Welcome to the Deep Dive. We're plunging straight into a stack of sources today
that introduces us to something pretty interesting in the software world.
Live Helper Chat, or LHC. Our mission really is to unpack this thing.
It's an open source solution, apparently doing some serious heavy lifting for big
organizations. So for you, the learner, we want to focus
on explaining what LHC actually is, how something free can be, well, battle
tested for enterprise use, and why its design makes it sort of a
central hub for almost every communication and AI tool out there today.
We want to give you the key info, the strategic bits, without getting you totally
bogged down in technical jargon. But first, a quick word from our supporter.
This deep dive is supported by Safe Server. Safe Server handles the hosting
for this kind of software and supports you in your digital
transformation journey. You can find out more at www.safeserver.de
You know, what's really fascinating here is the contradiction. I mean, live
customer support that's usually locked down, proprietary stuff,
yet here's LHC delivering it at scale, completely open source under an Apache
2.0 license. Ah, the license. That's important, right?
Absolutely. It guarantees transparency, long-term use.
It's probably why you see these big security-focused clients actually
trusting it. Okay, that makes sense. That's really the core of it. So
let's unpack this. Start from the beginning. What is Live Helper Chat,
basically? Okay, so simply put, it's an open-source
application designed to add powerful live support to your website or app.
And the key thing, it's completely free. Free live support, okay.
But, and the sources really stress this, it's not just some basic text chat
widget, it's way more. It supports web, mobile apps, proper voice
and video calls, even screen share. Right out of the box.
Wow. So enterprise features, but free. For someone just starting, maybe a small
teen, what's the setup like? Is it complicated?
No, actually that's another plus. It's designed to be incredibly accessible.
The basic setup, dead simple. You just need PHP version 8.2 or newer,
and MySQL. Just PHP and MySQL, that's it. That's pretty much all you need to get a
basic chat service up and running. Very common stuff.
Okay, but here's the bit I'm trying to connect for the learner.
Simple setup, fine. But enterprise customization,
how does it handle that without locking you in like
proprietary software often does? Right, good question. That comes down to the
architecture. It's built using a modern MVC structure.
MVC, model view controller. Exactly. If you're not a developer,
just think of it as separating the app's brain, the logic, from how it looks, the
appearance. The view part, the look and feel, uses
the Bootstrap 5 CSS framework. Very standard,
very reliable. Okay. So because the look and the core code are separate,
you can customize the design fonts, colors, layout,
everything without ever needing to touch the main operational code,
the kernel. I see. So you can paint the car without messing with the engine.
That's a good way to put it. And that flexibility is really key to why it's so
widely adopted and constantly updated by the community.
It's perfect sense. Okay. Customizable shell, reliable engine.
Now, the elephant in the room, volume. If something's free and open source,
people always worry. Can it scale? Can it handle the kind of traffic
I don't know, big bank needs? It definitely can. Looking at the metrics
they share, load isn't an issue. They have production environments handling over,
get this, 10,000 chats per day. 10,000 a day.
Yep. With dozens of operators working actively at the same time, all running
smoothly. It's not just scalable. It's optimized specifically for those high
load situations. Okay. That's impressive. But hold on. We just
said free, open source. Are we really saying major banks, health sectors,
places where data protection is everything, are trusting this over some
expensive license thing? Why? What gives them the confidence?
Well, I think it boils down to two things. Transparency and capability. First,
because the code is open, that Apache 2.0 license, again, these big institutions
can literally audit every single line. Ah, so they can check it themselves for
security holes. Exactly. They're not just taking a
vendor's word for it. They can verify the code meets their standards, ensures
compliance. Second, to handle that kind of scale, it
uses optional tools that are themselves industry standards for
high performance. Like what? Well, for example, to get stats
instantly across millions of old chats, they integrate
Elasticsearch. Elasticsearch. Okay, for the learner,
why is that needed? Why not just use the regular database?
Good point. Elasticsearch is basically a super fast search engine
built for huge amounts of data. If you tried running complex reports on, say,
a year's worth of chats at 10,000 a day using just a standard MySQL database,
it would likely slow everything down, maybe even grind to a halt.
Right. Elasticsearch lets LHC pull statistics on
millions of chats in like seconds. It justifies itself pretty quickly in
those really high volume places. They also use things like Node.js and
background workers to handle heavy tasks away from the main application.
Offloading the work. Yeah, keeps things snappy.
And it even supports Amazon S3 for file storage.
S3. So basically infinite storage for uploads.
Pretty much. You never really have to worry about running out of space for
documents or images shared in chats. Wow, okay. So it can handle the load.
But volume's one thing, intelligence is another. To handle 10k chats and connect to
everything.
That architecture must be pretty flexible. You mentioned it acts like a hub.
Exactly. That seems to be the core design philosophy. Make it easy to plug anything
in.
Especially AI. The sheer range of AI integrations is probably its biggest strategic
advantage.
We're not just talking about hooking up one chat button.
Okay, so what specific AIs are we talking about? What are the sources mentioned?
Well, pretty much all the main generative ones. It supports chat GPT and not just
basic chat,
but the more powerful stuff like chat completion, generating responses, even the
assistant API.
But beyond that, it connects to other big platforms. Rasa AI,
Alama AI for maybe self-hosted models, and Google's Gemini too.
So flexibility. A company can pick the AI that fits their needs or budget.
Precisely. And manage it all through the one LHC interface.
And you said it uses AI for more than just chatting back to customers, like for
management tasks.
Yes. And that's really clever. It uses AI for practical stuff.
For instance, it uses Deepavlov for sentiment analysis.
Sentiment analysis. So figuring out if a customer is happy or angry in real time.
