October 31, 2024 • 13 mins
What if your business could harness the power of AI without breaking the bank or stretching resources thin? Uncover how custom GPTs and Retrieval Augmented Generation (RAG) are revolutionizing the way businesses operate. Say goodbye to the overwhelming wave of new tech and discover a solution designed to enhance efficiency and productivity effortlessly. Imagine having an AI assistant, tailored to your business, ready to answer questions about products, processes, and company culture, all while being surprisingly affordable.
Join us for a lively discussion as we break down the magic behind RAG—an ingenious combination of data retrieval and language processing that acts as a super-efficient research tool. Picture this: you're in a meeting, and a question about a product detail comes up; instead of fumbling through documents, your AI assistant provides an instant answer. From streamlining meetings to smoothing out employee onboarding, these tools offer tangible benefits that keep your business ahead of the curve. Don’t miss out as we unpack how these innovations can transform your operations, making technology not just accessible but incredibly impactful for your company.
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:00):
You know, running a business these days, sometimes
it feels like you can barelykeep up with all the new tech
coming out.
Yeah, I mean AI especially.
It seems like every day there'sa new promise.
You know, ai is going torevolutionize everything.
Speaker 2 (00:13):
Yeah, I think there's some truth to that.
Speaker 1 (00:15):
Right, but it can feel overwhelming, I think, for
a lot of business owners.
Speaker 2 (00:18):
Oh, for sure.
Speaker 1 (00:19):
Who maybe feel like they're already stretched thin.
Yeah, yeah, absolutely.
You know they don't have thetime or the resources to figure
all this stuff out, yeah.
Speaker 2 (00:27):
So what if I told you there's a way to use the power
of AI?
Speaker 1 (00:31):
in a way.
Speaker 2 (00:32):
That's really straightforward.
Speaker 1 (00:33):
Yeah.
Speaker 2 (00:33):
Surprisingly affordable.
Speaker 1 (00:35):
Okay, now we're talking.
Speaker 2 (00:36):
Even for medium-sized businesses.
Speaker 1 (00:38):
That sounds pretty good, that sounds up our alley.
Speaker 2 (00:41):
That's where custom GPTs and Argae come in All right
, so you said custom GPTs.
Yeah.
Speaker 1 (00:47):
What exactly are those?
Speaker 2 (00:48):
So think of a custom GPT as an AI assistant oh wait,
but one that's been tailored toyour business, uh-huh.
It's kind of like having anintern that read every single
document, every email, everycustomer interaction in your
company's history Wow and theycan answer questions about your
(01:08):
products, your processes, evenyour company culture, all based
on your data.
Speaker 1 (01:12):
Okay, that makes sense.
Speaker 2 (01:13):
Yeah.
Speaker 1 (01:14):
So it's using our data to basically answer our
questions.
Speaker 2 (01:16):
Exactly, okay yeah.
Speaker 1 (01:17):
But you know, even the best interns need a little
bit of guidance, right?
Speaker 2 (01:21):
For sure yeah.
Speaker 1 (01:22):
So how do we make sure this AI assistant is always
providing the right info?
Speaker 2 (01:26):
Right, well, that's where ARA comes in Okay, rag.
What is RAG?
Speaker 1 (01:30):
So it stands for Retrieval, augmented Generation.
Speaker 2 (01:33):
Retrieval Augmented Generation.
Speaker 1 (01:35):
Okay, I can see why we shortened that to RAG.
Speaker 2 (01:37):
And it's pronounced just like the word RAG.
Speaker 1 (01:39):
Okay, rag Got it.
Speaker 2 (01:40):
So think of it like giving your AI assistant a team
of expert researchers who caninstantly pull up any
information from all of yourcompany's digital stuff.
Speaker 1 (01:49):
So like contracts, presentations, internal wikis,
all that kind of stuff.
Speaker 2 (01:53):
All of it.
Speaker 1 (01:53):
Yep, that sounds amazing.
I mean, it really does soundlike giving our AI assistant a
superpower to just instantlyaccess and process all that
company knowledge.
Speaker 2 (02:05):
Totally yeah.
It's like the ultimate researchtool.
Speaker 1 (02:07):
Yeah, so what does that look like in the real world
, like in practice?
How does that actually help abusiness like mine?
Speaker 2 (02:13):
Let me give you an example.
Speaker 1 (02:14):
Okay.
Speaker 2 (02:15):
Say you're in a meeting and someone asks about a
product detail.
Speaker 1 (02:19):
Happens all the time.
Speaker 2 (02:21):
Right, and it's buried in some huge technical
document.
Instead of wasting timesearching for it, you just ask
your AI assistant oh, instantanswer.
Speaker 1 (02:30):
Oh, that's awesome.
Speaker 2 (02:30):
Or think about onboarding new employees.
Speaker 1 (02:32):
Okay.
Speaker 2 (02:33):
Rye can get them up to speed on policies, procedures
, best practices, all withoutdigging through tons of
documentation.
Speaker 1 (02:41):
Okay, so right off the bat, we're talking about
like big efficiency gains.
Speaker 2 (02:43):
Huge yeah of documentation.
Speaker 1 (02:45):
Okay, so right off the bat we're talking about like
big efficiency gains, huge yeah, but the tech side of things
still feels a little mysteriousto me.
I bet I get the concept, buthow does our gag actually work?
Like under the hood.
Speaker 2 (02:54):
Yeah, so it's a two-step process.
Speaker 1 (02:56):
Okay.
