KLoBot Introduces KLapper – Virtual Counsel Powered by Generative AI

About the Announcement:

KM and AI: Powering the Future of Law Firm Intelligence Automating repetitive tasks and synthesizing information, generative AI is revolutionizing how information is managed, disseminated, and utilized in law firms. As a result, AI is reshaping the traditional role of KM, elevating the strategic importance of knowledge professionals.

KLoBot Inc. recently introduced KLapper, an AI-powered DIY platform for creating virtual assistants, that provide “intelligence anywhere” access to attorneys across their favorite devices and apps using just their voice or text. KLapper is one of many tech innovations of Ragav Jagannathan, an industry disrupter and creator of AI and automation solutions for law firms across the globe.

Jagannathan will share his experience in helping law firms automate and streamline knowledge management, his views on the changing role of knowledge management, and his vision for the future of AI in the legal industry.

Transcript: 1 00:00:06,666 --> 00:00:10,625 Welcome to Law Next PR, the podcast where we put a spotlight on the latest news

2 00:00:10,625 --> 00:00:12,750 coming out of the legal tech industry.

3 00:00:12,750 --> 00:00:17,000 This is Bob Ambrogi and in each episode of Law Next PR, I interview a legal tech

4 00:00:17,000 --> 00:00:21,500 company about its just released news or latest developments.

5 00:00:22,166 --> 00:00:27,375 Today, we highlight KLapper, an innovative no -code, do -it -yourself legal virtual

6 00:00:27,375 --> 00:00:31,125 assistant builder powered by generative AI.

7 00:00:31,500 --> 00:00:34,750 It was developed by the company KLoBot and

8 00:00:34,750 --> 00:00:39,375 Here to tell us about it is KLoBot's CEO, Ragav Jagannathan.

9 00:00:39,833 --> 00:00:41,541 Ragav, welcome to the show.

10 00:00:41,875 --> 00:00:43,208 Thanks, Bob, for having me.

11 00:00:43,750 --> 00:00:47,208 Ragav, before we get to the product, before we talk about KLoBot, tell me a

12 00:00:47,208 --> 00:00:48,041 little bit about yourself.

13 00:00:48,166 --> 00:00:49,458 My name is Ragav Jagannathan.

14 00:00:49,458 --> 00:00:54,166 I've been in the industry for just over a couple of decades now, primarily working

15 00:00:54,166 --> 00:00:55,958 within the legal industry.

16 00:00:55,958 --> 00:01:01,000 I work personally consulted for law firms over the last couple of decades in many

17 00:01:01,000 --> 00:01:06,791 different capacities, especially in the last five years, we've been focused on how

18 00:01:06,791 --> 00:01:11,875 we can use the power of artificial intelligence to surface firm intelligence

19 00:01:11,875 --> 00:01:17,458 in basically where attorneys work in SharePoint or in the...

20 00:01:17,458 --> 00:01:20,958 Windows platform or the Teams or Zoom or any of that.

21 00:01:20,958 --> 00:01:26,541 So my focus has been over the last five years, primarily around surfacing from

22 00:01:26,541 --> 00:01:30,416 intelligence using AI where attorneys work.

23 00:01:31,416 --> 00:01:36,541 Last week you introduced KLapper, which is something new to the market.

24 00:01:36,541 --> 00:01:38,208 Tell us what it does.

25 00:01:38,541 --> 00:01:41,041 KLapper truly is a unique platform.

26 00:01:41,166 --> 00:01:42,791 It's a first of its kind.

27 00:01:42,791 --> 00:01:48,375 It is a do -it -yourself, no -code virtual assistant builder platform.

28 00:01:48,375 --> 00:01:54,458 Now what that means in simple English is basically KLapper helps non -technical

29 00:01:54,458 --> 00:01:58,666 people, knowledge managers, knowledge attorneys, knowledge workers, to basically

30 00:01:58,666 --> 00:01:59,583 people, knowledge managers, knowledge attorneys, knowledge workers, to basically

31 00:01:59,583 --> 00:02:02,458 connect and surface intelligence.

32 00:02:02,458 --> 00:02:05,125 that is hidden within their knowledge systems.

33 00:02:05,125 --> 00:02:09,833 For example, your document management systems like NetDocuments, iManage, your

34 00:02:09,833 --> 00:02:15,666 experience management systems, the Litera Foundation, your SQL databases

35 00:02:15,666 --> 00:02:21,666 that powers your time -building platforms like Elite and AdRent, your custom

36 00:02:21,666 --> 00:02:26,666 homegrown applications where you might have custom databases designed for that.

37 00:02:26,666 --> 00:02:30,041 So knowledge lives beyond just documents.

38 00:02:30,041 --> 00:02:31,250 So KLapper...