Kind of, yeah. Gaging the emotional tone of the conversation as it's happening.
And even more practically, it includes insult detection.
Insult detection. Wow. What's the point of that? I mean, beyond the obvious.
Well, think about agent well-being and management oversight.
In a busy contact center, the system can automatically flag chats where staff might
be getting abuse.
So a supervisor can step in.
Right. Immediately. Protect operators from burnout, maintain service quality, stop
things escalating.
It makes the platform proactive, not just reactive. It's a safeguard.
That's actually a really powerful use case. Okay, let's shift the customer
connection points.
You said it connects to loads of channels, more than just the website widget.
Oh, yeah. It genuinely seems to connect to almost every major channel people use
daily.
We're talking Telegram, which you can also use as a mobile app for the operators
themselves,
which is huge.
Oh, interesting. Operators can use Telegram.
Yeah, as their client. Plus Facebook Messenger, Facebook WhatsApp, Twilio for both
SMS and direct
WhatsApp, Viber, Discord, even Mattermost for internal or community chats.
They have a lot. One interface manages conversations coming from all those
different places.
Exactly. Massive consolidation saves so much time and effort.
And you mentioned voice and video earlier. That's often a big jump from just text
chat.
It is. But LHD handles it. You get Jitsi integration for free right out of the box.
Voice,
video, screen sharing, easy win.
Jitsi. OK, free and open source too.
Correct. But if you're a bigger enterprise needing, you know, guaranteed uptime top
performance for really critical calls, there's also an option to integrate with the
paid
Agora platform.
Agora.
Yeah, it's a high performance enterprise grade provider for voice, video and screen
share.
So you have choices depending on your needs.
That clarifies things. Free option with Jitsi, paid enterprise stability with Agora.
It really brings up that question again, doesn't it? Why spend time and money
building separate
systems for chat, video, AI messaging, when this one open source tool seems to
connect them all.
And you can audit the code yourself.
It really leans into centralization and efficiency, makes a strong case.
Okay, let's pivot slightly. Let's talk about the features that make life easier for
the
operators day to day, and maybe improve the customer's experience directly.
Right. For the agents, there's some pretty sophisticated stuff, good performance
tracking,
priority queues. So important chats get handled first. And this one's surprising.
The ability to see what users are typing before they hit send.
Whoa, really? Like real-time typing preview?
Yeah. Imagine the advantage you can anticipate the question,
maybe even have an answer ready just as they finish typing. Big time saver, better
service.
That sounds slightly creepy, but I can see the efficiency gain.
And what about canned messages?
Ah, yes. Delayed canned messages. That's smart, too.
It lets operators use standard pre-written answers for common questions,
but the system sends them with a slight delay.
So it looks like they're typing it out.
Exactly. It feels more personal, less robotic, maintains that human touch,
but still massively cuts down how long it takes to handle each chat.
Efficiency without sacrificing the experience.
Clever. Okay, now flip side. The customer experience and tracking.
You mentioned tracking was detailed.
Oh, very. It gives operators a ton of context.
Real-time tracking of who's online, where they are geographically
uses three different sources for accuracy, tracks every page they view,
how long they spend on the site overall, and, really useful for marketing,
it tracks the first time a user ever visited.
The first visit. So it builds a history even for anonymous visitors.
Seems so. Even if they never chat, the system knows their journey through the site
over time.
And that tracking helps route chats intelligently, you said.
Absolutely. It's very flexible. You can set rules to send visitors to specific
operators
based on location or language. The source specifically mentions
routing, say, a visitor from Lithuania directly to an operator who speaks Lithuanian.
Makes sense. Immediate connection, better service, builds trust faster.
Definitely. Big impact on quality.
Okay, rounding out the features. What about security beyond the code auditing,
and how do operators actually access this?
For access, it's got dedicated native apps, Windows, Linux,
Mac, so operators can use it easily on whatever system they have.
Good cross-platform. Yep. Security-wise, it supports
two-factor authentication, 2FA, using authenticator apps.
And of course, HTTPS encryption is standard, essential stuff.
And importantly, they seem to have tackled the spam problem
quite elegantly. Spambots in chat. Always annoying.
Right. It uses advanced CAPTCHA techniques, but apparently without making the
actual
human users type in codes. No annoying click the traffic lights thing.
Seems not. So it blocks the bots without adding friction for real visitors.
It's all about efficiency and safety working together.
Okay, let's try and wrap this up. What does this all mean? We've seen live
helper chat is completely free, open source, under
that Apache 2.0 license. You can check the code.
Yet it's robust enough for banks, universities,
handling, what was it, 10,000-plus chats a day? Yeah, that's the figure they quote
for high load environments. And its real power seems to be acting as this
central hub, pulling in AI like ChatGPT and Gemini,
connecting all the messaging apps like WhatsApp, Telegram,
all into one place. Right, I think the core takeaway for you, the learner,
is that you don't always need massive license fees for sophisticated digital
infrastructure. This demonstrates open source can deliver
that complexity, even niche things like AI for insult
detection or sentiment analysis, while still being fundamentally simple
to set up and trustworthy because you can see the code.
A final thank you again to our supporter SafeServer.
They provide hosting for this kind of advanced software and assist with your
digital transformation. You can find more info at www.safeserver.de.
Now here's something to think about, a final thought for you to mull over.
We heard LHC tracks not just visits, but the first visit,
how long someone stays on a page and can even apparently grab a screenshot of
the user's page. How does having that level of granular
detail on anonymous visitors fundamentally change the relationship
between a business and the people just browsing its site? Does it shift
this from just a support tool into something more like a
well a marketing intelligence or even an espionage engine?
That's something to maybe explore on your own. Thank you for joining us for
the Deep Dive, we'll catch you next time.