1 00:00:00,000 --> 00:00:04,670 Welcome welcome welcome to the deep dive the show that's well your shortcut to 2 00:00:04,670 --> 00:00:06,140 being genuinely well informed 3 00:00:06,140 --> 00:00:09,680 We cut through the noise to get you straight to the insights that matter most 4 00:00:09,680 --> 00:00:14,560 Before we jump into today's topic though a huge shout out to our supporter safe 5 00:00:14,560 --> 00:00:14,880 server 6 00:00:14,880 --> 00:00:18,900 They're the experts you want for software hosting and they're a real partner in 7 00:00:18,900 --> 00:00:20,320 digital transformation 8 00:00:20,320 --> 00:00:24,330 Basically helping you level up your tech and navigate that whole complex digital 9 00:00:24,330 --> 00:00:27,060 world if you're looking to empower your projects 10 00:00:27,060 --> 00:00:32,770 Definitely check them out at WWW dot safe server dot DE again. That's WWW dot safe 11 00:00:32,770 --> 00:00:33,920 server dot DE 12 00:00:33,920 --> 00:00:39,850 Okay, so let's be real in today's world. We're just swimming maybe drowning in 13 00:00:39,850 --> 00:00:40,760 information, right? 14 00:00:40,760 --> 00:00:43,560 Whether you're trying to find out one perfect pair of shoes online or maybe 15 00:00:43,560 --> 00:00:45,380 pinpoint a specific song in a giant music library 16 00:00:45,380 --> 00:00:48,600 Or digging for that crucial file buried somewhere. We all want the same thing 17 00:00:48,600 --> 00:00:51,240 instant access effortless find exactly what you need right away 18 00:00:51,240 --> 00:00:54,480 No messing around and today we're taking a deep dive into type sense 19 00:00:54,480 --> 00:00:57,980 It's a really powerful open source tool designed specifically to make those search 20 00:00:57,980 --> 00:01:00,340 experiences less frustrating and honestly delightful 21 00:01:00,340 --> 00:01:03,980 That's a great way to put it. Yeah type sense is fundamentally an open source 22 00:01:03,980 --> 00:01:05,520 lightning fast search engine 23 00:01:05,520 --> 00:01:10,940 But it's like built for mere mortals. That's how they put it. The main goal is top 24 00:01:10,940 --> 00:01:11,640 performance 25 00:01:11,640 --> 00:01:13,820 Absolutely, but just as important as ease of use 26 00:01:13,820 --> 00:01:16,320 It's about making sure you don't need you know 27 00:01:16,320 --> 00:01:20,820 A PhD or a huge dedicated team to get fantastic search working or even just to 28 00:01:20,820 --> 00:01:22,340 understand what it can do it kind of 29 00:01:22,560 --> 00:01:25,300 Demystify search deck. I like that for mere mortals 30 00:01:25,300 --> 00:01:26,300 Okay 31 00:01:26,300 --> 00:01:30,360 So our mission for this deep dive unpack what type sense is see how it stacks up 32 00:01:30,360 --> 00:01:32,720 against the big often way more complex 33 00:01:32,720 --> 00:01:36,450 Players out there and figure out why it's getting so much attention for making 34 00:01:36,450 --> 00:01:37,360 search powerful 35 00:01:37,360 --> 00:01:40,640 But also accessible and well efficient for pretty much everyone 36 00:01:40,640 --> 00:01:44,210 We've gathered insights straight from the type sense github repository and their 37 00:01:44,210 --> 00:01:45,080 official website 38 00:01:45,080 --> 00:01:46,520 So we're getting it from the source 39 00:01:46,520 --> 00:01:51,090 Think of this as your fast track to understanding what might be the next big thing 40 00:01:51,090 --> 00:01:51,600 in search 41 00:01:51,720 --> 00:01:53,720 Okay, let's uh, let's make this real 42 00:01:53,720 --> 00:01:58,070 think about those everyday search frustrations, you know the feeling you type 43 00:01:58,070 --> 00:02:00,300 