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
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
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
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,
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
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.
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.
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.
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
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
bit technical.
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
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
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
within your organization.
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...
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
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
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
assistant to those applications to get and set data, meaning that you can get
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?
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.
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
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,
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.
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
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.
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?
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,
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.
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
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
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
you want to train it from.
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
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
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?
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.
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
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
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
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
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
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.