Daisy labs is the front door to access the event graph.

We started structuring events because we were tired of missing out on things to do. 
It is when we asked potential customers the question "what would you do if you had access to every event happening around you?," that we learned this data's potential.
Here is what we heard:

Different industries, different budgets, different vocabularies. But underneath, every one of them was asking the same thing: what is actually happening in this place, right now. And none of them could find out.

So, what is Daisy Labs?

Daisy Labs is how businesses of all sizes can access our graphed open calendars.

The open calendar is the thousands of calendars and millions of events (in the US alone) that are lost in the open web. These calendars were designed to be found but their events can still get lost beyond their page. We've built a proprietary engine to map and structure this expanding data set. Our engines handle tens of millions of rows every day, turning location driven data that was previously impossible to consume into something a business can actually use. It arrives structured, it refreshes as the sources do, and every entry traces back to whoever published it.

The accuracy work matters at both ends of the range. The individual trying to find the farmer's market, and the economic development office trying to understand a whole region, are asking the same question at different scales. The commonality is that accuracy matters. Our work is making sure every row is as current as its source, because nothing is worse than vague or bad data.

We like a metaphor, so think of Daisy Labs as scientists in hazmat suits. We do the detailed and dirty work of connecting the messiest data on the internet.

Because every company before us focused on monetizing their "original" calendar rather than connecting the existing open calendars together. Every product that ever touched events started with monetizing the transaction, advertising first and then ticketing, because that is where the revenue is. And a business built on the sale only has a reason to index events that produce a sale. For example, the concert got promoted but the trivia night got missed, because they made more money from the ticket sales. So every events dataset and every events website shows you the ticketed economy, because nobody was ever incentivized to connect every event in the community. We built it the other way around, without needing any individual event to pay for itself. And with this approach, you're graphing millions of events, and solving a problem that vexes everyone.

Events are back and growing. We saw data projecting the event economy to reach $2.5 trillion globally by 2035 (per Allied Market Research). The problem is you cannot build an event economy if you do not have a complete event database. Think of it this way. Yelp did this for local businesses. Zillow did it for home listings. Foursquare did it for point of interest locations. Each took a scattered category of the physical world and gave it a structure, and each turned out to be worth building. Events are the category nobody finished.

Because Daisy Labs structures the whole record rather than the transactional slice, you can do things the ticketed data cannot.

Daisy Labs is currently 215,000+ venues and 18M+ events, and growing daily.