Welcome to Law Next PR, the podcast where we put a spotlight on the latest news coming out of the legal tech industry. This is Bob Ambrogi and in each episode of Law Next PR, I interview a legal tech company about its just released news or latest developments. Today, we highlight KLapper, an innovative no -code, do -it -yourself legal virtual assistant builder powered by generative AI. It was developed by the company KLoBot and Here to tell us about it is KLoBot's CEO, Ragav Jagannathan.
Ragav, welcome to the show. Thanks, Bob, for having me. Ragav, before we get to the product, before we talk about KLoBot, tell me a little bit about yourself. My name is Ragav Jagannathan. I've been in the industry for just over a couple of decades now, primarily working within the legal industry.
I work personally consulted for law firms over the last couple of decades in many different capacities, especially in the last five years, we've been focused on how we can use the power of artificial intelligence to surface firm intelligence in basically where attorneys work in SharePoint or in the... Windows platform or the Teams or Zoom or any of that. So my focus has been over the last five years, primarily around surfacing from intelligence using AI where attorneys work.
Last week you introduced KLapper, which is something new to the market. Tell us what it does. KLapper truly is a unique platform. It's a first of its kind. It is a do -it -yourself, no -code virtual assistant builder platform.
Now what that means in simple English is basically KLapper helps non -technical people, knowledge managers, knowledge attorneys, knowledge workers, to basically people, knowledge managers, knowledge attorneys, knowledge workers, to basically connect and surface intelligence. that is hidden within their knowledge systems.
For example, your document management systems like NetDocuments, iManage, your experience management systems, the Litera Foundation, your SQL databases that powers your time -building platforms like Elite and AdRent, your custom homegrown applications where you might have custom databases designed for that. So knowledge lives beyond just documents. So KLapper... Design assistance, assistance that you can design with KLapper with no code.
You can simply use our powerful connectors to connect to these databases, your You can simply use our powerful connectors to connect to these databases, your documents and systems, and just surface intelligence using the power of JourneyBI.
So KLapper helps you design, create, and deploy a very intelligent assistant that So KLapper helps you design, create, and deploy a very intelligent assistant that So KLapper helps you design, create, and deploy a very intelligent assistant that you can use basically for Q &A. For example, you can ask it questions that is intelligence and uses the intelligence that it just gathered from those knowledge sources to answer your question in the most appropriate way with citations.
Or you can even do things on your behalf to a true assistant. For example, creating a meeting on your behalf, doing time entry on your behalf, For example, creating a meeting on your behalf, doing time entry on your behalf, even applying for leave on your behalf, manage expense claims on your behalf, approved claims on your behalf, or even submit a claim on your behalf.
So KLapper design assistants can not only surface knowledge, but they can also do So KLapper design assistants can not only surface knowledge, but they can also do actions, take actions, truly act as an assistant for an attorney. And all this can be done securely with our KLapper platform using the KLapper Builder. And the beauty about the KLapper platform itself is it's highly secure. It deploys and gets configured on the firm's Azure tenant.
This is a major differentiator for some of the other possible competitors out there because all your data that KLapper learns lives in your tenant. because all your data that KLapper learns lives in your tenant.
So we as a vendor, we do not have access to it and neither does anybody else except So we as a vendor, we do not have access to it and neither does anybody else except for the Microsoft Azure tenant that you provisioned as part of the Microsoft Azure subscription that you have and KLapper data, all its learnings just stays there. And the last but not the least, the most important part of KLapper is this pricing model, which makes it available to everybody.
model, which makes it available to everybody. One of the key problems with AI and its adoption is cost. It's so expensive for mid -sized firms, even larger firms, to adapt and adopt an AI -based assistant slash helper. AI -based assistant slash helper. With KLapper, you can design assistants that is based on a very cost -effective, active user model. meaning that you only pay for the users that use KLapper. So the three prong approach makes KLapper unique.
No code, highly connected learning model that can learn off your data sources, your No code, highly connected learning model that can learn off your data sources, your actual knowledge sources within your firm, not just documents, beyond documents. A highly secure deployment infrastructure, meaning that KLapper lives within your Azure tenant, within your domain, so no one has access to the data it learns except for you.
