Ask, don't search. How PromptQL democratizes go-to-market analytics in real-time

And I work with a lot of go-to-market leaders, often in the sales and revenue space. They're looking to make better business decisions by drawing insights from data that are in all of their different go-to-market systems. This could be Salesforce, it could be Clary, it could be APIs. Using these signals, they want to draw better decisions, draw better data, and make decisions faster. The challenge they have at the moment is to get that information. They even need to spend a lot of time in Salesforce They need to query lots of different places. They need to build up these different dashboards, build reports, or work with data scientists to do the same. And by the time they have that data, they need to slice and dice it in different ways. So there's often very long feedback loops, which is only further complicated by the fact that deals are moving all the time. And by the time you look at data from last week, it's often out of date. So using PromptQL, what we can do is take an approach where we give access to insights to business leaders. I'm asking a question I've connected up to a couple of our GTM systems. I've said, hey, why may we not close any committed deals this quarter? Or what may impede us from committing specific deals? Are there any deals at risk? What PromptQL will do is it will go to all of my different systems and it will help me build this representation of risk. And then it will get that data, provide that data to me in real time, and allow me to visualize that in different dashboards, in different charts, and often in tabular form as well. So looking at this, it's saying, hey, I want to know the kind of information we have about our opportunities. I want to look at late stage opportunities, and then for each of those opportunities, get a better understanding of what may cause us to not close that. If I see anything in here, and all of this is automatically generated from PromptQL, if I see anything in here that doesn't quite work with my dataset, maybe I only want to look at late stage opportunities, maybe even technical validation, I may want to take that away. I can remove that and I can fire that query off again. So working like a query partner in order to drive PromptQL to a better conclusion. Now, what PromptQL is doing is it's building up this representation, it's going to the data sources, it's querying it, it's providing me with all of this information in real time. So I can look at this and I can see all of the deals that may have risk. So here's a bit of a risk assessment of all of these deals. I can say, hey, that's, you know, probability of this is being pulled from Salesforce and why there are risk factors. So in this case, no primary contact, no recent activity. And what PromptQL will do is it will steer me in the right direction to show, hey, I've got a few high risk deals. I can then focus on them. Looking at this in a little bit more of a rich form, looking at a bit of a conversation I had earlier on today, I asked PromptQL to build me a dashboard that shows all of my important business metrics. ARR by customer type, I've got some charts in here, looking at region ARR, and all of this kind of thing. The end result in this is that if I zoom down here to my performance dashboard, again, something PromptQL put together for me, it's gone out to all of these different sources and pulled all of the information, again, in real time without me having to go and construct this or write a single line of SQL or talk to a data scientist. All of these insights are now fully democratized, and I'm able to work in my own business and drive insights on myself. If I look at how I've constructed this, what I've done is I've connected it up to Salesforce, I've connected it up to Clary, and then I've connected it up to a whole bunch of different actions. So I'm now able, as soon as these data sources have been plugged in, without moving any data, without changing anything, without having to write a single line of SQL, I'm now able to write natural language queries that go across any number of different data sets, run calculations, and provide me with the insights that I need in order to better run my business.