Speaker 2 (02:56):
Retrieval and generation.
Speaker 1 (02:57):
Retrieval and generation.
Speaker 2 (02:58):
Think of it like this you ask a question.
Rg is like a super efficientlibrarian and finds the most
relevant info in your company'sdata.
Got it?
That's the retrieval part.
Speaker 1 (03:09):
Okay.
Speaker 2 (03:10):
But it's even smarter than a regular search engine.
Speaker 1 (03:12):
How so.
Speaker 2 (03:13):
It understands the meaning behind your question and
finds related info, even if thewording's not identical.
Speaker 1 (03:18):
Oh, wow, okay, that's impressive.
Speaker 2 (03:20):
Yeah.
Speaker 1 (03:21):
So that's retrieval, but how do we go from finding
the info to actually getting ananswer?
Speaker 2 (03:26):
Right.
So that's where the generationpart comes in.
Speaker 1 (03:28):
Okay.
Speaker 2 (03:35):
RG gathers all the relevant pieces of information
and then uses its languageprocessing abilities to
synthesize those pieces into aclear and concise answer.
Speaker 1 (03:40):
Wow.
Speaker 2 (03:40):
It's like giving your AI assistant a briefing packet
full of facts.
I like that, yeah, and thenthey just present those facts in
a way that makes sense.
Speaker 1 (03:48):
Okay.
So it's not just spitting outrandom facts, it's putting them
together in a way that I canunderstand.
Speaker 2 (03:52):
Exactly yeah.
Speaker 1 (03:53):
So it's actually useful, right?
Okay, this is all soundingreally good, but let's talk
about how we actually do this.
Like, what are the practicalsteps to get RAG up and running
in my business?
Speaker 2 (04:03):
It's simpler than you might think.
Speaker 1 (04:04):
Okay, good.
Speaker 2 (04:05):
And affordable.
Speaker 1 (04:06):
Or even better.
Speaker 2 (04:08):
There are three key components.
Speaker 1 (04:10):
Okay.
Speaker 2 (04:10):
First, you need a way to gather all your important
info.
Okay, that's where SaaSintegrations come in.
Speaker 1 (04:16):
SaaS integrations.
Speaker 2 (04:19):
I've heard that term before.
They basically connect yourexisting systems to your AI
assistant.
Speaker 1 (04:23):
So, like my CRM, my HR platform, things like that,
that's a back player.
Okay, so we're not talkingabout getting rid of the systems
we already have.
Speaker 2 (04:29):
No no.
Speaker 1 (04:30):
We're talking about making them work together.
Speaker 2 (04:32):
Yeah, connecting them , Okay.
Next you need a vector database.
Speaker 1 (04:35):
Okay, a vector database.
What is that?
Speaker 2 (04:37):
It's like a digital filing cabinet for all your
information, and each piece ofinfo gets a unique fingerprint
based on its meaning.
Speaker 1 (04:45):
Okay.
Speaker 2 (04:45):
So that makes searching super fast and
accurate.
Speaker 1 (04:48):
Okay, I like that.
Speaker 2 (04:49):
Don't worry, you don't need to build one yourself
.
Speaker 1 (04:51):
Oh good.
Speaker 2 (04:52):
There are lots of SaaS solutions for this.
Speaker 1 (04:54):
Plenty of options?
Yeah, all right.
So we've gathered all the info,we've organized it in a way
that the AI can use it Right.
What's the final piece of thepuzzle?
Speaker 2 (05:02):
So we need to augment the prompts.
Speaker 1 (05:04):
Augment the prompts.
What does that mean?
Speaker 2 (05:06):
Basically, we're giving the AI a little extra
context with each question, okay.
So say you ask what are our topselling products in the
Southwest region?
Aaraj automatically adds infolike sales data, customer
demographics, regional marketingcampaigns.
Speaker 1 (05:27):
Oh, I see, so it gives the AI, everything it
needs to give you a really greatanswer.
So, basically, we're giving ita cheat sheet with all the
relevant facts.
Speaker 2 (05:30):
Exactly.
Okay, I like that it's likegiving it a little boost.
Speaker 1 (05:33):
Yeah, that makes sense.
So, just to recap, we can doall of this using existing SaaS
solutions.
Speaker 2 (05:39):
Yeah, for sure.
Speaker 1 (05:40):
So we don't need a whole team of developers.
Not at all or any of that crazyexpensive infrastructure.
Speaker 2 (05:45):
No.
Speaker 1 (05:46):
Okay, that's really good to know.
Speaker 2 (05:47):
Yeah, there are SaaS providers who specialize in our
ag.
Speaker 1 (05:50):
Okay.
Speaker 2 (05:50):
And they take care of all the technical stuff for you
.
Speaker 1 (05:53):
So it's like hiring a contractor.
Speaker 2 (05:54):
Exactly.
Speaker 1 (05:55):
Okay, I like that analogy Right.
So one last question before wemove on.
We've been talking about usingRAG with our internal company
data, but what about theinternet?
Ah Can we bring that into theequation as well?
Speaker 2 (06:08):
That's a great question.
Speaker 1 (06:09):
It feels like there's a whole other world of
information out there.
Speaker 2 (06:12):
Yeah, and that's exactly what we'll be talking
about next time.
Speaker 1 (06:15):
All right, can't wait , I'm hooked.
Speaker 2 (06:16):
Me too.
So last time we were talkingabout RAG and how it can access
your internal data.