And third is cost effective, which means that anybody can afford a news KLapper to design your AI strategy. You've covered a lot there. Let me break down a little bit more some of the details around this. First of all, who are the kind of the target users for this within a law firm? So KLapper has two components to it. One component is designing the assistant itself. Assistant design, meaning the, in the olden days or five, seven years ago, this term we used to use was chatbots.
Now we don't no longer use that because of many different reasons, but obviously because of the fact that the new General AI models and the term that often people use is assistant. So I'm going to continue to use assistant. So there are two aspects of KLapper. One is an assistant builder and an assistant consumer. The assistant builder, the target audience for that could be both non -technical and technical people within your firm.
So a non -technical person could be a knowledge attorney who has limited to decent knowledge in IT, which means that he or she has built something before using say a power app with Microsoft, like a form or a simple workflow or it's a little say a power app with Microsoft, like a form or a simple workflow or it's a little bit technical. or simply a completely non -technical person who is really focused on knowledge. or simply a completely non -technical person who is really focused on knowledge.
So, Klackware Assistants can be built by both non -technical and technical knowledge workers, knowledge attorneys, knowledge managers, innovations professionals, and IT. So, you can simply use a drag -and -drop model that helps you design an Assistant So, you can simply use a drag -and -drop model that helps you design an Assistant connected to your line of business data, your time and billing data, your DMS within seconds.
Once you configure and design your assistant, you're tested within the sandbox. And then you deploy that for your end user consumption in a channel, like a Microsoft And then you deploy that for your end user consumption in a channel, like a Microsoft team channel or a Zoom channel or as a Windows app. So the idea is that you design the assistant as a knowledge professional, and then you deploy that assistant on any platform where knowledge consumption happens.
And that could be on a website, that could be on your SharePoint Internet teams, as I said before. So the end users or the attorneys or the partners, associates, the interns, those are the consumers of KLapper.
Even shared services folks like HR, finance, marketing, basically depends on the reason you created the assistant for that can be consumed by any employee the reason you created the assistant for that can be consumed by any employee the reason you created the assistant for that can be consumed by any employee within your organization.
Ragav, I assume that the builders can build multiple assistants to address Ragav, I assume that the builders can build multiple assistants to address multiple scenarios. Can you give examples of some of the scenarios that firms would use this for? Sure, yeah. So typically, as I said, KLapper is an assistant builder platform, meaning that you're designing an assistant for a specific or specific use cases, either a specific use case or use cases.
Let me give you an example of a generic use case like a My HR Assistant. With a My HR Assistant, you can create a very powerful assistant that can...
With a My HR Assistant, you can create a very powerful assistant that can... answer questions related to HR within your firm, could help you with onboarding answer questions related to HR within your firm, could help you with onboarding process, could apply for leave on your behalf, could check on leave balance on process, could apply for leave on your behalf, could check on leave balance on your behalf, and perform a lot of different HR duties on behalf of the
your behalf, and perform a lot of different HR duties on behalf of the attorney, like the ones I just mentioned. So that my HR assistant, the HR professional in your firm, maybe the HR... consultant, the director, whoever the person is, would simply go to KLapper Builder platform, create a new assistant, call it MyHR, for example, and then Builder platform, create a new assistant, call it MyHR, for example, and then connect it to your HR system using our connectors.
For example, if you use ADP or if you use PeopleSoft, you can simply connect that For example, if you use ADP or if you use PeopleSoft, you can simply connect that assistant to those applications to get and set data, meaning that you can get information about information about How much PTO do I have left? Or you can set information. Can I apply for a leave on a specific day or a duration of days? Can I apply for a leave on a specific day or a duration of days?
You can even train that assistant on data, which are a document like policies and procedures that may live in, say, iManage or NetDocuments or just in SharePoint. procedures that may live in, say, iManage or NetDocuments or just in SharePoint. So you can simply use one of our connectors, iManage connector, or SharePoint connector, or NetDocuments connector. Train that assistant.
on the document library or the workspace and all the documents within the workspace or document library so that when people ask questions about leave policy within my or document library so that when people ask questions about leave policy within my firm or any kind of discrimination policy within my firm or any kind of policy and firm or any kind of discrimination policy within my firm or any kind of policy and procedure that exists with my firm, KLapper, my HR assistants already learn
from those sources. So when you deploy this to say your HR team in Teams, or simply make it available as a chatbot in your intranet on your HR portal, users, or simply make it available as a chatbot in your intranet on your HR portal, users, attorneys, just staff members can simply click on it and interact with it. They can ask questions on your corporate policies or on HR, or they can ask you to do stuff on the attorney's behalf, like apply for a leave or check on the balance.
