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]

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