Speaker 1 (06:22):
Yeah, it's like having a super-powered research
assistant for your company.
Speaker 2 (06:25):
Right, exactly.
Speaker 1 (06:26):
But you hinted that we could take it even further.
Speaker 2 (06:28):
We can.
Speaker 1 (06:29):
And bring in information from the internet.
Speaker 2 (06:31):
Absolutely.
Speaker 1 (06:31):
That's where it starts to feel really futuristic
, totally Like almost too goodto be true.
Speaker 2 (06:36):
So imagine combining your company's knowledge with
insights from the entireinternet.
Speaker 1 (06:41):
Wow.
Speaker 2 (06:41):
So it's like giving your AI a window to the outside
world.
Speaker 1 (06:45):
Yeah.
Speaker 2 (06:46):
It can see market trends, industry news, customer
sentiment.
Speaker 1 (06:50):
Okay.
So now we're not just lookingat what's happening inside our
company, right, we're connectingit to what's happening out
there in the real world.
Speaker 2 (06:57):
Exactly.
It's like having a team ofanalysts constantly monitoring
everything.
Speaker 1 (07:02):
I like that, so can you give me an example?
Speaker 2 (07:04):
Sure, let's say you're a retail company.
Speaker 1 (07:07):
Okay.
Speaker 2 (07:07):
And you're about to launch a new line of athletic
wear.
Speaker 1 (07:11):
All right, I'm following.
Speaker 2 (07:13):
Your AI could look at your internal sales data.
Speaker 1 (07:17):
Okay To see what's worked in the past look at your
internal sales data.
Speaker 2 (07:21):
Okay, to see what's worked in the past Right.
But it could also check socialmedia trends See what's hot in
fitness right now.
Speaker 1 (07:24):
To see what people are actually talking about.
Speaker 2 (07:25):
Exactly, and it could even analyze your competitors'
websites.
Speaker 1 (07:30):
So we could see what's selling well for them.
Speaker 2 (07:31):
Yeah, and at what price?
Speaker 1 (07:33):
That's amazing.
Yeah, I mean, that's a wholedifferent level of market
intelligence.
Speaker 2 (07:37):
Right, it's not just reacting, it's anticipating.
Speaker 1 (07:40):
Okay, so we're talking about a real competitive
advantage here.
Speaker 2 (07:43):
Definitely, and it goes beyond just market analysis
.
Speaker 1 (07:46):
Okay, how so?
Speaker 2 (07:47):
Think about customer service.
Speaker 1 (07:49):
Okay.
Speaker 2 (07:49):
A customer has a question about a product.
Speaker 1 (07:52):
Happens all the time.
Speaker 2 (07:53):
Your AI can pull up the specs from your database,
but also search the internet forreviews.
Oh, that's smart.
Troubleshooting tips.
Speaker 1 (08:02):
Okay.
Speaker 2 (08:02):
Even safety updates.
Speaker 1 (08:04):
So we're giving the customer the most up-to-date
information possible.
Speaker 2 (08:07):
Exactly.
Speaker 1 (08:07):
That's awesome, but my next question is with all
this information coming in, howdo we make sure we're not
drowning in data?
Speaker 2 (08:16):
Right, well, that's where the AI comes in.
Okay, it doesn't just collectdata, it analyzes it and finds
patterns.
Speaker 1 (08:21):
So it helps us make sense of it all.
Speaker 2 (08:22):
Exactly.
It's like having a team ofanalysts summarizing everything
for you.
Speaker 1 (08:31):
I like that.
Okay, so RIT can do all thisamazing stuff.
Speaker 2 (08:32):
Are there any drawbacks we should be aware of?
Well, as with any technology,there are some things to keep in
mind.
Okay, like what Data quality iscrucial.
That makes sense Garbage ingarbage outright.
Speaker 1 (08:40):
Right.
Speaker 2 (08:40):
So your internal data needs to be accurate and up to
date Makes sense.
Speaker 1 (08:44):
Anything else.
Speaker 2 (08:45):
Security is paramount .
Speaker 1 (08:46):
Oh yeah, especially when we're talking about the
internet.
Speaker 2 (08:48):
Exactly so.
You want to work with trustedproviders.
Speaker 1 (08:52):
Who have strong security measures in place.
Speaker 2 (08:54):
Right, it's like having a good security system
for your house.
Speaker 1 (08:57):
Makes sense.
Speaker 2 (08:57):
Okay.
Speaker 1 (08:58):
Okay, so we've talked about the benefits, the
possibilities, some potentialchallenges.
What's next for someone who'sready to explore RAG?
So first you need to figure outwhat you want to use it for.
Okay, find the right use case.
Speaker 2 (09:10):
Right.
What problems are you trying tosolve?
Speaker 1 (09:13):
Customer service, internal operations, market
intelligence Exactly.
So start with the problem andthen find the right tool.
Speaker 2 (09:20):
That's it.
Speaker 1 (09:21):
Okay, any other advice?
Speaker 2 (09:22):
The AI world is constantly changing, so stay
curious and experiment.
Speaker 1 (09:27):
Don't be afraid to try new things.
Speaker 2 (09:29):
Exactly Start small with a pilot project.
Speaker 1 (09:31):
And see what works.
Speaker 2 (09:32):
Right.
The future of business isdata-driven, and RAG can help
you get there.
Speaker 1 (09:37):
All right, I'm sold.
I think we need to dive intosome practical tips for
implementation next time.