Basically, consumer of that assistant once you deploy it in a channel they consume. So that's an example of my HR system. For example, a different use case could be a time and billing assistant. For example, a different use case could be a time and billing assistant. A time and billing assistant could be very useful.
And this is a very common use case because as part of a couple of other companies that we build a lot of intranets for firms, intranets that intranet portals that basically surface data intelligence. So the ability to surface that data intelligence that is stored within my time and billing platform. or even apply or enter time sheets and automate the process or proactively deliver alerts to you based on some key data metrics. Give me an example of that.
You can design a time and billing assistant and can know who the person is. So you make it persona driven and user driven, meaning that it only shows you the So you make it persona driven and user driven, meaning that it only shows you the data you're supposed to see from your time and billing platform. And you can simply connect this assistant as the assistant builder. to your time and billing platform database, let's say SQL, let's say Elite SQL, and it let it learn of the data.
SQL, and it let it learn of the data. And you design the assistant, you fine tune the assistant prompt engineering. And basically the purpose of this assistant is to, is a reactively a proactive deliver data alerts to you, the data that you care about. For example, my missing time sheets for the week, for example, or my billing's here to date. The ability to get that data or the matters that I'm working on, right? The ability to get that data or the matters that I'm working on, right?
or just to get the status of a recent matter that I was involved in. So to have that instant data point access, either reactively that I'm asking the assistant as an attorney on a team chat or a chat interface in the SharePoint portal, assistant as an attorney on a team chat or a chat interface in the SharePoint portal, wherever it surfaced, the ability to ask that or reactively ask that or proactively being delivered that alert in my team chat by KLapper Assistant.
So these are some of the use cases that you can design without writing a single line of code where KLapper is connected, seamlessly connected through our connectors, through a line of business data. It learns of the datasets using the PowerJet API and either does stuff on your behalf or answers stuff on your behalf, questions and answers. behalf or answers stuff on your behalf, questions and answers.
You talk a lot about these intelligent connectors as one of the unique features of this application. How easy is it to set up those connections using your intelligent connectors? Great question. So our intelligent connectors, the reason why we call them intelligent connectors is because they're truly intelligent.
And if you notice, I continue to use the word no code because one of the key points And if you notice, I continue to use the word no code because one of the key points of KLapper is a platform designed for non -technical people, meaning that creation of KLapper is a platform designed for non -technical people, meaning that creation of an assistant is simply clicking on a button that says create assistant and it has a name and a description.
Once you create that assistant, empowering that assistant with a knowledge source Once you create that assistant, empowering that assistant with a knowledge source from an Imanage workspace is simply clicking on a button called Knowledge Space and picking Imanage as a connector and then simply picking your source where Space and picking Imanage as a connector and then simply picking your source where you want to train it from.
Using our really simple to use content browser window, you can simply browse the Using our really simple to use content browser window, you can simply browse the content that you care about in Imanage, taking an example. workspace that you care about, you can simply search for the workspace, find that folder that you want to train the content from, and pick that folder, take it, and folder that you want to train the content from, and pick that folder, take it, and just say train. That's it.
It's that simple. So the design behind KLapper, if you compare it with, say, some of the other So the design behind KLapper, if you compare it with, say, some of the other products out there, including Microsoft Co -Pilot, which is a pretty technical tool if you want to design an assistant, we designed an assistant builder platform with attorneys in mind. with knowledge managers in mind.
Because of our experience working with attorneys, working with knowledge managers, we understand the nuances around all the technical terms that you're hit with when you're designing AI power bots and agents and assistants. So with our intelligent connectors, it literally is extremely simple. And some of the videos that we publish on the internet will showcase that. How easy it is to simply pick, point, click, configure, and click on the train button. And just like that.
Using the Power of Journey BI, we learn the content, the KLapper assistant learns the content in that context so you can ask good questions. So Ragav, if I'm a law firm innovation professional or KM professional and I'm listening to this interview right now and I say, sounds interesting, how do I get started? How do they get started? What's involved in getting this set up and deployed in the first instance? What's involved in getting this set up and deployed in the first instance?