something hit enter and you wait or 44 00:02:00,300 --> 00:02:05,060 Worse you make one tiny typo just one letter off and boom no results found so 45 00:02:05,060 --> 00:02:05,640 annoying 46 00:02:05,640 --> 00:02:09,720 Or maybe you get too much back just a flood of stuff that isn't quite right and you 47 00:02:09,720 --> 00:02:10,400 feel totally lost 48 00:02:10,400 --> 00:02:15,330 We want fast easy precise, but search often feels more like I don't know digging 49 00:02:15,330 --> 00:02:17,760 through a messy attic. Oh, absolutely 50 00:02:17,760 --> 00:02:21,280 It's a common pain point and that's exactly where type sense comes in is this 51 00:02:22,000 --> 00:02:25,400 Elegant solution at its core. It's a fast 52 00:02:25,400 --> 00:02:29,060 typo-tolerant in memory fuzzy search engine 53 00:02:29,060 --> 00:02:33,170 Okay, let's break that down a bit because those terms are key to the no PhD 54 00:02:33,170 --> 00:02:34,440 required idea fuzzy 55 00:02:34,440 --> 00:02:38,360 Just means it's forgiving you misspell something only remember part of a name 56 00:02:38,360 --> 00:02:42,240 Type sense is smart enough to often guess what you meant and still find it 57 00:02:42,240 --> 00:02:46,670 So it understands intent not just the exact letters I type exactly it gets what you 58 00:02:46,670 --> 00:02:48,320 meant not just what you typed 59 00:02:48,400 --> 00:02:53,070 That's huge for user experience and then in memory. This is really interesting 60 00:02:53,070 --> 00:02:54,260 because it's core to its speed 61 00:02:54,260 --> 00:02:58,970 It means the search index the data it's searching is loaded right into the computer's 62 00:02:58,970 --> 00:03:00,560 RAM. It's working memory 63 00:03:00,560 --> 00:03:04,190 Okay, so like keeping the important stuff right on your desk instead of filed away 64 00:03:04,190 --> 00:03:06,720 somewhere precisely imagine looking for a book 65 00:03:06,720 --> 00:03:11,200 Is it faster to grab it off the shelf next to you or go search boxes in the garage 66 00:03:11,200 --> 00:03:11,580 in? 67 00:03:11,580 --> 00:03:14,040 Memory is having it right there on the shelf 68 00:03:14,440 --> 00:03:18,600 Super fast lookups. It's all designed to cut complexity and give you that genuinely 69 00:03:18,600 --> 00:03:22,080 delightful fast search without needing deep technical expertise 70 00:03:22,080 --> 00:03:27,100 That attic versus bookshelf analogy really clicks. Okay, so here's where it gets 71 00:03:27,100 --> 00:03:29,100 like really interesting for a lot of folks 72 00:03:29,100 --> 00:03:31,280 Type sense often gets mentioned as an alternative 73 00:03:31,280 --> 00:03:36,440 Maybe even a better one sometimes compared to big names like elastic search or Algolia 74 00:03:36,440 --> 00:03:40,960 For someone starting out or even a developer looking for a simpler way. What really 75 00:03:40,960 --> 00:03:42,960 sets type sense apart? Why choose it? 76 00:03:43,080 --> 00:03:46,640 Yeah, the differences are pretty stark when you look at actually using them take 77 00:03:46,640 --> 00:03:48,520 elastic search. It's powerful 78 00:03:48,520 --> 00:03:54,800 No doubt hue scale complex queries. It can do a lot, but it's often a really big 79 00:03:54,800 --> 00:03:56,240 piece of software 80 00:03:56,240 --> 00:04:01,240 Setting it up tuning it scaling it that could be complex often needs specialized 81 00:04:01,240 --> 00:04:01,600 teams 82 00:04:01,600 --> 00:04:06,530 Significant ongoing effort so a big investment in just managing the search part, 83 00:04:06,530 --> 00:04:06,680 right? 