← The Digital Executive
The Digital Executive
Dr. John Bates on AI, Document Intelligence, and Trusted Automation | Ep 1247
00:18:12
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Podcast Host (Interviewer)
Welcome to Corazon Technologies, home of the Digital Executive Podcast. Do you work in emerging tech? Working on something innovative? Maybe an entrepreneur? Apply to be a guest at www.corazon.com brand welcome to the Digital Executive. Today's guest is Dr. John Bates. Dr. John Bates is the Chief Executive Officer of DOCSIS, formerly SIR Group. John is an experienced CEO with over 25 years of industry experience and he has collaborated three times with DOCSIS majority owners, the Carlyle Group. John is also a non Executive Director of Sage Group plc, a leader in cloud accounting and financial management software. Prior to DOCSIS, John was the CEO of Eggplant, a pioneer of AI powered software test automation and the CEO of Platone, an IoT apps platform acquired by SAP and founder and president of Apima, a pioneer of streaming analytics. He has also served as a C level executive in several public software companies including Software Ag and Progress Software. He holds a PhD in Computer Science from Cambridge University. Well, good afternoon John. Welcome to the show.
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Dr. John Bates (Guest, CEO of DOCSIS)
Thank you very much. Great to be here.
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Podcast Host (Interviewer)
Absolutely my friend.
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Dr. John Bates (Guest, CEO of DOCSIS)
I appreciate it.
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Podcast Host (Interviewer)
And you're hailing out of the London, England area in the uk. I'm in Kansas City, so I just really appreciate you making the time and jumping time zones and calendars, et cetera to get here. So thank you again. And John, if you don't mind, I'm jumping into your first question. You've built an impressive career leading multiple innovative software companies from founding Appoma to now serving as a CEO of docsis. What key experiences shaped your journey to where you are today?
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Dr. John Bates (Guest, CEO of DOCSIS)
Well, I'm really a product guy and so I always look at things through a product lens. I guess I'm a former professor of computer Science. I'm a PhD in Computer Science and Apalma which was the first company was when I cut the umbilical cord and went over there to from the crossed over to the dark side if you like and decided okay, I'm going to commercialize some of my research which was a company that used machine learning techniques to find patterns in fast moving data and act on them in sub microsecond latency. But so my first experience I guess was building everything myself from the product to the company to the go to market to then doing crossing the chasm. Boy, that's a lot of effort. So we applied that technology in the, in the area of algorithmic trading. So I had a lot of early experience of autonomous agents kind of running around trading automatically and processing millions of events a second and fighting against each other. So I think I've got a little bit of a harbinger for what's going to happen with the agents now that we're rolling out of AI. But, but I learned really from that that it's really cool to find a really good technology and in a space that's ripe for disruption. In that case it was algorithmic trading. People were taking months to build algorithms, gave them a technology where they could plug them together in hours and pointing that technology in that space that's right for disruption playing into a coming revolution. And I've done that a couple of times since I've sold five businesses and everything from my previous company Eggplant, which was a really cool software test automation technology where we used it was really the first AI powered software test automation which everyone's doing now but applying generative AI with a model to say okay, let's automate the building of test scripts based on what we can figure out about this system and then let's use AI powered agents bots to be able to run those test scripts in real time without even access to the code. So the Orion space vehicle that's just gone around the moon, that was the interface of that was tested with Eggplant. So that would, that was a really cool pivoting that technology, using AI into the software test automation challenge. And then Docsis is similar, which is document intelligence we call it, which is the next generation of document management, document automation and applying AI to the end to end document cycle. So that's really, it's all about the vision and taking cool technologies and dropping driving them into places where disruption is, is about to happen.
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Podcast Host (Interviewer)
That's amazing. Thank you and I appreciate your Background, obviously your, your educational, your research, PhD background has made a difference and contributed to your just extensive career here. And I liked how you, you look through this product lens as you talked about, because you, you mentioned built, you built everything from the ground up. You did product, you did design leadership, you did it all. And I think because of that, you built some of the most innovative companies and software and now you're actually leveraging that power of AI in this new document automation, document management, end to end. And I think that's amazing. So thank you. And John, at docsis, you're focused on intelligent content automation. What problem are you trying to solve for enterprises and why is it so critical right now?
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Dr. John Bates (Guest, CEO of DOCSIS)
Problem that way trying to solve really is how can you maximize your team and make them 100 times more productive when they're managing documents. And documents are really still the lifeblood of businesses. Every day, billions of documents flow into enterprises, whether it be invoices, orders, resumes, you name it, they're driving businesses with documents. And businesses have to store them, have to find, have to search them, have to generate new ones, have to communicate them, have to interact with them, have to do or collaborate with them. So this is a massive problem, it's a massive productivity problem. And there's a whole load of legacy platforms out there that are just not bringing us into the new era. Because what you really need to do is automate the whole document life cycle, from the understanding of documents, automating that with AI, to the automation of processes around documents, to being able to store documents in a massive scale. I'm talking about tens of billions and being able to find things in those. How can you automatically find the gold nuggets that are the opportunities and threats in your business? And then how can you collaborate around them? How can you automate the generation of them, the communication of them, and so on? So we've really brought together, converged a load of different technologies into one seamless platform, which is an AI first platform. And if you just consider, for example, just take hr, which is a real big consumer of documents. Imagine you want to hire people, you want to understand resumes coming in saying, are these relevant for this job? This is what we're looking for. Match them, send them to the right people for approval, automatically triage them. Then when you want to hire somebody, how do you automate the document processes around their hiring? How do you generate their contract? How do you send out mass emails tailored to employees without causing massive overheads? And how can you help your team automate this? And the Same is true in financial documents with the CFO department, invoices, purchase orders, purchase to pay, order to cash. Same is true in financial services organizations. Know your customer processes, detecting fraud, generation of your annual statements and insurance, and so on and so on. So documents are still the lifeblood of businesses but they need a new era of platform and that's what we're trying to do.