So KLapper deploys on your Azure platform on your Azure tenant, you are meaning the So KLapper deploys on your Azure platform on your Azure tenant, you are meaning the firm's Azure tenant. We do offer a hosted model, but we recommend that you go with this model that be strongly endorsed to take KLapper and deployed on your Azure tenant. So to get started, KLapper installation literally takes minutes. So to get started, KLapper installation literally takes minutes.
We've thought through the entire process from start to beginning as long as. The firm's IT can provision the prerequisites for KLapper, the Azure The firm's IT can provision the prerequisites for KLapper, the Azure tenant space that it needs, the Azure OpenAI subscription that it needs. tenant space that it needs, the Azure OpenAI subscription that it needs. Deploying KLapper takes minutes.
Once it's deployed, the next step is to work with our customer success team to Once it's deployed, the next step is to work with our customer success team to Once it's deployed, the next step is to work with our customer success team to help understand how the KLapper Builder works. Now, again, as I repeatedly said during this podcast, we design software for lawyers, for knowledge attorneys. So as soon as you look at the KLapper UI, the user interface, you would see that it's super simple.
You would not need a user guide to use KLapper, to create a virtual assistant, to empower the virtual assistant, literally connecting to an iMinute source or a NetDocument source or a SQL source or a SharePoint source. or even a modern web application microservice, I just threw a lot of tech terms there, source, or even SQL source, SQL server database source. Connecting to those sources is really simple. Point, click, configure, connect.
The additional training that we provide is around formatting of the data and prompt engineering. How do you design prompts that helps KLapper understand the queries better so it can answer the queries better? And once, when it answers the queries better, how does it answer it? How does the formatting of the answer work? And the formatting of those answers can, you don't need to learn JSON. You don't need to learn all those things.
You can simply write English language texts and say, look, format in bold amount in dollars. Literally a text like that. And KLapper learns that, look, if I encounter a dollar amount in my output, I should format that in bold. So we've talked through the whole process of how the input formatting input prompting works, how the output formatting works.
No need to learn JSON, no need to learn variables, no need to learn all that stuff that, for example, in power automated you need to do or co -pilot a studio you need to work on. With KLapper, all that stuff is just plain old simple English. So we'll help you, we'll train you with our customer success team to do input and output prompt engineering. And really it's a joined effort.
So from that point onwards, We are available from a consulting perspective for the firm so that we can help you design some advanced skills for KLapper. If that's a use case that you want, we can also jointly build together a proof of concept that you may have that you want KLapper to learn from sources so that it can do stuff or answer stuff. We can jointly design that for you together as part of a service. But there are many ways to engage. Our bottom line is this.
We believe KLapper is an amazing product. We've designed KLapper based on our learnings from doing AI powered software over the last five years. We've designed a software for attorneys and knowledge managers and knowledge workers. So working with our customer success team, we can make sure you're successful. I guess we're about out of time. Anything else you'd like listeners to know about KLapper?
I think you covered most of it with your questions and hopefully answered those in I think you covered most of it with your questions and hopefully answered those in an informative way.
The one thing I want to leave you from a KLapper perspective, the key value proposition of KLapper, truly simplicity and our know how of the law, especially proposition of KLapper, truly simplicity and our know how of the law, especially the legal communities, because if we build intranets, we build extranets, we build custom solutions, we understand the nuances of data from data.
So in terms of KLapper, connecting to these datasets, extracting intelligence from the dataset, literally connecting to these datasets, extracting intelligence from the dataset, literally is a point, click and configure. So reach out to us, help us help you launch your next AI big thing at the idea firm. KLapper truly is an amazing product. I can't wait to show you. Thank you so much. Thanks so much for being with us today.
We've been speaking with Ragav Jagannathan, the CEO of KLoBot about KLapper. That's with K -L -A -P -P -E -R, just released last week. That's it for today's episode. If you enjoyed it, please subscribe wherever you get your podcasts or on YouTube at LawNext underscore PR. You can also find all of the episodes on the LawNext Legal Tech Directory under the resources tab. This is Bob Ambrogi. Thanks so much for listening.