Financials

What is the revenue model?

We offer a paid subscription where we have dozens of different tiered levels of service offerings, similar to Netflix, mixed with Amazon, but for datasets. We offer $0.99c updates per dataset per data source per minute per context which drives the revenue model.

Customers can pay in fiat or crypto (BTC/ETH), then 50% of the subscription value will be bought in VXV on the open market that will be placed in the customer’s wallet and assigned to a number of services (dataset, Smart Baskets etc.). As they use the services, the VXV is used up. For instance, generating Smart Baskets from the datasets to find hidden correlations using the Vectorspace AI algorithms uses up the VXV. They are then locked up for a period of time. This period of time has yet to be determined.

The other 50% will work as a “fee” that translates to revenue. Revenue will be used to build the company which increases its valuation and impact in the world. We are sharing the fee. It is like a revenue share with the public. Please note that the percentage of the “fee” is adjustable, so it could be changed in the future.

Some might sign up for datasets and some sign up for datasets that have pre-generated Smart Baskets they can immediately trade. Datasets -> clusters -> Smart Baskets of all kinds.

Imagine company A pays Vectorspace AI 100k$ per month for certain datasets that are updated at a certain frequency.

Behind the scenes, 50% of that flows to Vectorspace AI to pay for operating costs and expansion. It is gross revenue.

The other 50% is used to set limited buy orders on the open market for VXV at certain price levels.

This creates liquidity pools at these price levels. If someone sells, these orders can get triggered. If these limited buy orders are triggered, 50% goes to Vectorspace AI, and 50% to a customer wallet. This customer wallet is controlled by Vectorspace AI, through our partner Trustology. By having the customer wallet, the circulating supply of VXV is reduced.

This process can change as needed.

A revenue projection can be seen on page 14 of our deck: https://vectorspace.ai/assets/VXV_Deck_External.pdf

Why is the token valuable?

The value created by our community which includes the core team, the outside team and contributing members of our global community, translates directly into the value of the VXV utility token and as a global public trading vehicle.

VXV utility tokens do not function like a security or currency and share only minor similarities with e.g., Google Cloud credits, AWS credits, or WeWork utility credits due to VXV doubling as a public trading vehicle in a global public marketplace.

Our top-tier proprietary datasets and algorithms deployed in the financial markets that enable asset management groups, hedge funds and institutions to generate and capture alpha, can only be used by a limited number of customers. In this business, it is a common requirement from our top-tier customers to prevent saturating the market. It is like giving everybody the exact same weapons. This means the value of VXV is controlled by our customers, who will also be taking long term positions in VXV. It only makes sense and it is out of our control.

In order to serve our customers properly, we have carved out a public marketplace which allows them to acquire blocks of VXV and out-bid other customers if they would like to ‘corner the market’ on particular proprietary datasets.

The VXV utility token credit also doubles as a global public trading vehicle available to be transacted, acquired, bought and sold between anyone, including speculators, in the global public crypto markets via exchanges. This means a farmer in Kenya or a villager in Borneo can acquire VXV to access a dataset one minute and resell VXV to a trillion-dollar asset management company the next minute in exchange for “JPM coin” for example. This is completely out of our control.

As mentioned in question 30, we have plans on enabling machines (data engineering pipelines onsite at customer locations) to transact VXV with one another for the purpose of ‘minimizing loss’ which is at the core of effective ML/AI.

What is Vectorspace AI’s total addressable market?

Billions. This is because we are a data company with a focus on revenue generating customers, which are trillion-dollar asset management companies, funds and other financial institutions. Our job is to help them make money by providing them with an edge. This happens based on our product, NLP/NLU on-demand datasets that are updated every minute and based on any data they choose.

This includes transacting dataset updates along with our Data Pipeline Provenance (DPP) hash which controls data lineage (a.k.a. data provenance). Knowing where your data comes from and knowing how reliable it is, is extremely important to financial institutions that rely on it to make billion-dollar decisions every day. We give financial institutions an edge that to them, is worth billions. Here we are talking about one example in the finance industry, but our platform has applications in almost all industry verticals.

What is the upper limit of dataset updates/combinations Vectorspace AI can provide?

We currently charge $0.99c per dataset per update. We have an infinite combination of dataset permutations, combinations, and customizations. Our data engineering pipelines are being prepared to scale toward updating deltas per dataset permutations which would mean anytime a data point changes it gets reflected in the dataset. This level of customization is available today on a case-by-case basis.

There are different On-Demand Price Tiers for Vectorspace AI, ranging from free to institutional. How has the feedback been from potential clients using the free tier?

The feedback has been great so far, but we are not going to be issuing numbers at this time. We are strategically going to be releasing the Alpha Week article and communication by S&P global, followed by a presentation of the numbers.

What is the current revenue status?

We are revenue positive, i.e., we are already doing business.

What level of user adoption can be expected by the end of 2021?

We expect it to be high.

Is there any indication of when or at what stage buybacks are to be expected?

Our objective is not to move tokens from the main wallet. The objective is to acquire as much VXV as we can. We will be doing this with buybacks. The ability to do so is driven by revenue generation. We will see large buybacks occur when there is consequential revenue.

In the case of someone paying $100k, is it all automated in the sense that $50k will automatically go onto the exchange and buy $50k worth of VXV?

Yes, and that is where it gets interesting, we can use a few algorithms to monitor sensitivity on the ask side, sell pressure, and even a few overbought or oversold indicators, e.g., the 10 day Moving Average Convergence Divergence indicator (MACD), while placing limit orders to support new legs up.

We would essentially be serving as our own Market Maker (MM) and an Ax, with a fiduciary responsibility to maintain an orderly market, which is the primary mandate for a MM, for the sake of our customers and market participants.

Will it be possible to resell subscriptions?

Yes, we expect some customers will want to resell their VXV subscriptions and wallets at higher valuations to any bidder.

We also anticipate experts and specialists to come in, build powerful and unique datasets, subscribe to them and lease them out to other funds they consult with.

How will the subscriptions change value if it is worth $0,99c per minute?

The value of a dataset is based on how much the customer from an industry such as life sciences or the financial markets, values the ‘signal’ that the dataset is able to produce. For a hedge fund, this ‘signal’ is represented as ‘alpha’. If you have a dataset that is generating alpha, that is how much the dataset is worth at the time.

The value of a dataset can go up or down over time based on the change in the value of the signal it generates. This is why most datasets will appreciate in value over time especially if triangulated and combined with new and existing datasets. All of this supercharges AI and ML systems in addition to being their ‘gasoline’.

Why did the token value decrease so much in the end of 2019?

There was a small crypto hedge fund that held a number of positions in cryptos and ours was one of them. They blew up and ran into a few regulatory issues. They were forced to liquidate most of their holdings across the board so they could spin their fund down and likely start another. We chose to not allow them to sell into any significant news announcements.

Does VXV keep track of relationships with American Depositary Receipts (ADRs) or only with native U.S. securities?

We currently operate on native U.S. securities and markets. ADRs do not move much historically and are not as liquid as normal trading vehicles. This is a reason for why we do not include them. ADRs trade a bit differently and with less volatility. Our relationship with S&P Global allows us to operate on all global indices.