39 00:02:31,250 --> 00:02:35,833 Design assistance, assistance that you can design with KLapper with no code.

40 00:02:35,833 --> 00:02:40,250 You can simply use our powerful connectors to connect to these databases, your

41 00:02:40,250 --> 00:02:41,666 You can simply use our powerful connectors to connect to these databases, your

42 00:02:41,666 --> 00:02:47,083 documents and systems, and just surface intelligence using the power of JourneyBI.

43 00:02:47,333 --> 00:02:49,416 So KLapper helps you design, create, and deploy a very intelligent assistant that

44 00:02:49,416 --> 00:02:55,083 So KLapper helps you design, create, and deploy a very intelligent assistant that

45 00:02:55,083 --> 00:02:55,500 So KLapper helps you design, create, and deploy a very intelligent assistant that

46 00:02:55,500 --> 00:02:58,083 you can use basically for Q &A.

47 00:02:58,083 --> 00:03:03,166 For example, you can ask it questions that is intelligence and uses the intelligence

48 00:03:03,166 --> 00:03:07,083 that it just gathered from those knowledge sources to answer your question in the

49 00:03:07,083 --> 00:03:09,791 most appropriate way with citations.

50 00:03:09,791 --> 00:03:14,083 Or you can even do things on your behalf to a true assistant.

51 00:03:14,083 --> 00:03:19,791 For example, creating a meeting on your behalf, doing time entry on your behalf,

52 00:03:19,791 --> 00:03:19,833 For example, creating a meeting on your behalf, doing time entry on your behalf,

53 00:03:20,000 --> 00:03:23,875 even applying for leave on your behalf, manage expense claims on your behalf,

54 00:03:23,875 --> 00:03:26,791 approved claims on your behalf, or even submit a claim on your behalf.

55 00:03:26,916 --> 00:03:30,583 So KLapper design assistants can not only surface knowledge, but they can also do

56 00:03:30,583 --> 00:03:32,083 So KLapper design assistants can not only surface knowledge, but they can also do

57 00:03:32,083 --> 00:03:36,166 actions, take actions, truly act as an assistant for an attorney.

58 00:03:36,166 --> 00:03:40,916 And all this can be done securely with our KLapper platform using the KLapper

59 00:03:40,916 --> 00:03:41,541 Builder.

60 00:03:41,541 --> 00:03:46,416 And the beauty about the KLapper platform itself is it's highly secure.

61 00:03:46,416 --> 00:03:52,166 It deploys and gets configured on the firm's Azure tenant.

62 00:03:52,166 --> 00:03:57,916 This is a major differentiator for some of the other possible competitors out there

63 00:03:57,916 --> 00:04:04,125 because all your data that KLapper learns lives in your tenant.

64 00:04:04,125 --> 00:04:04,166 because all your data that KLapper learns lives in your tenant.

65 00:04:04,333 --> 00:04:06,875 So we as a vendor, we do not have access to it and neither does anybody else except

66 00:04:06,875 --> 00:04:09,416 So we as a vendor, we do not have access to it and neither does anybody else except

67 00:04:09,416 --> 00:04:13,375 for the Microsoft Azure tenant that you provisioned as part of the Microsoft Azure

68 00:04:13,375 --> 00:04:18,958 subscription that you have and KLapper data, all its learnings just stays there.

69 00:04:19,250 --> 00:04:22,750 And the last but not the least, the most important part of KLapper is this pricing

70 00:04:22,750 --> 00:04:24,291 model, which makes it available to everybody.

71 00:04:24,291 --> 00:04:26,666 model, which makes it available to everybody.

72 00:04:26,666 --> 00:04:30,208 One of the key problems with AI and its adoption is cost.

73 00:04:30,208 --> 00:04:36,166 It's so expensive for mid -sized firms, even larger firms, to adapt and adopt an

74 00:04:36,166 --> 00:04:37,500 AI -based assistant slash helper.

75 00:04:37,500 --> 00:04:40,291 AI -based assistant slash helper.

76 00:04:40,291 --> 00:04:46,041 With KLapper, you can design assistants that is based on a very cost -effective,

77 00:04:46,041 --> 00:04:47,875 active user model.

78 00:04:47,875 --> 00:04:51,625 meaning that you only pay for the users that use KLapper.

79 00:04:51,958 --> 00:04:54,541 So the three prong approach makes KLapper unique.

80 00:04:54,541 --> 00:04:55,416 No code, highly connected learning model that can learn off your data sources, your

81 00:04:55,416 --> 00:04:59,791 No code, highly connected learning model that can learn off your data sources, your

82 00:04:59,791 --> 00:05:04,958 actual knowledge sources within your firm, not just documents, beyond documents.