84 00:04:06,680 --> 00:04:10,370 You have to ask do you want your team focused on managing search infrastructure or 85 00:04:10,370 --> 00:04:11,600 building your actual product? 86 00:04:11,600 --> 00:04:14,080 Type sense flips that it's designed to be lightweight 87 00:04:14,080 --> 00:04:18,480 But still really powerful and scalable and it comes as a single binary one file 88 00:04:18,480 --> 00:04:19,240 seriously 89 00:04:19,240 --> 00:04:23,840 Yeah, pretty much you download one file run it and you're basically ready to go. No 90 00:04:23,840 --> 00:04:24,920 complex installs 91 00:04:24,920 --> 00:04:29,640 No fighting dependencies. It's plug-and-play for search. The focus is really on 92 00:04:29,640 --> 00:04:33,480 Developer happiness a clean well documented API 93 00:04:33,480 --> 00:04:37,310 That's a toolkit for programmers to interact with it and the API is designed to be 94 00:04:37,310 --> 00:04:38,240 straightforward 95 00:04:38,240 --> 00:04:42,540 So it you know, it just works well out of the box less tinkering needed Wow 96 00:04:42,540 --> 00:04:46,770 Okay, one file install sounds amazing for anyone who's struggled with setup before 97 00:04:46,770 --> 00:04:49,040 so what about Algolia then? 98 00:04:49,040 --> 00:04:52,290 That's often a hosted service people know how does type sense compare there, 99 00:04:52,290 --> 00:04:53,920 especially cost and flexibility wise? 100 00:04:53,920 --> 00:04:57,400 That's a really important comparison. Algolia is great performs 101 00:04:57,400 --> 00:05:01,040 Well good UX, but it's proprietary hosted search as a service 102 00:05:01,040 --> 00:05:05,920 The potential issue there is cost as your site or app grows you hit search limits 103 00:05:06,140 --> 00:05:09,800 Indexing limits and suddenly your bill can jump it can get expensive fast 104 00:05:09,800 --> 00:05:14,920 Ah the scaling cost trap exactly type sense being open source gives you the choice 105 00:05:14,920 --> 00:05:16,060 run it on your own servers 106 00:05:16,060 --> 00:05:20,620 Totally free beside your server costs. That's potentially huge savings as you scale 107 00:05:20,620 --> 00:05:23,240 or if you want managed convenience 108 00:05:23,240 --> 00:05:27,920 There's type sense cloud, but its pricing is different. It's based on fixed hourly 109 00:05:27,920 --> 00:05:29,760 costs for the server resources 110 00:05:29,760 --> 00:05:34,330 It's predictable not based on how many records you have or how many searches people 111 00:05:34,330 --> 00:05:36,080 do which can be hard to predict 112 00:05:36,080 --> 00:05:40,190 And budget for with other services. Okay, predictable pricing is a big plus any key 113 00:05:40,190 --> 00:05:43,280 technical differences besides the hosting model 114 00:05:43,280 --> 00:05:47,440 Yes a key one for efficiency type sense can give you sorted results from a single 115 00:05:47,440 --> 00:05:48,020 index 116 00:05:48,020 --> 00:05:53,050 So if you want users to sort products by price or by date or by rating type sense 117 00:05:53,050 --> 00:05:55,580 handles that efficiently with one main data structure 118 00:05:55,580 --> 00:05:59,870 Algolia often needs you to create separate duplicate indices for each sort order 119 00:05:59,870 --> 00:06:01,200 sort by price 120 00:06:01,200 --> 00:06:05,320 That's one index sort by date another index which means more memory usage more 121 00:06:05,320 --> 00:06:06,020 complexity 122 00:06:06,020 --> 00:06:09,480 Right more memory more management overhead now to be fair 123 00:06:09,480 --> 00:06:12,810 Algolia does have some very mature features like built-in personalization and 124 00:06:12,810 --> 00:06:16,080 server-side analytics that types sense is still building out 125 00:06:16,080 --> 00:06:20,240 But for core search functionality and especially for analytics 126 00:06:20,240 --> 00:06:25,000 You can easily use standard web analytics tools with type sense on the client side 127 00:06:25,000 --> 00:06:25,480 for now 128 00:06:25,480 --> 00:06:30,040 For many the simplicity cost and open source benefits outweigh those current 129 00:06:30,040 --> 00:06:30,880 differences 130 00:06:30,880 --> 00:06:34,510 Yeah, it really sounds like ease of use is deeply embedded and the source is 131 00:06:34,510 --> 00:06:37,120 mentioned getting from zero to instant search and like 132 00:06:37,120 --> 00:06:39,680 30 seconds, that's incredible 133 00:06:39,680 --> 00:06:45,250 Plus multiple easy install options Docker native binaries the managed cloud. It 134 00:06:45,250 --> 00:06:47,080 seems built to remove friction 135 00:06:47,080 --> 00:06:50,180 So, okay, it's easy. It's fast. But what about the features? 136 00:06:50,180 --> 00:06:54,530 What specific things does type sense offer that make the search experience itself 137 00:06:54,530 --> 00:06:55,640 better smarter more? 138 00:06:55,640 --> 00:06:58,960 Delightful for the person actually doing the searching right beyond the basics 139 00:06:58,960 --> 00:07:02,580 There's some really user-friendly features first off typo tolerance. This is 140 00:07:02,580 --> 00:07:05,240 massive. It handles typos gracefully out of the box 141 00:07:05,240 --> 00:07:10,140 No special setup needed. Remember the example from their docs search stork and it 142 00:07:10,140 --> 00:07:11,840 finds stark industries, huh? 143 00:07:11,840 --> 00:07:17,240 Okay, that's smart. We've all made those typos. Exactly. It just understands then 144 00:07:17,240 --> 00:07:19,160 the blazing fast speed 145 00:07:19,160 --> 00:07:23,810 We keep saying it but it's engineered for it builds in C plus plus N aiming for 146 00:07:23,810 --> 00:07:25,620 under 50 meters response times 147 00:07:26,240 --> 00:07:31,480 That speed feels good to users. You also get great control with tunable ranking 148 00:07:31,480 --> 00:07:33,280 sorting fasting and filtering 149 00:07:33,280 --> 00:07:35,520 Sounds tucky, but it's about control 150 00:07:35,520 --> 00:07:39,460 Tunable ranking that's decide what's most important in results. Maybe newer items 151 00:07:39,460 --> 00:07:40,760 first or higher rated ones 152 00:07:40,760 --> 00:07:44,560 Sorty is obvious. Let users sort by price date etc and 153 00:07:44,560 --> 00:07:49,200 Faceting and filtering is that like the sidebar options on shopping sites precisely 154 00:07:49,200 --> 00:07:51,960 like filter by brand filter by size filter by color 155 00:07:51,960 --> 00:07:55,890 Yeah, it lets users slice and dice the results easily turns a huge list into 156 00:07:55,890 --> 00:07:58,520 exactly what they want makes finding things intuitive 157 00:07:58,520 --> 00:08:02,260 Okay, that makes perfect sense very user centric definitely and synonyms are great 158 00:08:02,260 --> 00:08:05,720 to handle things like pants versus trousers sneakers versus trainers 159 00:08:05,720 --> 00:08:09,660 Users find stuff even if they use different words then we get into more advanced 160 00:08:09,660 --> 00:08:11,020 territory, but still kept accessible 161 00:08:11,020 --> 00:08:15,950 Vector search and semantic hybrid search. This is cool. It's about understanding 162 00:08:15,950 --> 00:08:17,080 meaning not just key words 163 00:08:17,160 --> 00:08:22,600 so going beyond exact word matching right think searching for comfortable shoes for 164 00:08:22,600 --> 00:08:23,120 walking and 165 00:08:23,120 --> 00:08:27,970 It finds results even if they don't