Speaker 2 (09:41):
Sounds good, let's do it.
Speaker 1 (09:42):
Okay, so we've talked about what RAG is and why it's
so powerful.
Speaker 2 (09:45):
Right, we've laid the groundwork.
Speaker 1 (09:47):
But now let's get down to brass tacks.
Speaker 2 (09:48):
I like it.
Speaker 1 (09:49):
How do we actually make this work for our
businesses?
Speaker 2 (09:52):
So the first step is to get really clear about your
goals.
Speaker 1 (09:55):
Okay, so don't just implement RRAC, because it's the
shiny new toy.
Speaker 2 (09:59):
Exactly.
It's got to solve a realproblem.
Speaker 1 (10:01):
So what are we trying to achieve?
Are we looking to improvecustomer service, streamline
operations, get a betterunderstanding of our market?
Speaker 2 (10:09):
Those are all great examples.
Speaker 1 (10:10):
Yeah, so start with the problem, not the solution.
Speaker 2 (10:13):
Right, figure out what you want to accomplish.
Speaker 1 (10:15):
And then find the right tool for the job.
Speaker 2 (10:17):
Exactly Makes sense.
Speaker 1 (10:20):
Okay, so once we know what we want to achieve, Then
it's time to look at your data.
Our data Okay.
Speaker 2 (10:25):
What information do you already have?
Speaker 1 (10:26):
Yeah.
Speaker 2 (10:27):
Where is it stored, is it organized, is it easy to
access?
Speaker 1 (10:30):
That's a good point, because data is the fuel that
powers our red.
Speaker 2 (10:34):
Yeah, right, it is.
It's the foundation.
Speaker 1 (10:36):
But data management can be a real headache.
Speaker 2 (10:38):
Oh, I know.
Speaker 1 (10:39):
Any tips for making that process a little less
painful?
Speaker 2 (10:42):
Don't try to boil the ocean.
Okay, start with the datathat's most relevant to your
goals.
So, if we're trying to improvecustomer service, focus on
customer interactions.
Product information supportdocs.
Speaker 1 (10:54):
Keep it manageable.
Speaker 2 (10:55):
Right Prioritize.
Speaker 1 (10:56):
Okay, so we've got our goals defined and our data
is prepped and ready to go.
Speaker 2 (11:00):
Okay.
Speaker 1 (11:01):
How do we actually choose the right R-Rad solution?
Speaker 2 (11:04):
Right, so there are a lot of providers out there.
Speaker 1 (11:06):
It's a crowded market .
Speaker 2 (11:07):
It is, but don't let that overwhelm you.
Speaker 1 (11:09):
Okay.
Speaker 2 (11:09):
Good, just keep a few things in mind.
Speaker 1 (11:11):
Okay, what are those?
Speaker 2 (11:12):
Ease of use.
Speaker 1 (11:13):
Ease of use.
Speaker 2 (11:13):
Okay Can you integrate Systems?
Is the interface user-friendly?
Speaker 1 (11:19):
Yeah, we don't want something that requires a PhD to
operate.
Speaker 2 (11:22):
Exactly you want your team to be able to use.
It Makes sense.
Speaker 1 (11:25):
What else?
Speaker 2 (11:26):
Scalability.
Speaker 1 (11:27):
Scalability okay.
Speaker 2 (11:28):
Can the solution grow with your business?
Speaker 1 (11:31):
As our data volume increases.
Exactly so it's got to be ableto keep up.
Speaker 2 (11:35):
Right, it's like choosing a car.
Okay, compact car might be finefor running errands.
Speaker 1 (11:40):
Yeah.
Speaker 2 (11:40):
But for a cross-country trip you need
something bigger.
Speaker 1 (11:43):
Makes sense, so we need to choose a solution that
can handle the long haul.
Speaker 2 (11:47):
Right, what else it's security?
Speaker 1 (11:49):
Security, of course.
Speaker 2 (11:50):
This is super important.
Absolutely You're trusting thesystem with your data.
Speaker 1 (11:55):
So we need to make sure it's protected.
Speaker 2 (11:57):
Top-notch security measures encryption, access
controls, compliance.
Speaker 1 (12:00):
All the good stuff.
Speaker 2 (12:01):
Right.
Speaker 1 (12:02):
Okay, so we've talked about the tech side of things.
Speaker 2 (12:04):
Uh-huh.
Speaker 1 (12:05):
But we can't forget about the human element.
Speaker 2 (12:07):
Oh, absolutely.
Speaker 1 (12:08):
Implementing RG successfully.
That requires communication,training, support.
Speaker 2 (12:11):
It's a team effort.
Speaker 1 (12:12):
Yeah, we need to bring our people along on this
journey.
Change management is key.
Make sure everyone understandswhy we're doing this.
Speaker 2 (12:18):
Right.
Give them the skills they needto use it.
Speaker 1 (12:20):
And be there to answer their questions.
Speaker 2 (12:22):
Exactly.
Speaker 1 (12:23):
Okay.
So as we wrap up this deep diveon RAG, what's the one key
takeaway you want our listenersto remember?
Speaker 2 (12:30):
AI can seem intimidating, but RG makes it
accessible.
Speaker 1 (12:35):
Accessible and affordable.
Speaker 2 (12:36):
Right For businesses of all sizes.
Speaker 1 (12:39):
So, identify your goals, get your data in order,
find the right provider.
Speaker 2 (12:45):
And don't be afraid to experiment.
Speaker 1 (12:47):
Start small, learn as you go.