83 00:05:05,041 --> 00:05:10,625 A highly secure deployment infrastructure, meaning that KLapper lives within your

84 00:05:10,625 --> 00:05:15,041 Azure tenant, within your domain, so no one has access to the data it learns

85 00:05:15,041 --> 00:05:16,333 except for you.

86 00:05:16,500 --> 00:05:22,875 And third is cost effective, which means that anybody can afford a news KLapper to

87 00:05:22,875 --> 00:05:24,833 design your AI strategy.

88 00:05:25,250 --> 00:05:26,583 You've covered a lot there.

89 00:05:26,583 --> 00:05:31,041 Let me break down a little bit more some of the details around this.

90 00:05:31,041 --> 00:05:35,541 First of all, who are the kind of the target users for this within a law firm?

91 00:05:35,708 --> 00:05:38,458 So KLapper has two components to it.

92 00:05:38,458 --> 00:05:41,583 One component is designing the assistant itself.

93 00:05:42,041 --> 00:05:47,125 Assistant design, meaning the, in the olden days or five, seven years ago, this

94 00:05:47,125 --> 00:05:49,250 term we used to use was chatbots.

95 00:05:49,250 --> 00:05:53,625 Now we don't no longer use that because of many different reasons, but obviously

96 00:05:53,625 --> 00:05:59,583 because of the fact that the new General AI models and the term that often people

97 00:05:59,583 --> 00:06:00,583 use is assistant.

98 00:06:00,583 --> 00:06:02,208 So I'm going to continue to use assistant.

99 00:06:02,208 --> 00:06:04,708 So there are two aspects of KLapper.

100 00:06:04,708 --> 00:06:08,750 One is an assistant builder and an assistant consumer.

101 00:06:08,916 --> 00:06:14,166 The assistant builder, the target audience for that could be both non -technical and

102 00:06:14,166 --> 00:06:15,666 technical people within your firm.

103 00:06:15,666 --> 00:06:21,166 So a non -technical person could be a knowledge attorney who has limited to

104 00:06:21,166 --> 00:06:26,083 decent knowledge in IT, which means that he or she has built something before using

105 00:06:26,083 --> 00:06:27,833 say a power app with Microsoft, like a form or a simple workflow or it's a little

106 00:06:27,833 --> 00:06:32,458 say a power app with Microsoft, like a form or a simple workflow or it's a little

107 00:06:32,458 --> 00:06:33,583 bit technical.

108 00:06:33,583 --> 00:06:36,750 or simply a completely non -technical person who is really focused on knowledge.

109 00:06:36,750 --> 00:06:38,750 or simply a completely non -technical person who is really focused on knowledge.

110 00:06:38,750 --> 00:06:42,708 So, Klackware Assistants can be built by both non -technical and technical

111 00:06:42,708 --> 00:06:46,291 knowledge workers, knowledge attorneys, knowledge managers, innovations

112 00:06:46,291 --> 00:06:48,458 professionals, and IT.

113 00:06:48,458 --> 00:06:50,958 So, you can simply use a drag -and -drop model that helps you design an Assistant

114 00:06:50,958 --> 00:06:53,250 So, you can simply use a drag -and -drop model that helps you design an Assistant

115 00:06:53,250 --> 00:06:57,500 connected to your line of business data, your time and billing data, your DMS

116 00:06:57,500 --> 00:06:58,666 within seconds.

117 00:06:58,750 --> 00:07:02,833 Once you configure and design your assistant, you're tested within the

118 00:07:02,833 --> 00:07:03,541 sandbox.

119 00:07:03,541 --> 00:07:05,291 And then you deploy that for your end user consumption in a channel, like a Microsoft

120 00:07:05,291 --> 00:07:09,541 And then you deploy that for your end user consumption in a channel, like a Microsoft

121 00:07:09,541 --> 00:07:15,916 team channel or a Zoom channel or as a Windows app.

122 00:07:15,916 --> 00:07:21,500 So the idea is that you design the assistant as a knowledge professional, and

123 00:07:21,500 --> 00:07:26,458 then you deploy that assistant on any platform where knowledge consumption

124 00:07:26,458 --> 00:07:27,500 happens.

125 00:07:27,666 --> 00:07:31,125 And that could be on a website, that could be on your SharePoint Internet teams, as I

126 00:07:31,125 --> 00:07:31,916 said before.

127 00:07:31,916 --> 00:07:37,500 So the end users or the attorneys or the partners, associates, the interns, those

128 00:07:37,500 --> 00:07:39,583 are the consumers of KLapper.

129 00:07:39,583 --> 00:07:45,000 Even shared services folks like HR, finance, marketing, basically depends on

130 00:07:45,000 --> 00:07:45,208 the reason you created the assistant for that can be consumed by any employee

131 00:07:45,208 --> 00:07:47,583 the reason you created the assistant for that can be consumed by any employee

132 00:07:47,583 --> 00:07:50,000 the reason you created the assistant for that can be consumed by any employee

133 00:07:50,000 --> 00:07:51,375 within your organization.