use those exact words because it understands 166 00:08:27,970 --> 00:08:30,580 the concept. It uses AI models to find 167 00:08:30,580 --> 00:08:36,240 Eerily accurate results matching the intent Wow. Okay. That's next level 168 00:08:36,240 --> 00:08:42,080 It is and even more so is conversational search with built-in rag rag stands for 169 00:08:42,080 --> 00:08:43,240 retrieval augmented generation 170 00:08:43,920 --> 00:08:49,070 Think chat GPT but running securely over your own data your company Docs your 171 00:08:49,070 --> 00:08:49,680 knowledge base 172 00:08:49,680 --> 00:08:53,720 Whatever you index wait, so I can ask it questions in normal language exactly 173 00:08:53,720 --> 00:08:57,430 You can ask something like what's our policy on international shipping and instead 174 00:08:57,430 --> 00:08:59,440 of just give you a list of documents where that might be 175 00:08:59,440 --> 00:09:03,530 Mentioned it retrieved the relevant info from your data and then generates a clear 176 00:09:03,530 --> 00:09:04,720 natural language answer 177 00:09:04,720 --> 00:09:08,360 Like our policy states that based on the documents it read that's incredible 178 00:09:08,360 --> 00:09:12,460 It's not just finding it's answering that changes everything for internal knowledge 179 00:09:12,460 --> 00:09:14,060 search or customer support bots 180 00:09:14,060 --> 00:09:18,200 It's a huge leap and there's also geo search perfect for finding things nearby 181 00:09:18,200 --> 00:09:22,980 Like stores or services within a certain distance and finally federated search 182 00:09:22,980 --> 00:09:27,770 This lets you search across different types of information at once like one search 183 00:09:27,770 --> 00:09:30,600 bar could hit your products your blog posts and your help 184 00:09:30,600 --> 00:09:34,720 Docs simultaneously bringing it all together in one place very neat 185 00:09:34,960 --> 00:09:38,940 Okay, those features are compelling but you know proof is in the pudding numbers 186 00:09:38,940 --> 00:09:39,080 talk 187 00:09:39,080 --> 00:09:42,990 What kind of actual performance are we talking about and who's really using this? 188 00:09:42,990 --> 00:09:45,280 Can it handle serious scale? 189 00:09:45,280 --> 00:09:48,140 It definitely handles scale. The benchmarks are pretty telling 190 00:09:48,140 --> 00:09:53,060 Let's take one example a data set of 2.2 million recipes names ingredients the 191 00:09:53,060 --> 00:09:53,480 whole thing 192 00:09:53,480 --> 00:09:58,500 indexing that took only about 900 megabytes of RAM and type sense and on a fairly 193 00:09:58,500 --> 00:10:02,120 standard server for virtual CPUs it handled 194 00:10:02,680 --> 00:10:06,740 104 concurrent searches per second a hundred people searching at the exact same 195 00:10:06,740 --> 00:10:07,040 time 196 00:10:07,040 --> 00:10:11,950 Yep, and the average processing time just 11 milliseconds near instant or a bigger 197 00:10:11,950 --> 00:10:12,220 one 198 00:10:12,220 --> 00:10:19,570 28 million books titles authors categories that used about 14 gigs of RAM same 199 00:10:19,570 --> 00:10:20,040 server 200 00:10:20,040 --> 00:10:24,360 It managed 46 concurrent searches per second average time 28 milliseconds 201 00:10:24,360 --> 00:10:28,680 So even with tens of millions of items it stays incredibly responsive 202 00:10:28,680 --> 00:10:32,450 All right that directly impacts user happiness and can mean lower server costs for 203 00:10:32,450 --> 00:10:35,440 you. Those are solid numbers really backs up the speed claims 204 00:10:35,440 --> 00:10:38,960 What about adoption is it just niche or lots of people using it? 205 00:10:38,960 --> 00:10:42,760 Oh, it's way beyond me now type sense cloud their managed service is serving over 206 00:10:42,760 --> 00:10:44,400 10 billion searches every month 207 00:10:44,400 --> 00:10:49,170 That's massive real-world usage 10 billion. Okay. Yeah, that's serious in the docker 208 00:10:49,170 --> 00:10:49,600 images 209 00:10:49,600 --> 00:10:53,610 How developers often run it downloaded over 12 million times? That shows a huge 210 00:10:53,610 --> 00:10:55,020 active community 211 00:10:55,020 --> 00:10:58,230 It's being used by all sorts of companies. Yeah from you know, scrappy startups 212 00:10:58,230 --> 00:11:01,280 building the next big thing to well-known household names 213 00:11:01,280 --> 00:11:06,220 You can even play with live demos on their site searching 32 million songs or those 214 00:11:06,220 --> 00:11:07,940 28 million books instantly 215 00:11:07,940 --> 00:11:11,380 It really shows it off. Okay impressive scale and adoption 216 00:11:11,380 --> 00:11:16,500 Now that open source aspect is a big draw but licenses 217 00:11:16,500 --> 00:11:21,290 Sometimes they're confusing you mentioned the server is GPL 3.0, but the client 218 00:11:21,290 --> 00:11:23,320 libraries are Apache. Can you break that down? 219 00:11:23,320 --> 00:11:26,240 What does GPL mean for someone using the type sense server? 220 00:11:26,240 --> 00:11:31,460 Yeah, it's a good question and they've put thought into this so the core type sense 221 00:11:31,460 --> 00:11:33,720 server is GPL 3.0 222 00:11:33,720 --> 00:11:38,320 Z the client libraries the bits you use in your app code to talk to the server are 223 00:11:38,320 --> 00:11:39,280 Apache licensed 224 00:11:39,280 --> 00:11:41,920 Let's simplify the GPL part for the server 225 00:11:41,920 --> 00:11:46,370 Think of it like this GPL is designed to ensure that improvements to the core open 226 00:11:46,370 --> 00:11:47,180 source project 227 00:11:47,280 --> 00:11:51,360 Benefit the whole community in the long run if you take the type sense server code 228 00:11:51,360 --> 00:11:53,960 modify it and then distribute that modified version like 229 00:11:53,960 --> 00:11:57,320 Selling it as a service or including it in software you distribute you generally 230 00:11:57,320 --> 00:12:00,520 need to make your modifications available under the same GPL license 231 00:12:00,520 --> 00:12:04,610 Share your improvements back. Okay, so it encourages giving back to the project if 232 00:12:04,610 --> 00:12:06,320 you build upon it and share it like Linux 233 00:12:06,320 --> 00:12:10,260 It's exactly like Linux. It's a common model for foundational open source projects 234 00:12:10,260 --> 00:12:15,040 But here's a key point if you modify the types and server and only use it 235 00:12:15,040 --> 00:12:16,880 internally within your company 236 00:12:16,880 --> 00:12:20,870 Without distributing those changes outside you generally don't have to open source 237 00:12:20,870 --> 00:12:22,360 your internal modifications 238 00:12:22,360 --> 00:12:27,110 Ah, okay. So internal use gets more flexibility that makes sense for businesses, 239 00:12:27,110 --> 00:12:27,800 right? 