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Podcast Host (Interviewer)
Amazing. If you think about it, it's almost like we of take this for granted. There's documents everywhere in everyday life, personal or business, any industry. And if you think about that, it's massive. And you talked about this problem everywhere. How do you maximize your team's productivity when there are millions, billions of various types of documents in everyday business? But you're automating with docsis, the whole document lifestyle, receiving, sending, search, indexing, storing, et cetera. And you shared some examples in the HR and the finance verticals. Leveraging the power of abdocs, this AI first platform and you're really going to make the world a better place. So thank you John. With AI increasingly embedded in enterprise software, how should organizations think about balancing automation with control, governance and business value?
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Dr. John Bates (Guest, CEO of DOCSIS)
Well, for me it's all about trust. Trust is e in your enterprise systems and there's a lot of confusion right now. Everything's about AI. You've seen the SaaS apocalypse in the markets and lots of fear around. Oh, you can just do everything with an LLM, it's going to replace everything and maybe if you just feed your documents into an LLM that will just replace everything, maybe it can just generate all the applications you need. But the danger here, and I think we're going to see this more and more of course unchecked with just raw LLMs you can get hallucinations, so you can get things that aren't actually there in your documents, you can get non determinism. So your processes will behave differently on the same process will behave differently on different days, different moments. And you can generate code that can't scale and might run into serious bottlenecks. So I mean for me AI is clearly a massive game changer. It's a new industrial revolution. But you've got to manage that trust piece. So there's amazing promise out there. You can ask questions in natural language, you can generate new applications quickly, you can use agents to replace or augment people approving steps. So but you need to add things around this. So you need governance, you know, you need one security model, one authorization model, you need determinism, you need to make sure your automation behaves the same way every time with the same input. So you need determinism in automation, you need determinism in search. So you want to make sure that there's no hallucinations in your search. And the way that we do that is with a technique called retrieval augmented generation combined with vectorization so that you can add real data from documents back into your search so you actually zero in on the right information rather than it cooking something up for you. You need a highly scalable system so you're not going to just vibe code the next generation document management system and it needs to be future proof. So you need to be able to have what I call composable AI, the ability to map into different large language models even dynamically. So you might send particular analyses requests to a different LLM depending on the specialization. And then finally I like to think of sort of you need a Checkpoint Charlie. So if you are going to have agents to vibe code or agents to do certain things, you need to Give them defined APIs to access this system so that you preserve trust, determinism, scalability and the right routes authorization through the platform. So these are just some of the things that I think you need to think about when you're embarking upon a next gen document strategy.
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Podcast Host (Interviewer)
Thank you. Ought to unpack there, but I think it's important the takeaway here in your answer was trust is key in these enterprise systems, especially in this world of AI with these LLMs. And you talked about unchecked LLMs can produce hallucinations. There could be some unchecked code, creating bottlenecks could be all kinds of problems. And I think it's important you did highlight having that one security, one governance model. And key takeaway here is determination and automation which you delved into there. So I appreciate that. And John, the last question of the day as we look ahead to the future, how do you see AI automation and enterprise platforms evolving over the next decade and what role will companies like docsis play in shaping that future of intelligence business operations?
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Dr. John Bates (Guest, CEO of DOCSIS)
Your AI is clearly going to change everything, is changing everything. But it's of power. And like any great power, rather than just let it loose unguarded, we need to have checks and balances around it to make sure it does bring in those trusts. And I think that's the kind of role that enterprise companies going to buy play enterprise platforms anyway in their own domains. And I think there's going to be a bit of a, if you like what Gartner would call a trough of dissolution month in AI going to come up, but that doesn't mean it's not super important and game changing. But I think these topics of trust, determinism, reliability, scalability are going to bite some people. They just haven't thought this through. They're under such pressure to, oh my goodness, we've got to have an AI strategy and they need to think these things through. And I think a little bit like the Internet bubble where, you know, if you go back to the late 90s, you have this, oh my goodness, it's all about eyeballs and clicks and so on and so forth. And then it turned out actually the Internet was a game changer, but it was actually all about value and the right business models. And so a lot of things get swept away, but the right business models did in fact come to the fore. And whether it be your Amazons or your Microsoft's or whatever, that still around today. And I think you're going to see similar, you're going to see AI find its real powerful value propositions. And I think a lot of that will be through enterprise platforms that add the guardrails around a particular domain. I think you're going to see domain specific models. I think you're going to see things tailored to particular vertical horizontal problems, I mean, all powered by LLMs, but with the right guardrails around it. And I think you're going to see also the hastened demise of a lot of legacy businesses that aren't AI first. So that's what I think is going to happen at an accelerated rate over the next five years.
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Podcast Host (Interviewer)
Thank you. And I agree with that last statement. I think legacy companies and platforms will go by the wayside if they haven't already started working on that strategy of AI first. But jumping into a couple things here, AI obviously has currently and is changing the landscape and I think will forever change the our business landscape here. But and we talk about this a lot on the podcast, we need to have those checks and balances in governing these platforms without guardrails. I think we could have a serious problem on our hands. And that's been a big discussion, like I said, throughout the globe right now. But governance, scalability, reliability, those are important when you're looking at these systems. So I appreciate the insights today, John. And John, it was such a pleasure having you on today and I look forward to speaking with you real soon. Andy, Brian, bye for now.
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