Phil Fersht — CEO, HFS Research[00:21]
Hey, it’s great to get some time with an AI founder who’s coming at us from the San Francisco area today. Andrew Antos, who’s the founder and CEO of Klarity. So great to have you here. Andrew, maybe just to get started, for the benefit of folks at HFS, what is Klarity, the Klarity platform, all about, and a little bit about how you got started?
Andrew Antos — Founder and CEO, Klarity[00:51]
Yeah, absolutely, and thank you so much for having me. I’m excited to be here. So what we do is we help companies automatically document the work that actually gets done, because it’s mostly held in people’s heads, a lot of old existing documents, and a lot of video walkthroughs. We hope to really understand what people are actually doing on a day-to-day basis, in excruciating detail, and then we hope to automate those tasks.
Phil Fersht — CEO, HFS Research[01:14]
You know, you’ve come up through the world of, I guess we used to call it intelligent document processing, RPA, intelligent automation, etc. How would you characterize Klarity in the business you’re in now in terms of the value you bring to market, and do you fit into a box or are you creating a whole new paradigm?
Andrew Antos — Founder and CEO, Klarity[01:40]
We actually never thought about ourselves as fitting into any boxes. A lot of the work that we’re helping to do is actually done with a lot of consultants and a lot of BPO work, right? So just on the automation of documenting everything that’s actually going on, and helping you get insights into how can I automate my SOX testing, how can I automate all of my transition to the AI world. It all starts with actually documenting what people are doing. Some companies do this naturally in-house, but most companies just do it with a lot of consultants, and they do it not very frequently. And so we think the biggest opportunities for AI are actually not in terms of replacing existing software categories, but in terms of actually focusing on headcount. Really what Gen AI is, is a labor arbitrage opportunity with cost that is massively decreasing over time, rather than increasing over time.
Phil Fersht — CEO, HFS Research[02:53]
OK. And you know, your platform is very much centered around transformation and how to do this successfully. What have you learned about transformation in your time, and what do you think is working and what isn’t working for enterprises?
Andrew Antos — Founder and CEO, Klarity[03:12]
There’s always this trade-off between breadth of transformation and depth of transformation. What oftentimes happens is a lot of companies end up in the situation where they’re trying to transform seven or ten different things at the same time with very questionable ROI. And so what we’ve learned, and that’s why we launched that second product that I talked about as well, the Architect, is you want to achieve both breadth — you want to look at your entire organization and understand how it’s actually working, what is the work that people are doing on a day-to-day basis — and then achieve the depth of understanding, like, OK, what are they doing? So you can actually find the three to four needle movers that, if you go in and automate those, you get the 80/20 kind of ROI, strong ROI, right up front.
Phil Fersht — CEO, HFS Research[04:10]
Right, right. And so as we look at — you mentioned Gen AI earlier, and some of these emerging techs that are hitting enterprises — how is that impacting the transformation conversation? Is it that clients are saying, hey, can we look at this tool, can we look at that tool? Or are you trying to ground them in thinking a bit more about the process and the outcome before we think about the technology, and how are things changing from that perspective?
Andrew Antos — Founder and CEO, Klarity[04:28]
So I think there are two different kinds of things that are happening at the same time. The first is that the future of automation is much more verticalized than it has been, in our opinion, right? Because historically you had a couple of automation platforms that would just sit there, and you could use them to automate all kinds of admin, paper-pushing tasks across your organization, because they were pretty shallow and very horizontal. What we’re seeing now is that everything we see in the market, including what we do, is very verticalized and very deep, right? So you go from some transaction processing that is done by 100 people today, and you go to three people and a lot of AI. And so I think the future is going to be much more verticalization. The days where you can have one or two automation platforms as an enterprise are gone. That’s number one. And then number two, I think it really starts with scope. Scope is deeply misunderstood, because we still think about scope as we thought for traditional software, right? You have an exact spec of what that software can do, and then you’re trying to say, OK, well, what processes can we fit into that scope. Now it’s the other way around — you want to first understand what people actually do, so you can figure out how to replicate that work, because AI is so much more flexible than traditional software. So those are the two key insights that we got.
Phil Fersht — CEO, HFS Research[06:09]
Right, so it’s created a lot more flexibility in the conversation, so we can certainly do a lot more, there’s a lot more options, there’s a lot more tools available. So when we get to documentation, which I know is very big for Klarity — you guys have talked about it, it’s a must for any transformation — what do people do wrong when it comes to documentation?
