They want to group us with other companies which is based on their timing based on their life sciences focus. Microsoft will be a general focus and has an investment arm that the team will be pursuing as well. PR will likely be released by them and they will produce case studies.

What is the current status on the pending Public Relations (PR) with Microsoft, S&P Global etc.?

They are in progress and that is all we can say at this time.

Would Ocean Protocol not be an interesting partner for Vectorspace AI? Ocean offers data marketplaces, e.g., for healthcare (e.g., they collaborate with Roche). Vectorspace AI could thus either become a vendor of datasets on the ocean marketplace, or acquire proprietary data from other vendors for their datasets.

Yes, they would be but time and resources are currently focused on revenue generation at this time.

Decentralized Finance (DeFi) is the big hype currently in the blockchain space. Could we see DeFi protocols using Vectorspace AI datasets and Smart Baskets for financial products in the future?