Speaker 2 (12:50):
Exactly.
Speaker 1 (12:51):
The future of business is data driven and RAG
is the key.
Speaker 2 (12:54):
Couldn't have said it better myself.
Speaker 1 (12:56):
I love it.
Well, thanks for joining us onthis deep dive into our rag.
I hope everyone listening feelsempowered to explore this
incredible technology and seehow it can transform their
business.
Until next time, happyinnovating.
Speaker 2 (13:08):
See ya.
You know, running a business these days, sometimes
it feels like you can barelykeep up with all the new tech
coming out.
Yeah, I mean AI especially.
It seems like every day there'sa new promise.
You know, ai is going torevolutionize everything.
Speaker 2 (00:13):
Yeah, I think there's some truth to that.
Speaker 1 (00:15):
Right, but it can feel overwhelming, I think, for
a lot of business owners.
Speaker 2 (00:18):
Oh, for sure.
Speaker 1 (00:19):
Who maybe feel like they're already stretched thin.
Yeah, yeah, absolutely.
You know they don't have thetime or the resources to figure
all this stuff out, yeah.
Speaker 2 (00:27):
So what if I told you there's a way to use the power
of AI?
Speaker 1 (00:31):
in a way.
Speaker 2 (00:32):
That's really straightforward.
Speaker 1 (00:33):
Yeah.
Speaker 2 (00:33):
Surprisingly affordable.
Speaker 1 (00:35):
Okay, now we're talking.
Speaker 2 (00:36):
Even for medium-sized businesses.
Speaker 1 (00:38):
That sounds pretty good, that sounds up our alley.
Speaker 2 (00:41):
That's where custom GPTs and Argae come in All right
, so you said custom GPTs.
Yeah.
Speaker 1 (00:47):
What exactly are those?
Speaker 2 (00:48):
So think of a custom GPT as an AI assistant oh wait,
but one that's been tailored toyour business, uh-huh.
It's kind of like having anintern that read every single
document, every email, everycustomer interaction in your
company's history Wow and theycan answer questions about your
(01:08):
products, your processes, evenyour company culture, all based
on your data.
Speaker 1 (01:12):
Okay, that makes sense.
Speaker 2 (01:13):
Yeah.
Speaker 1 (01:14):
So it's using our data to basically answer our
questions.
Speaker 2 (01:16):
Exactly, okay yeah.
Speaker 1 (01:17):
But you know, even the best interns need a little
bit of guidance, right?
Speaker 2 (01:21):
For sure yeah.
Speaker 1 (01:22):
So how do we make sure this AI assistant is always
providing the right info?
Speaker 2 (01:26):
Right, well, that's where ARA comes in Okay, rag.
What is RAG?
Speaker 1 (01:30):
So it stands for Retrieval, augmented Generation.
Speaker 2 (01:33):
Retrieval Augmented Generation.
Speaker 1 (01:35):
Okay, I can see why we shortened that to RAG.
Speaker 2 (01:37):
And it's pronounced just like the word RAG.
Speaker 1 (01:39):
Okay, rag Got it.
Speaker 2 (01:40):
So think of it like giving your AI assistant a team
of expert researchers who caninstantly pull up any
information from all of yourcompany's digital stuff.
Speaker 1 (01:49):
So like contracts, presentations, internal wikis,
all that kind of stuff.
Speaker 2 (01:53):
All of it.
Speaker 1 (01:53):
Yep, that sounds amazing.
I mean, it really does soundlike giving our AI assistant a
superpower to just instantlyaccess and process all that
company knowledge.
Speaker 2 (02:05):
Totally yeah.
It's like the ultimate researchtool.
Speaker 1 (02:07):
Yeah, so what does that look like in the real world
, like in practice?
How does that actually help abusiness like mine?
Speaker 2 (02:13):
Let me give you an example.
Speaker 1 (02:14):
Okay.
Speaker 2 (02:15):
Say you're in a meeting and someone asks about a
product detail.
Speaker 1 (02:19):
Happens all the time.
Speaker 2 (02:21):
Right, and it's buried in some huge technical
document.
Instead of wasting timesearching for it, you just ask
your AI assistant oh, instantanswer.
Speaker 1 (02:30):
Oh, that's awesome.
Speaker 2 (02:30):
Or think about onboarding new employees.
Speaker 1 (02:32):
Okay.
Speaker 2 (02:33):
Rye can get them up to speed on policies, procedures
, best practices, all withoutdigging through tons of
documentation.
Speaker 1 (02:41):
Okay, so right off the bat, we're talking about
like big efficiency gains.
Speaker 2 (02:43):
Huge yeah of documentation.
Speaker 1 (02:45):
Okay, so right off the bat we're talking about like
big efficiency gains, huge yeah, but the tech side of things
still feels a little mysteriousto me.
I bet I get the concept, buthow does our gag actually work?
Like under the hood.
Speaker 2 (02:54):
Yeah, so it's a two-step process.
Speaker 1 (02:56):
Okay.
Speaker 2 (02:56):
Retrieval and generation.
Speaker 1 (02:57):
Retrieval and generation.
Speaker 2 (02:58):
Think of it like this you ask a question.
Rg is like a super efficientlibrarian and finds the most
relevant info in your company'sdata.
Got it?
That's the retrieval part.
Speaker 1 (03:09):
Okay.
Speaker 2 (03:10):
But it's even smarter than a regular search engine.
Speaker 1 (03:12):
How so.
