At Nomics, one of the things we don't talk about very often but something that's been really popular among our enterprise customers are our consultative or concierge data services. It's something that's a lot of fun because it allows us to partner at a deeper level with institutional investors, family offices, hedge funds, private investment offices, prop [00:00:30] shops, et cetera. It allows us to get to know a lot more about how these organizations use data, how they think about data, and how data is integrated with their trading strategy. Whether it's active strategy, and maybe they're running a real time trading environment or it's more of a passive strategy and they're looking for analysis on historical data sets for the purpose of [00:01:00] back testing and things like that.

But our concierge data services are really for organizations that make heavy use of crypto asset data. They either don't have an in-house development staff that can build out arrays of machines or the infrastructure necessary to run [00:01:30] pretty complex trading operations. That's fine. There's a lot of really brilliant investors and big data people at these places that are really great at what they do but they don't necessarily have a background in software development or they're too busy making money for their fun to set up some of this infrastructure at least to take the first pass [00:02:00] at some of this infrastructure.

They either don't have the in-house engineering resources or the people that could do this in the organization are too busy executing against strategies that they know work, and that they know make money and they come to us because they have a hypothesis around some things that might work, and they want to test a strategy. In most cases [00:02:30] when these folks come to us to have custom work done, to have concierge data services done or created, we're able to charge them a lot less than it would cost them to build it themselves from scratch even paying existing employees, or to farm this out because we're working with data and cryptocurrency data all day long, really. So, we have a lot [00:03:00] of the building blocks in place already to do this. We're usually not starting from scratch, we're usually not testing different ways to store this data or to ingest new data sources that they might need. We have a lot of these ingestion pipelines already in place if they need a strategy that scales across multiple machines, we have that infrastructure in place already.

I should note that, [00:03:30] to get started, it's usually again, less money than hiring someone to do this from scratch. But these services do start at 30 grand, for anyone I think, who has a fund of the size that would need these services, this usually isn't a problem at all, especially if you're a $20 million plus fund and [00:04:00] you're winning, and you have a hypothesis of what might work. This is really a drop in the bucket and certainly below market, well below market.

In fact, often we're able to charge sometimes, less than other firms might charge for just out of the box products that are already created. A little bit about [00:04:30] how we go about engaging with folks here. I think it's worth noting that at the end of the day, we are product company and we're makers that prefer to spend our time solving problems rather than navigating complex sales cycles. I think it's important to know up front when we're working with folks if they are going to need a lot of back and forth on the phone, if [00:05:00] they have in house legal counsel or there's going to be a lot of commercial contract negotiations, that's good to know up front, because we will build that in to the price.

What kind of services do we offer? Well, it really runs the gamut. Again, because we take a consultative approach, we like to start out with what [00:05:30] folks generally need and what problems they're looking to solve. Our services are not products that we're just labeling as services. It really is around custom services. Sometimes people want to know every last feature that comes with our services and that's not really the nature of services work. We can jump on the phone and describe what's possible, but I think these engagements tend [00:06:00] to work better when prospective customers have a really good sense of what they're looking to accomplish, what their needs are. They don't need to know what features we have available, but they do need to have a good understanding of what they're solving for, and the outcome that they're looking for. We'll figure out how to get there, but they need to know the outcome they're looking for.

But there are a few buckets that our services [00:06:30] fall into. The first is around custom pricing methodologies. Sometimes hedge funds, index funds have a formal methodology or at least they would like to have a formal methodology around how they price assets. They don't just want to go to CoinMarketCap or go to nomics.com and just get the price. That's not going to really hold water [00:07:00] with their investment committee. They need to have a rigorous methodology around how they report net asset values either of an index or to LPs in their fund. That's something we can help out with.

Sometimes we find out that these funds want to price their nav according to prices [00:07:30] on certain exchanges, and not just certain exchanges, but certain trading pairs on certain exchanges. So they don't just want all trading pairs that include Bitcoin to be included in the bitcoin price. They want to use certain trading pairs on certain exchanges to derive that price on a volume weighted basis or on some other basis actually.

We can do that. If they say, "Hey, we want to price these assets [00:08:00] every month and we want to price them according to prices on Coinbase pro and Gemini and Bittreks, and maybe Poloniex and a few other reputable U.S exchanges. They only want to price their assets that have ... They only want to price assets where one part of the trading pair is either in [00:08:30] Bitcoin in Ethereum, in fiat currencies, or in some kind of reputable stable coin for example like USDC or something like that. We can do that. Often they want to price portfolios at the end of the day and they want to price them at the end of the day in a given time zone. They want their end of day price to be in Pacific Standard Time, or [00:09:00] they want it to be in Eastern Standard Time, wherever their fund is located.

That's something we can do. We can work this out. There's often lots of nuance to it and custom things that go into this based on what they've written up in their methodology. I think it's good to have a rigorous pricing methodology. I think, often fund administrators are not [00:09:30] the best at doing this. But if you are a fund administrator, and you'd like to work with us on this, we're always here to talk, and we can just explore some ideas here.

The second frequent bucket that things fall into are extremely low latency trade data, or order book snapshot data. If you want data from [00:10:00] a number of exchanges and you just want a straight socket through to where you're at and you want everything through one combined socket. You also want gapless historical raw trade data, we can do that or normalized data we can do that. We [00:10:30] are able to do things like stand up 20 machines that are ingesting data in parallel order book data or trade data from multiple exchanges.

Often when it comes to order book snapshots, there's rate limits, but if you stand up an array of machines, you can ingest data in parallel [00:11:00] and get around rate limits. We can do that and then stitch the data together in real time and give you extremely low latency data. But, this is pretty hardcore work. Often, it behooves you to co-locate with where our machines are located. In the same Amazon Web Services data centers that we're in.

[00:11:30] That's another kind of thing that we do. I think that's pretty good for arbitrage strategies, for strategies that require very low latency data. I think this is particularly helpful when it comes to order book data. The third kind of thing that we do is white label market data APIs. [00:12:00] We are able to, basically through our exchange integration program, if you stand up like two endpoints, two or three private endpoints to us, we can get data, very primitive raw data from your exchange in the most granular and primitive form possible.

From those handful two to three endpoints, we can stand [00:12:30] up an entire white label market data API for your exchange. This is a service that we offer to exchanges. If you just send us a raw feed of what's happening on your exchange from that, we can stand up dozens of endpoints. Endpoints for various candle sizes, for all-time highs on different markets, order book stuff, web socket stuff. [00:13:00] It's pretty fantastic. Generally, we found that it takes an engineer at an exchange about a day of work to stand up and never more than a day, sometimes three or four hours to stand up a handful of endpoints that give us very primitive data around what's happening on your exchange. And then from that we can run essentially data.yourexchange.com. Or API.yourexchange.com. And ensure that market makers and people that can bring a lot of liquidity to your exchange or [00:13:30] platform have access to the data that they need to really participate with your system and your trading environment or your exchange.

This is something we really enjoy doing. It's a lot of fun. We not only provide you with a few dozen endpoints based on a couple primitive endpoints that you send to us, we'll also create your documentation [00:14:00] and we'll support your API. It's all done in a white label fashion where no one knows that we're doing this.

Anyway, that is a rundown of the data services that we offer. If you have any questions, if you'd like to talk further, just hit me up on Twitter. You can hit us up at sales@nomics.com. But we really enjoy doing this stuff and it's fun to work really deeply with folks that are knee deep [00:14:30] in this data day in and day out. It's usually good times. All right. Take care. Bye.