Andrew Antos — Founder and CEO, Klarity[06:32]
I think there’s a couple of key properties that documentation has. Number one, it’s almost never a priority, right, unless you’re going public or there’s some kind of audit or transformation effort. It’s almost never a priority, and so you’re always playing catch-up. It’s very rare that you have people — and there are some industries like banking and insurance and so on that do better because they have to, because of regulators — but there’s just a lack of documentation, and that means there’s a lack of people whose sole responsibility, or at least number one priority, is to have good documentation. And so there’s this kind of lack of transparency. It’s almost like looking at the contours of a map. You don’t actually see the whole map in detail. And so if you go from this spot today, where you haven’t automated yet, you haven’t transformed it, and you want to arrive at that spot, you kind of need to see the whole map — where do all the roads go. And that’s where documentation really comes in, and that’s why we built the Architect: to really help companies understand what the actual map is, where they are today, what the analysis of that state is — it tells you, oh, these are your automation opportunities, these are the tools that could do it really well, this is the spec, this is what the future process looks like. Really it’s like fill in the map for the transformation effort.
Phil Fersht — CEO, HFS Research[07:51]
What do people need — and we talk about documentation now that has changed in terms of keeping it updated, keeping it relevant, those types of things — and how does your platform help with that?
Andrew Antos — Founder and CEO, Klarity[08:17]
Yeah, so our core insight is that how the work actually gets done is in three places. It’s in some existing documentation. It’s in a lot of video walkthroughs — especially in the pandemic, companies started recording a lot of video walkthroughs, so there are a lot of Teams or Zoom recordings lying around. But most importantly, it’s tribal knowledge. It’s in people’s heads. And so we have a way where we can take videos in, irrespective of what the structure is and how long they are, we can take existing documentation, and most importantly, we have something called AI Interviewer. It’s literally AI that talks to you and asks you questions about your process, and you can share a screen, and it understands everything that you actually do. We take that in, and then we create the documentation. And then every quarter or every month, or if there’s an event, it just comes to you and says, do a five-minute interview on what is the change, what is the delta in the process. And then it automatically updates all the documents, whether it’s SOPs, BRDs, SOX narratives, whatever that might be. And so the activation energy to update documentation basically went down to close to zero.
Phil Fersht — CEO, HFS Research[09:26]
So where do you see this going? Maybe look out three to five years. You know, we’ve been doing things very much in a similar way for the last three or four decades. We have all these tools at our disposal, we have more flexibility, regulations are shifting, there’s also lots more unknowns. What do you think this space is going to look like in another three to five years?
Andrew Antos — Founder and CEO, Klarity[09:45]
So I think there are kind of three things that will happen. Number one is — and I cannot overemphasize this — the depth of understanding of how work actually gets done, I think, is going to change drastically, right? Because if you think about a big company right now, you have three layers, or five layers, or sometimes ten layers of people between a decision maker and who’s actually doing the work, right? And so getting the visibility and understanding what the work actually is — that’s going to change, and it’s going to be tools like us that will help with that. This is deep business understanding. I think business intelligence and understanding metrics made huge progress over the last 30 years. I think the next big step is deep business understanding — what do organizations actually do on a really detailed level. The second thing that I think is going to change is that a lot of things that are done in a cadence, whether it’s annual or biannual or quarterly or monthly, are going to change to a continuous system, whether it’s continuous SOX testing. I’m not going to be testing my controls once a year and then scrambling to fix something. I’m going to be testing them every single day, because the cost of testing — that’s what we mean by talking about the cost of intelligence coming down. I can test all of these things for very little money, or nearly free, all the time, and so I’m not going to have any nasty surprises. That’s the second thing. And then the third thing, and that’s my biggest question, is what’s going to happen with the cultural shift, because I think the biggest friction is not the technology, it’s not the unknowns, but it’s just, this is how we think, this is how we’ve always been doing things — and just how quickly will people and processes change and adapt. But I think we’re going to start seeing, and it’s already showing now, the first true exponential organizations, where you have companies that are supporting much more revenue per person than we historically thought.
Phil Fersht — CEO, HFS Research[12:18]
I guess it’s all about people and technology and the blurring together of our worlds, and the fact that people are expected to be so much more productive, can handle a lot more transactional volume because of the tools at our disposal. So thanks very much for sharing your platform and the great work that you’re doing, and I look forward to hearing about your successes in the future. Thank you, Andrew.
Andrew Antos — Founder and CEO, Klarity[12:18]
Thanks so much for having me, Phil. This was a lot of fun.