Speaker 2 (03:13):
It understands the meaning behind your question and
finds related info, even if thewording's not identical.
Speaker 1 (03:18):
Oh, wow, okay, that's impressive.
Speaker 2 (03:20):
Yeah.
Speaker 1 (03:21):
So that's retrieval, but how do we go from finding
the info to actually getting ananswer?
Speaker 2 (03:26):
Right.
So that's where the generationpart comes in.
Speaker 1 (03:28):
Okay.
Speaker 2 (03:35):
RG gathers all the relevant pieces of information
and then uses its languageprocessing abilities to
synthesize those pieces into aclear and concise answer.
Speaker 1 (03:40):
Wow.
Speaker 2 (03:40):
It's like giving your AI assistant a briefing packet
full of facts.
I like that, yeah, and thenthey just present those facts in
a way that makes sense.
Speaker 1 (03:48):
Okay.
So it's not just spitting outrandom facts, it's putting them
together in a way that I canunderstand.
Speaker 2 (03:52):
Exactly yeah.
Speaker 1 (03:53):
So it's actually useful, right?
Okay, this is all soundingreally good, but let's talk
about how we actually do this.
Like, what are the practicalsteps to get RAG up and running
in my business?
Speaker 2 (04:03):
It's simpler than you might think.
Speaker 1 (04:04):
Okay, good.
Speaker 2 (04:05):
And affordable.
Speaker 1 (04:06):
Or even better.
Speaker 2 (04:08):
There are three key components.
Speaker 1 (04:10):
Okay.
Speaker 2 (04:10):
First, you need a way to gather all your important
info.
Okay, that's where SaaSintegrations come in.
Speaker 1 (04:16):
SaaS integrations.
Speaker 2 (04:19):
I've heard that term before.
They basically connect yourexisting systems to your AI
assistant.
Speaker 1 (04:23):
So, like my CRM, my HR platform, things like that,
that's a back player.
Okay, so we're not talkingabout getting rid of the systems
we already have.
Speaker 2 (04:29):
No no.
Speaker 1 (04:30):
We're talking about making them work together.
Speaker 2 (04:32):
Yeah, connecting them , Okay.
Next you need a vector database.
Speaker 1 (04:35):
Okay, a vector database.
What is that?
Speaker 2 (04:37):
It's like a digital filing cabinet for all your
information, and each piece ofinfo gets a unique fingerprint
based on its meaning.
Speaker 1 (04:45):
Okay.
Speaker 2 (04:45):
So that makes searching super fast and
accurate.
Speaker 1 (04:48):
Okay, I like that.
Speaker 2 (04:49):
Don't worry, you don't need to build one yourself
.
Speaker 1 (04:51):
Oh good.
Speaker 2 (04:52):
There are lots of SaaS solutions for this.
Speaker 1 (04:54):
Plenty of options?
Yeah, all right.
So we've gathered all the info,we've organized it in a way
that the AI can use it Right.
What's the final piece of thepuzzle?
Speaker 2 (05:02):
So we need to augment the prompts.
Speaker 1 (05:04):
Augment the prompts.
What does that mean?
Speaker 2 (05:06):
Basically, we're giving the AI a little extra
context with each question, okay.
So say you ask what are our topselling products in the
Southwest region?
Aaraj automatically adds infolike sales data, customer
demographics, regional marketingcampaigns.
Speaker 1 (05:27):
Oh, I see, so it gives the AI, everything it
needs to give you a really greatanswer.
So, basically, we're giving ita cheat sheet with all the
relevant facts.
Speaker 2 (05:30):
Exactly.
Okay, I like that it's likegiving it a little boost.
Speaker 1 (05:33):
Yeah, that makes sense.
So, just to recap, we can doall of this using existing SaaS
solutions.
Speaker 2 (05:39):
Yeah, for sure.
Speaker 1 (05:40):
So we don't need a whole team of developers.
Not at all or any of that crazyexpensive infrastructure.
Speaker 2 (05:45):
No.
Speaker 1 (05:46):
Okay, that's really good to know.
Speaker 2 (05:47):
Yeah, there are SaaS providers who specialize in our
ag.
Speaker 1 (05:50):
Okay.
Speaker 2 (05:50):
And they take care of all the technical stuff for you
.
Speaker 1 (05:53):
So it's like hiring a contractor.
Speaker 2 (05:54):
Exactly.
Speaker 1 (05:55):
Okay, I like that analogy Right.
So one last question before wemove on.
We've been talking about usingRAG with our internal company
data, but what about theinternet?
Ah Can we bring that into theequation as well?
Speaker 2 (06:08):
That's a great question.
Speaker 1 (06:09):
It feels like there's a whole other world of
information out there.
Speaker 2 (06:12):
Yeah, and that's exactly what we'll be talking
about next time.
Speaker 1 (06:15):
All right, can't wait , I'm hooked.
Speaker 2 (06:16):
Me too.
So last time we were talkingabout RAG and how it can access
your internal data.
Speaker 1 (06:22):
Yeah, it's like having a super-powered research
assistant for your company.
Speaker 2 (06:25):
Right, exactly.
Speaker 1 (06:26):
But you hinted that we could take it even further.
Speaker 2 (06:28):
We can.
Speaker 1 (06:29):
And bring in information from the internet.
Speaker 2 (06:31):
Absolutely.
Speaker 1 (06:31):
That's where it starts to feel really futuristic
, totally Like almost too goodto be true.