134 00:07:51,708 --> 00:07:55,708 Ragav, I assume that the builders can build multiple assistants to address

135 00:07:55,708 --> 00:07:57,500 Ragav, I assume that the builders can build multiple assistants to address

136 00:07:57,500 --> 00:07:58,375 multiple scenarios.

137 00:07:58,375 --> 00:08:04,458 Can you give examples of some of the scenarios that firms would use this for?

138 00:08:04,458 --> 00:08:06,000 Sure, yeah.

139 00:08:06,375 --> 00:08:11,583 So typically, as I said, KLapper is an assistant builder platform, meaning that

140 00:08:11,583 --> 00:08:18,000 you're designing an assistant for a specific or specific use cases, either a

141 00:08:18,000 --> 00:08:19,791 specific use case or use cases.

142 00:08:19,791 --> 00:08:25,500 Let me give you an example of a generic use case like a My HR Assistant.

143 00:08:25,625 --> 00:08:30,500 With a My HR Assistant, you can create a very powerful assistant that can...

144 00:08:30,500 --> 00:08:31,541 With a My HR Assistant, you can create a very powerful assistant that can...

145 00:08:31,708 --> 00:08:35,041 answer questions related to HR within your firm, could help you with onboarding

146 00:08:35,041 --> 00:08:36,625 answer questions related to HR within your firm, could help you with onboarding

147 00:08:36,625 --> 00:08:37,541 process, could apply for leave on your behalf, could check on leave balance on

148 00:08:37,541 --> 00:08:41,541 process, could apply for leave on your behalf, could check on leave balance on

149 00:08:41,541 --> 00:08:42,333 your behalf, and perform a lot of different HR duties on behalf of the

150 00:08:42,333 --> 00:08:45,750 your behalf, and perform a lot of different HR duties on behalf of the

151 00:08:45,750 --> 00:08:47,791 attorney, like the ones I just mentioned.

152 00:08:47,875 --> 00:08:53,500 So that my HR assistant, the HR professional in your firm, maybe the HR...

153 00:08:53,500 --> 00:08:57,916 consultant, the director, whoever the person is, would simply go to KLapper

154 00:08:57,916 --> 00:08:59,125 Builder platform, create a new assistant, call it MyHR, for example, and then

155 00:08:59,125 --> 00:09:03,583 Builder platform, create a new assistant, call it MyHR, for example, and then

156 00:09:03,583 --> 00:09:07,083 connect it to your HR system using our connectors.

157 00:09:07,125 --> 00:09:11,791 For example, if you use ADP or if you use PeopleSoft, you can simply connect that

158 00:09:11,791 --> 00:09:12,291 For example, if you use ADP or if you use PeopleSoft, you can simply connect that

159 00:09:12,291 --> 00:09:17,583 assistant to those applications to get and set data, meaning that you can get

160 00:09:17,583 --> 00:09:18,416 information about

161 00:09:18,416 --> 00:09:19,250 information about

162 00:09:19,250 --> 00:09:21,333 How much PTO do I have left?

163 00:09:21,375 --> 00:09:23,125 Or you can set information.

164 00:09:23,125 --> 00:09:26,583 Can I apply for a leave on a specific day or a duration of days?

165 00:09:26,583 --> 00:09:29,166 Can I apply for a leave on a specific day or a duration of days?

166 00:09:29,166 --> 00:09:34,208 You can even train that assistant on data, which are a document like policies and

167 00:09:34,208 --> 00:09:39,750 procedures that may live in, say, iManage or NetDocuments or just in SharePoint.

168 00:09:39,750 --> 00:09:39,875 procedures that may live in, say, iManage or NetDocuments or just in SharePoint.

169 00:09:39,875 --> 00:09:42,958 So you can simply use one of our connectors, iManage connector, or

170 00:09:42,958 --> 00:09:45,250 SharePoint connector, or NetDocuments connector.

171 00:09:45,250 --> 00:09:46,750 Train that assistant.

172 00:09:46,750 --> 00:09:51,666 on the document library or the workspace and all the documents within the workspace

173 00:09:51,666 --> 00:09:56,083 or document library so that when people ask questions about leave policy within my

174 00:09:56,083 --> 00:09:58,000 or document library so that when people ask questions about leave policy within my

175 00:09:58,000 --> 00:09:58,541 firm or any kind of discrimination policy within my firm or any kind of policy and

176 00:09:58,541 --> 00:10:03,791 firm or any kind of discrimination policy within my firm or any kind of policy and

177 00:10:03,791 --> 00:10:07,958 procedure that exists with my firm, KLapper, my HR assistants already learn

178 00:10:07,958 --> 00:10:09,500 from those sources.