240 00:12:27,800 --> 00:12:33,000 It protects the open source nature when code is shared but allows private use and 241 00:12:33,000 --> 00:12:35,560 the Apache license for the client libraries 242 00:12:35,560 --> 00:12:37,000 That's much more permissive 243 00:12:37,000 --> 00:12:41,160 It basically means you can easily use those libraries in your own applications even 244 00:12:41,160 --> 00:12:42,720 proprietary closed source ones 245 00:12:42,920 --> 00:12:46,250 Without needing to open source your application code just because you're talking to 246 00:12:46,250 --> 00:12:50,840 typesense so easy integration without strings attached for your own app code 247 00:12:50,840 --> 00:12:55,640 Precisely. It's a smart balance protect the core projects openness with GPL 248 00:12:55,640 --> 00:13:00,440 Enable easy adoption in any kind of app with Apache for the clients that really 249 00:13:00,440 --> 00:13:01,960 sounds like a well-thought-out approach 250 00:13:01,960 --> 00:13:06,470 And if people run into issues or need help, what's the support situation like it's 251 00:13:06,470 --> 00:13:07,140 pretty robust 252 00:13:07,140 --> 00:13:10,940 There's an active public slack community great for general questions getting quick 253 00:13:10,940 --> 00:13:11,900 feedback from other users 254 00:13:11,960 --> 00:13:16,160 Even the core team sometimes hangs out there for bugs or feature requests 255 00:13:16,160 --> 00:13:20,100 Github issues are the way to go standard open source practice and then for 256 00:13:20,100 --> 00:13:23,440 businesses needing guaranteed response times or private support 257 00:13:23,440 --> 00:13:27,800 There are paid support options available with SLA's service level agreements. So 258 00:13:27,800 --> 00:13:30,540 help is there at different levels great 259 00:13:30,540 --> 00:13:35,750 So community help official issue tracking and paid options for businesses covers 260 00:13:35,750 --> 00:13:36,320 all bases 261 00:13:36,320 --> 00:13:40,000 Alright, that brings us towards the end of our deep dive on type sense 262 00:13:40,000 --> 00:13:44,370 I think the big takeaway is this isn't just another search tool. It's genuinely 263 00:13:44,370 --> 00:13:45,880 fast super forgiving with typos 264 00:13:45,880 --> 00:13:49,810 It's open source and really seems built around making developers lives easier while 265 00:13:49,810 --> 00:13:52,560 delivering. Yeah, truly delightful search experiences 266 00:13:52,560 --> 00:13:55,000 No PhD required really sums it up 267 00:13:55,000 --> 00:13:58,280 It makes complex search stuff feel accessible and efficient whether you're just 268 00:13:58,280 --> 00:14:00,940 starting out or scaling up big time a real game changer 269 00:14:00,940 --> 00:14:05,440 It seems absolutely and it makes you think doesn't it if a tool like typesense can 270 00:14:05,440 --> 00:14:08,720 revolutionize something as fundamental as search by focusing on speed 271 00:14:09,200 --> 00:14:11,560 simplicity and well scar features 272 00:14:11,560 --> 00:14:17,280 What other parts of our digital lives our everyday online interactions could be 273 00:14:17,280 --> 00:14:19,600 made significantly better more intuitive 274 00:14:19,600 --> 00:14:21,800 Maybe even delightful it poses a question 275 00:14:21,800 --> 00:14:24,840 Where else can we apply this kind of focus on? 276 00:14:24,840 --> 00:14:30,280 Core user needs and really clever thoughtful engineering to smooth out the friction 277 00:14:30,280 --> 00:14:31,360 in our digital world 278 00:14:31,360 --> 00:14:34,400 Something to ponder as we all keep searching for things online 279 00:14:34,560 --> 00:14:38,330 That's a fantastic thought to end on and once again huge thank you to safe server 280 00:14:38,330 --> 00:14:41,320 for supporting the deep dive your trusted partner for software 281 00:14:41,320 --> 00:14:44,520 Hosting and digital transformation find out how they can help you at 282 00:14:44,520 --> 00:14:47,600 www.safe-server.de one more time 283 00:14:47,600 --> 00:14:52,140 www.safe-server.de. Thanks so much for joining us and we'll catch you on the next 284 00:14:52,140 --> 00:14:52,600 deep dive