Speaker 2 (06:36):
So imagine combining your company's knowledge with
insights from the entireinternet.
Speaker 1 (06:41):
Wow.
Speaker 2 (06:41):
So it's like giving your AI a window to the outside
world.
Speaker 1 (06:45):
Yeah.
Speaker 2 (06:46):
It can see market trends, industry news, customer
sentiment.
Speaker 1 (06:50):
Okay.
So now we're not just lookingat what's happening inside our
company, right, we're connectingit to what's happening out
there in the real world.
Speaker 2 (06:57):
Exactly.
It's like having a team ofanalysts constantly monitoring
everything.
Speaker 1 (07:02):
I like that, so can you give me an example?
Speaker 2 (07:04):
Sure, let's say you're a retail company.
Speaker 1 (07:07):
Okay.
Speaker 2 (07:07):
And you're about to launch a new line of athletic
wear.
Speaker 1 (07:11):
All right, I'm following.
Speaker 2 (07:13):
Your AI could look at your internal sales data.
Speaker 1 (07:17):
Okay To see what's worked in the past look at your
internal sales data.
Speaker 2 (07:21):
Okay, to see what's worked in the past Right.
But it could also check socialmedia trends See what's hot in
fitness right now.
Speaker 1 (07:24):
To see what people are actually talking about.
Speaker 2 (07:25):
Exactly, and it could even analyze your competitors'
websites.
Speaker 1 (07:30):
So we could see what's selling well for them.
Speaker 2 (07:31):
Yeah, and at what price?
Speaker 1 (07:33):
That's amazing.
Yeah, I mean, that's a wholedifferent level of market
intelligence.
Speaker 2 (07:37):
Right, it's not just reacting, it's anticipating.
Speaker 1 (07:40):
Okay, so we're talking about a real competitive
advantage here.
Speaker 2 (07:43):
Definitely, and it goes beyond just market analysis
.
Speaker 1 (07:46):
Okay, how so?
Speaker 2 (07:47):
Think about customer service.
Speaker 1 (07:49):
Okay.
Speaker 2 (07:49):
A customer has a question about a product.
Speaker 1 (07:52):
Happens all the time.
Speaker 2 (07:53):
Your AI can pull up the specs from your database,
but also search the internet forreviews.
Oh, that's smart.
Troubleshooting tips.
Speaker 1 (08:02):
Okay.
Speaker 2 (08:02):
Even safety updates.
Speaker 1 (08:04):
So we're giving the customer the most up-to-date
information possible.
Speaker 2 (08:07):
Exactly.
Speaker 1 (08:07):
That's awesome, but my next question is with all
this information coming in, howdo we make sure we're not
drowning in data?
Speaker 2 (08:16):
Right, well, that's where the AI comes in.
Okay, it doesn't just collectdata, it analyzes it and finds
patterns.
Speaker 1 (08:21):
So it helps us make sense of it all.
Speaker 2 (08:22):
Exactly.
It's like having a team ofanalysts summarizing everything
for you.
Speaker 1 (08:31):
I like that.
Okay, so RIT can do all thisamazing stuff.
Speaker 2 (08:32):
Are there any drawbacks we should be aware of?
Well, as with any technology,there are some things to keep in
mind.
Okay, like what Data quality iscrucial.
That makes sense Garbage ingarbage outright.
Speaker 1 (08:40):
Right.
Speaker 2 (08:40):
So your internal data needs to be accurate and up to
date Makes sense.
Speaker 1 (08:44):
Anything else.
Speaker 2 (08:45):
Security is paramount .
Speaker 1 (08:46):
Oh yeah, especially when we're talking about the
internet.
Speaker 2 (08:48):
Exactly so.
You want to work with trustedproviders.
Speaker 1 (08:52):
Who have strong security measures in place.
Speaker 2 (08:54):
Right, it's like having a good security system
for your house.
Speaker 1 (08:57):
Makes sense.
Speaker 2 (08:57):
Okay.
Speaker 1 (08:58):
Okay, so we've talked about the benefits, the
possibilities, some potentialchallenges.
What's next for someone who'sready to explore RAG?
So first you need to figure outwhat you want to use it for.
Okay, find the right use case.
Speaker 2 (09:10):
Right.
What problems are you trying tosolve?
Speaker 1 (09:13):
Customer service, internal operations, market
intelligence Exactly.
So start with the problem andthen find the right tool.
Speaker 2 (09:20):
That's it.
Speaker 1 (09:21):
Okay, any other advice?
Speaker 2 (09:22):
The AI world is constantly changing, so stay
curious and experiment.
Speaker 1 (09:27):
Don't be afraid to try new things.
Speaker 2 (09:29):
Exactly Start small with a pilot project.
Speaker 1 (09:31):
And see what works.
Speaker 2 (09:32):
Right.
The future of business isdata-driven, and RAG can help
you get there.
Speaker 1 (09:37):
All right, I'm sold.
I think we need to dive intosome practical tips for
implementation next time.
Speaker 2 (09:41):
Sounds good, let's do it.
Speaker 1 (09:42):
Okay, so we've talked about what RAG is and why it's
so powerful.
Speaker 2 (09:45):
Right, we've laid the groundwork.
Speaker 1 (09:47):
But now let's get down to brass tacks.
Speaker 2 (09:48):
I like it.
Speaker 1 (09:49):
How do we actually make this work for our
businesses?
Speaker 2 (09:52):
So the first step is to get really clear about your
goals.