179 00:10:09,500 --> 00:10:14,666 So when you deploy this to say your HR team in Teams,

180 00:10:14,666 --> 00:10:20,833 or simply make it available as a chatbot in your intranet on your HR portal, users,

181 00:10:20,833 --> 00:10:21,750 or simply make it available as a chatbot in your intranet on your HR portal, users,

182 00:10:21,750 --> 00:10:25,250 attorneys, just staff members can simply click on it and interact with it.

183 00:10:25,250 --> 00:10:30,958 They can ask questions on your corporate policies or on HR, or they can ask you to

184 00:10:30,958 --> 00:10:36,791 do stuff on the attorney's behalf, like apply for a leave or check on the balance.

185 00:10:36,791 --> 00:10:41,125 Basically, consumer of that assistant once you deploy it in a channel they consume.

186 00:10:41,250 --> 00:10:43,208 So that's an example of my HR system.

187 00:10:43,208 --> 00:10:45,750 For example, a different use case could be a time and billing assistant.

188 00:10:45,750 --> 00:10:47,416 For example, a different use case could be a time and billing assistant.

189 00:10:47,500 --> 00:10:49,833 A time and billing assistant could be very useful.

190 00:10:49,833 --> 00:10:54,666 And this is a very common use case because as part of a couple of other companies

191 00:10:54,666 --> 00:11:00,166 that we build a lot of intranets for firms, intranets that intranet portals

192 00:11:00,166 --> 00:11:04,375 that basically surface data intelligence.

193 00:11:04,541 --> 00:11:08,791 So the ability to surface that data intelligence that is stored within my time

194 00:11:08,791 --> 00:11:10,083 and billing platform.

195 00:11:10,375 --> 00:11:16,791 or even apply or enter time sheets and automate the process or proactively

196 00:11:16,791 --> 00:11:20,583 deliver alerts to you based on some key data metrics.

197 00:11:20,625 --> 00:11:21,916 Give me an example of that.

198 00:11:21,916 --> 00:11:26,958 You can design a time and billing assistant and can know who the person is.

199 00:11:26,958 --> 00:11:28,708 So you make it persona driven and user driven, meaning that it only shows you the

200 00:11:28,708 --> 00:11:31,041 So you make it persona driven and user driven, meaning that it only shows you the

201 00:11:31,041 --> 00:11:34,541 data you're supposed to see from your time and billing platform.

202 00:11:34,541 --> 00:11:37,708 And you can simply connect this assistant as the assistant builder.

203 00:11:37,791 --> 00:11:41,333 to your time and billing platform database, let's say SQL, let's say Elite

204 00:11:41,333 --> 00:11:41,916 SQL, and it let it learn of the data.

205 00:11:41,916 --> 00:11:44,041 SQL, and it let it learn of the data.

206 00:11:44,083 --> 00:11:47,833 And you design the assistant, you fine tune the assistant prompt engineering.

207 00:11:47,833 --> 00:11:51,708 And basically the purpose of this assistant is to, is a reactively a

208 00:11:51,708 --> 00:11:55,666 proactive deliver data alerts to you, the data that you care about.

209 00:11:55,666 --> 00:12:00,500 For example, my missing time sheets for the week, for example, or my billing's

210 00:12:00,500 --> 00:12:01,375 here to date.

211 00:12:01,583 --> 00:12:04,750 The ability to get that data or the matters that I'm working on, right?

212 00:12:04,750 --> 00:12:05,458 The ability to get that data or the matters that I'm working on, right?

213 00:12:05,458 --> 00:12:09,416 or just to get the status of a recent matter that I was involved in.

214 00:12:09,416 --> 00:12:14,833 So to have that instant data point access, either reactively that I'm asking the

215 00:12:14,833 --> 00:12:17,333 assistant as an attorney on a team chat or a chat interface in the SharePoint portal,

216 00:12:17,333 --> 00:12:20,208 assistant as an attorney on a team chat or a chat interface in the SharePoint portal,

217 00:12:20,208 --> 00:12:25,333 wherever it surfaced, the ability to ask that or reactively ask that or proactively

218 00:12:25,333 --> 00:12:30,041 being delivered that alert in my team chat by KLapper Assistant.

219 00:12:30,125 --> 00:12:33,916 So these are some of the use cases that you can design without writing a single

220 00:12:33,916 --> 00:12:37,750 line of code where KLapper is connected, seamlessly connected through our

221 00:12:37,750 --> 00:12:40,166 connectors, through a line of business data.

222 00:12:40,166 --> 00:12:45,083 It learns of the datasets using the PowerJet API and either does stuff on your

223 00:12:45,083 --> 00:12:46,791 behalf or answers stuff on your behalf, questions and answers.

224 00:12:46,791 --> 00:12:49,166 behalf or answers stuff on your behalf, questions and answers.

225 00:12:49,458 --> 00:12:52,875 You talk a lot about these intelligent connectors as one of the unique features

226 00:12:52,875 --> 00:12:54,750 of this application.

227 00:12:54,750 --> 00:13:00,083 How easy is it to set up those connections using your intelligent connectors?

228 00:13:00,291 --> 00:13:01,541 Great question.

229 00:13:01,833 --> 00:13:06,000 So our intelligent connectors, the reason why we call them intelligent connectors is

230 00:13:06,000 --> 00:13:07,666 because they're truly intelligent.

231 00:13:07,666 --> 00:13:10,708 And if you notice, I continue to use the word no code because one of the key points

232 00:13:10,708 --> 00:13:12,750 And if you notice, I continue to use the word no code because one of the key points

233 00:13:12,750 --> 00:13:17,041 of KLapper is a platform designed for non -technical people, meaning that creation

234 00:13:17,041 --> 00:13:18,750 of KLapper is a platform designed for non -technical people, meaning that creation

235 00:13:18,750 --> 00:13:24,416 of an assistant is simply clicking on a button that says create assistant and it

236 00:13:24,416 --> 00:13:26,166 has a name and a description.

237 00:13:26,250 --> 00:13:28,333 Once you create that assistant, empowering that assistant with a knowledge source

238 00:13:28,333 --> 00:13:30,916 Once you create that assistant, empowering that assistant with a knowledge source

239 00:13:30,916 --> 00:13:35,375 from an Imanage workspace is simply clicking on a button called Knowledge

240 00:13:35,375 --> 00:13:36,208 Space and picking Imanage as a connector and then simply picking your source where

241 00:13:36,208 --> 00:13:40,541 Space and picking Imanage as a connector and then simply picking your source where

242 00:13:40,541 --> 00:13:41,875 you want to train it from.

243 00:13:42,041 --> 00:13:44,958 Using our really simple to use content browser window, you can simply browse the

244 00:13:44,958 --> 00:13:47,916 Using our really simple to use content browser window, you can simply browse the

245 00:13:47,916 --> 00:13:51,750 content that you care about in Imanage, taking an example.

246 00:13:52,125 --> 00:13:55,750 workspace that you care about, you can simply search for the workspace, find that

247 00:13:55,750 --> 00:13:58,083 folder that you want to train the content from, and pick that folder, take it, and

248 00:13:58,083 --> 00:14:00,458 folder that you want to train the content from, and pick that folder, take it, and

249 00:14:00,458 --> 00:14:01,583 just say train.

250 00:14:01,583 --> 00:14:02,708 That's it.

251 00:14:02,708 --> 00:14:04,333 It's that simple.

252 00:14:04,333 --> 00:14:04,541 So the design behind KLapper, if you compare it with, say, some of the other

253 00:14:04,541 --> 00:14:08,958 So the design behind KLapper, if you compare it with, say, some of the other

254 00:14:08,958 --> 00:14:13,333 products out there, including Microsoft Co -Pilot, which is a pretty technical tool

255 00:14:13,333 --> 00:14:18,083 if you want to design an assistant, we designed an assistant builder platform

256 00:14:18,083 --> 00:14:19,583 with attorneys in mind.

257 00:14:19,833 --> 00:14:21,291 with knowledge managers in mind.

258 00:14:21,291 --> 00:14:24,416 Because of our experience working with attorneys, working with knowledge

259 00:14:24,416 --> 00:14:29,958 managers, we understand the nuances around all the technical terms that you're hit

260 00:14:29,958 --> 00:14:34,375 with when you're designing AI power bots and agents and assistants.

261 00:14:34,375 --> 00:14:38,500 So with our intelligent connectors, it literally is extremely simple.

262 00:14:38,500 --> 00:14:41,916 And some of the videos that we publish on the internet will showcase that.

263 00:14:41,916 --> 00:14:47,875 How easy it is to simply pick, point, click, configure, and click on the train

264 00:14:47,875 --> 00:14:48,333 button.

265 00:14:48,333 --> 00:14:50,000 And just like that.

266 00:14:50,000 --> 00:14:53,875 Using the Power of Journey BI, we learn the content, the KLapper assistant learns

267 00:14:53,875 --> 00:14:58,333 the content in that context so you can ask good questions.

268 00:14:58,833 --> 00:15:04,166 So Ragav, if I'm a law firm innovation professional or KM professional and I'm

269 00:15:04,166 --> 00:15:08,833 listening to this interview right now and I say, sounds interesting, how do I get

270 00:15:08,833 --> 00:15:09,416 started?

271 00:15:09,416 --> 00:15:10,583 How do they get started?