Speaker 1 (09:55):
Okay, so don't just implement RRAC, because it's the
shiny new toy.
Speaker 2 (09:59):
Exactly.
It's got to solve a realproblem.
Speaker 1 (10:01):
So what are we trying to achieve?
Are we looking to improvecustomer service, streamline
operations, get a betterunderstanding of our market?
Speaker 2 (10:09):
Those are all great examples.
Speaker 1 (10:10):
Yeah, so start with the problem, not the solution.
Speaker 2 (10:13):
Right, figure out what you want to accomplish.
Speaker 1 (10:15):
And then find the right tool for the job.
Speaker 2 (10:17):
Exactly Makes sense.
Speaker 1 (10:20):
Okay, so once we know what we want to achieve, Then
it's time to look at your data.
Our data Okay.
Speaker 2 (10:25):
What information do you already have?
Speaker 1 (10:26):
Yeah.
Speaker 2 (10:27):
Where is it stored, is it organized, is it easy to
access?
Speaker 1 (10:30):
That's a good point, because data is the fuel that
powers our red.
Speaker 2 (10:34):
Yeah, right, it is.
It's the foundation.
Speaker 1 (10:36):
But data management can be a real headache.
Speaker 2 (10:38):
Oh, I know.
Speaker 1 (10:39):
Any tips for making that process a little less
painful?
Speaker 2 (10:42):
Don't try to boil the ocean.
Okay, start with the datathat's most relevant to your
goals.
So, if we're trying to improvecustomer service, focus on
customer interactions.
Product information supportdocs.
Speaker 1 (10:54):
Keep it manageable.
Speaker 2 (10:55):
Right Prioritize.
Speaker 1 (10:56):
Okay, so we've got our goals defined and our data
is prepped and ready to go.
Speaker 2 (11:00):
Okay.
Speaker 1 (11:01):
How do we actually choose the right R-Rad solution?
Speaker 2 (11:04):
Right, so there are a lot of providers out there.
Speaker 1 (11:06):
It's a crowded market .
Speaker 2 (11:07):
It is, but don't let that overwhelm you.
Speaker 1 (11:09):
Okay.
Speaker 2 (11:09):
Good, just keep a few things in mind.
Speaker 1 (11:11):
Okay, what are those?
Speaker 2 (11:12):
Ease of use.
Speaker 1 (11:13):
Ease of use.
Speaker 2 (11:13):
Okay Can you integrate Systems?
Is the interface user-friendly?
Speaker 1 (11:19):
Yeah, we don't want something that requires a PhD to
operate.
Speaker 2 (11:22):
Exactly you want your team to be able to use.
It Makes sense.
Speaker 1 (11:25):
What else?
Speaker 2 (11:26):
Scalability.
Speaker 1 (11:27):
Scalability okay.
Speaker 2 (11:28):
Can the solution grow with your business?
Speaker 1 (11:31):
As our data volume increases.
Exactly so it's got to be ableto keep up.
Speaker 2 (11:35):
Right, it's like choosing a car.
Okay, compact car might be finefor running errands.
Speaker 1 (11:40):
Yeah.
Speaker 2 (11:40):
But for a cross-country trip you need
something bigger.
Speaker 1 (11:43):
Makes sense, so we need to choose a solution that
can handle the long haul.
Speaker 2 (11:47):
Right, what else it's security?
Speaker 1 (11:49):
Security, of course.
Speaker 2 (11:50):
This is super important.
Absolutely You're trusting thesystem with your data.
Speaker 1 (11:55):
So we need to make sure it's protected.
Speaker 2 (11:57):
Top-notch security measures encryption, access
controls, compliance.
Speaker 1 (12:00):
All the good stuff.
Speaker 2 (12:01):
Right.
Speaker 1 (12:02):
Okay, so we've talked about the tech side of things.
Speaker 2 (12:04):
Uh-huh.
Speaker 1 (12:05):
But we can't forget about the human element.
Speaker 2 (12:07):
Oh, absolutely.
Speaker 1 (12:08):
Implementing RG successfully.
That requires communication,training, support.
Speaker 2 (12:11):
It's a team effort.
Speaker 1 (12:12):
Yeah, we need to bring our people along on this
journey.
Change management is key.
Make sure everyone understandswhy we're doing this.
Speaker 2 (12:18):
Right.
Give them the skills they needto use it.
Speaker 1 (12:20):
And be there to answer their questions.
Speaker 2 (12:22):
Exactly.
Speaker 1 (12:23):
Okay.
So as we wrap up this deep diveon RAG, what's the one key
takeaway you want our listenersto remember?
Speaker 2 (12:30):
AI can seem intimidating, but RG makes it
accessible.
Speaker 1 (12:35):
Accessible and affordable.
Speaker 2 (12:36):
Right For businesses of all sizes.
Speaker 1 (12:39):
So, identify your goals, get your data in order,
find the right provider.
Speaker 2 (12:45):
And don't be afraid to experiment.
Speaker 1 (12:47):
Start small, learn as you go.
Speaker 2 (12:50):
Exactly.
Speaker 1 (12:51):
The future of business is data driven and RAG
is the key.
Speaker 2 (12:54):
Couldn't have said it better myself.
Speaker 1 (12:56):
I love it.
Well, thanks for joining us onthis deep dive into our rag.
I hope everyone listening feelsempowered to explore this
incredible technology and seehow it can transform their
business.
Until next time, happyinnovating.
Speaker 2 (13:08):
See ya.
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