272 00:15:10,583 --> 00:15:14,416 What's involved in getting this set up and deployed in the first instance?

273 00:15:14,416 --> 00:15:14,458 What's involved in getting this set up and deployed in the first instance?

274 00:15:14,583 --> 00:15:15,125 So KLapper deploys on your Azure platform on your Azure tenant, you are meaning the

275 00:15:15,125 --> 00:15:20,250 So KLapper deploys on your Azure platform on your Azure tenant, you are meaning the

276 00:15:20,250 --> 00:15:21,458 firm's Azure tenant.

277 00:15:21,458 --> 00:15:26,250 We do offer a hosted model, but we recommend that you go with this model that

278 00:15:26,250 --> 00:15:31,208 be strongly endorsed to take KLapper and deployed on your Azure tenant.

279 00:15:31,375 --> 00:15:32,791 So to get started, KLapper installation literally takes minutes.

280 00:15:32,791 --> 00:15:36,041 So to get started, KLapper installation literally takes minutes.

281 00:15:36,041 --> 00:15:40,291 We've thought through the entire process from start to beginning as long as.

282 00:15:40,458 --> 00:15:44,333 The firm's IT can provision the prerequisites for KLapper, the Azure

283 00:15:44,333 --> 00:15:45,583 The firm's IT can provision the prerequisites for KLapper, the Azure

284 00:15:45,583 --> 00:15:47,541 tenant space that it needs, the Azure OpenAI subscription that it needs.

285 00:15:47,541 --> 00:15:50,666 tenant space that it needs, the Azure OpenAI subscription that it needs.

286 00:15:50,791 --> 00:15:53,416 Deploying KLapper takes minutes.

287 00:15:53,500 --> 00:15:54,958 Once it's deployed, the next step is to work with our customer success team to

288 00:15:54,958 --> 00:15:59,125 Once it's deployed, the next step is to work with our customer success team to

289 00:15:59,125 --> 00:15:59,583 Once it's deployed, the next step is to work with our customer success team to

290 00:15:59,583 --> 00:16:03,458 help understand how the KLapper Builder works.

291 00:16:03,708 --> 00:16:08,666 Now, again, as I repeatedly said during this podcast, we design software for

292 00:16:08,666 --> 00:16:11,041 lawyers, for knowledge attorneys.

293 00:16:11,166 --> 00:16:15,375 So as soon as you look at the KLapper UI, the user interface, you would see that

294 00:16:15,375 --> 00:16:16,875 it's super simple.

295 00:16:16,875 --> 00:16:22,083 You would not need a user guide to use KLapper, to create a virtual assistant, to

296 00:16:22,083 --> 00:16:25,916 empower the virtual assistant, literally connecting to an iMinute source or a

297 00:16:25,916 --> 00:16:29,208 NetDocument source or a SQL source or a SharePoint source.

298 00:16:29,333 --> 00:16:33,583 or even a modern web application microservice, I just threw a lot of tech

299 00:16:33,583 --> 00:16:38,625 terms there, source, or even SQL source, SQL server database source.

300 00:16:38,625 --> 00:16:41,541 Connecting to those sources is really simple.

301 00:16:41,541 --> 00:16:43,625 Point, click, configure, connect.

302 00:16:43,625 --> 00:16:47,958 The additional training that we provide is around formatting of the data and prompt

303 00:16:47,958 --> 00:16:48,416 engineering.

304 00:16:48,416 --> 00:16:54,916 How do you design prompts that helps KLapper understand the queries better so

305 00:16:54,916 --> 00:16:57,000 it can answer the queries better?

306 00:16:57,000 --> 00:17:00,541 And once, when it answers the queries better, how does it answer it?

307 00:17:00,541 --> 00:17:04,125 How does the formatting of the answer work?

308 00:17:04,125 --> 00:17:08,041 And the formatting of those answers can, you don't need to learn JSON.

309 00:17:08,041 --> 00:17:09,708 You don't need to learn all those things.

310 00:17:09,708 --> 00:17:17,125 You can simply write English language texts and say, look, format in bold amount

311 00:17:17,125 --> 00:17:18,125 in dollars.

312 00:17:18,125 --> 00:17:19,791 Literally a text like that.

313 00:17:19,791 --> 00:17:24,833 And KLapper learns that, look, if I encounter a dollar amount in my output, I

314 00:17:24,833 --> 00:17:26,291 should format that in bold.

315 00:17:26,541 --> 00:17:30,541 So we've talked through the whole process of how the input formatting input

316 00:17:30,541 --> 00:17:33,958 prompting works, how the output formatting works.

317 00:17:33,958 --> 00:17:37,750 No need to learn JSON, no need to learn variables, no need to learn all that stuff

318 00:17:37,750 --> 00:17:41,708 that, for example, in power automated you need to do or co -pilot a studio you need

319 00:17:41,708 --> 00:17:42,708 to work on.

320 00:17:42,708 --> 00:17:45,500 With KLapper, all that stuff is just plain old simple English.

321 00:17:45,500 --> 00:17:49,541 So we'll help you, we'll train you with our customer success team to do input and

322 00:17:49,541 --> 00:17:51,166 output prompt engineering.

323 00:17:51,166 --> 00:17:53,625 And really it's a joined effort.

324 00:17:53,625 --> 00:17:55,500 So from that point onwards,

325 00:17:55,500 --> 00:17:59,416 We are available from a consulting perspective for the firm so that we can

326 00:17:59,416 --> 00:18:02,833 help you design some advanced skills for KLapper.

327 00:18:02,833 --> 00:18:08,208 If that's a use case that you want, we can also jointly build together a proof of

328 00:18:08,208 --> 00:18:12,625 concept that you may have that you want KLapper to learn from sources so that it

329 00:18:12,625 --> 00:18:14,041 can do stuff or answer stuff.

330 00:18:14,041 --> 00:18:17,916 We can jointly design that for you together as part of a service.

331 00:18:17,916 --> 00:18:20,000 But there are many ways to engage.

332 00:18:20,000 --> 00:18:21,625 Our bottom line is this.

333 00:18:21,625 --> 00:18:24,208 We believe KLapper is an amazing product.

334 00:18:24,666 --> 00:18:28,791 We've designed KLapper based on our learnings from doing AI powered software

335 00:18:28,791 --> 00:18:30,541 over the last five years.

336 00:18:30,875 --> 00:18:34,791 We've designed a software for attorneys and knowledge managers and knowledge

337 00:18:34,791 --> 00:18:35,875 workers.

338 00:18:35,875 --> 00:18:40,041 So working with our customer success team, we can make sure you're successful.

339 00:18:40,500 --> 00:18:41,833 I guess we're about out of time.

340 00:18:41,833 --> 00:18:45,333 Anything else you'd like listeners to know about KLapper?

341 00:18:45,541 --> 00:18:48,875 I think you covered most of it with your questions and hopefully answered those in

342 00:18:48,875 --> 00:18:49,125 I think you covered most of it with your questions and hopefully answered those in

343 00:18:49,125 --> 00:18:50,291 an informative way.

344 00:18:50,291 --> 00:18:54,208 The one thing I want to leave you from a KLapper perspective, the key value

345 00:18:54,208 --> 00:18:57,791 proposition of KLapper, truly simplicity and our know how of the law, especially

346 00:18:57,791 --> 00:19:00,833 proposition of KLapper, truly simplicity and our know how of the law, especially

347 00:19:00,833 --> 00:19:05,708 the legal communities, because if we build intranets, we build extranets, we build

348 00:19:05,708 --> 00:19:09,583 custom solutions, we understand the nuances of data from data.

349 00:19:09,625 --> 00:19:11,916 So in terms of KLapper,

350 00:19:11,916 --> 00:19:15,958 connecting to these datasets, extracting intelligence from the dataset, literally

351 00:19:15,958 --> 00:19:16,708 connecting to these datasets, extracting intelligence from the dataset, literally

352 00:19:16,708 --> 00:19:18,125 is a point, click and configure.

353 00:19:18,125 --> 00:19:24,333 So reach out to us, help us help you launch your next AI big thing at the idea

354 00:19:24,333 --> 00:19:24,958 firm.

355 00:19:24,958 --> 00:19:27,250 KLapper truly is an amazing product.

356 00:19:27,250 --> 00:19:28,541 I can't wait to show you.

357 00:19:28,541 --> 00:19:29,625 Thank you so much.

358 00:19:30,000 --> 00:19:32,208 Thanks so much for being with us today.

359 00:19:32,208 --> 00:19:36,750 We've been speaking with Ragav Jagannathan, the CEO of KLoBot about

360 00:19:36,750 --> 00:19:37,333 KLapper.

361 00:19:37,333 --> 00:19:41,750 That's with K -L -A -P -P -E -R, just released last week.

362 00:19:41,750 --> 00:19:42,958 That's it for today's episode.

363 00:19:42,958 --> 00:19:47,125 If you enjoyed it, please subscribe wherever you get your podcasts or on

364 00:19:47,125 --> 00:19:50,291 YouTube at LawNext underscore PR.

365 00:19:50,291 --> 00:19:55,000 You can also find all of the episodes on the LawNext Legal Tech Directory under the

366 00:19:55,000 --> 00:19:56,416 resources tab.

367 00:19:56,416 --> 00:19:58,208 This is Bob Ambrogi.

368 00:19:58,375 --> 00:20:00,291 Thanks so much for listening.