Agentic AI and No-Code Automation with Integrail

Transcript

can we just stop talking about AI already well no because it's all around us and it's only going to get more and more into our daily lives and what is Agent Ki what does it really mean how will this wave literally change the way we work what impact will it have not only on your jobs but also your daily lives in episode 95 of JT WGT we talked to co-founder and chief product officer at integraal Anton anti with $1 million in seed funding just secured and backing from ratmir timet integral is leading the charge in no code AI powered

business automation so let's keep this conversation going around AI this is episode 95 of great things with great Tech with Anton anage from Integra AI let's get into it hey Anton welcome to the show it's great to have you so look before we dive into the world of agent Ki and and that means for everybody in this world moving forward um and before we talk about integral um I want you're really interested in yourself um we've got a little bit of a crossover obviously at them software but take us back to your early days um you know your love of

computing where that came from and how you came to be you know the co-founder of integraal ah thank you thank you Anthony for having me and uh this is a dangerous question because uh I'm getting younger and as people get they tend to you know be be nostalgic about the youth and stuff I love Nostalgia yeah but yeah no actually funnily enough I wanted to be a nuclear physicist since age of six wow because I had an aunt who was a physics teacher and uh she really got me into it so that's who I almost became actually and

I always loved you know research I majored in physics but uh eventually due to mostly commercial considerations I moved into the software world but obviously me physics and programming development they quite connected so that uh that allowed me to uh actually launch my career as a developer at some point after the university but uh then after some years I moved to the business side of things so wow yeah okay so just just small aspirations when you were young to become a a nuclear physicist and stuff like that pretty crazy I mean it's it's

it's pretty cool though so you had an auntie who was doing it and you know and and to you're Russian and in that in that in that world like that's obviously a big thing right like technology that thing is huge in Russia to be able to lift yourself up and and you know become something significant right so there must have been a great feeling so what what did make you switch I mean I know I hated physics I actually I flunked physics actually in a 10 so I didn't I I loved it but I wasn't any good at it um so it's actually quite

interesting that you know I've become interested in coding later in life but I don't think they should mix I love space all that kind of jazz um yeah where did you start like in terms of software did you start as a developer um in any particular company were you're doing any any specific platform or were you just doing generic stuff yeah well yeah I mean I was actually doing some development while I was still uh doing physics research because there's a lot of stuff you need to calculate and everything so that that obviously gave

me some experience but then yeah it's it's a connected question as well because I uh finished University in the year 99 or so or 98 and that was not a good time in in Russia because Soviet Union sort of um uh broke down and there was an economic crisis and uh working as a physicist did not really pay your bills but at the same time it was uh a com boom yeah and during that time companies first discovered this offshore Outsourcing thing and uh of course everybody thinks about Indian companies but actually at that time Russian

companies were quite popular as well so there were many of those actually in Nova cers where where I started so I just went to that one of those companies called novasoft and I just started coding stuff for uh you know for the Doom companies so we were creating like online stores before Amazon and this type of thing of course everybody who we worked for died out but it was a good experience good experience yeah great time to kind of do that like again I was I was flunking University during the.

com boom and trying to work out what I wanted to be but I remember it all happening I mean I was more interested playing computer games but anyway digress um so you ended up an interesting path like um if you think about like the you were at V for a while but before that you at VMware um you know so you obviously got into that sort of operational side of things so talk a little bit quickly through that what you did at V and then because I think it's it's obviously connected to to ratmir and and what he did at ve and obviously

rat me is a big part of integraal as well so you know talk a little bit about what you were doing at ve and and how that prepped you for this next step after you left v a few years ago yeah uh it's um it was beam I mean like you just mentioned you you were part of it as well that that was probably the most amazing story career-wise and uh just building something cool and big uh and uh being a part of that was was definitely a great experience and uh for those who don't know VI grew from zero to 1 billion in Revenue in about 11 years I want to say

and actually there's a funny story behind it as well so um I was U uh working for Microsoft before VMware yeah um and uh when I decided to switch to VMware I met radmir uh right away because he founded VMA 2007 I think and I I went to VMware in 2007 so the guys who worked at Microsoft they looked at me as I was crazy because VMware was pretty small company at the time and they were like how do you leave Microsoft and go there and here I meet the guy who says we're going to be doing backup for VMware so for this small

company that that not many people know and he says we're going to be one billion in 10 years I was like polite I didn't want to argue with crazy people so I said okay good luck but then obviously we we became friends we exchanged like ideas on how to grow the company I was with the for about three years during all this time we were friends with RAR then eventually yeah I moved to be uh and switched more to operational roles because I did enjoy kind of processes uh defining things more formally thinking strategically about what we need to do

where we need to go etc etc but them I mean it's you you know it's impossible to to describe in in five minutes like every year we had a new challenges and it was just a great right all together yeah so after after vame you you you went off on your own still staying close with ratmir obviously and what what did you do in in the time between leaving ve and creating integral and then let talk a little bit about how integraal came to be what was the spark what was the idea for the company yeah so actually you know my

physics Roots uh it was genuinely what I left doing actually so I I actually missed research and uh I tried to follow more in the space of Computer Science and Mathematics eventually but they are quite connected anyway so after after them I made a pretty good exit so I could you know take a break so I I took a break actually I uh was doing some looking around and in what was going on in the world there were no you know clear waves uh yet but I always liked thei I I read a bunch of classical books so I tried to follow the research and

eventually when llm so large language model started to appear that was definitely something interesting so I invested in a couple of companies that were doing something uh in this area uh actually one of them I joined also as a CEO and then worked with them for about two years they were doing first machine translation but then they switched to llms and sort of expanded their stack so that that was a nice experience but then it was still you know it was kind of um all intermediate because basically after whim I didn't see myself doing something

fulltime I just took some time to figure out what what is interesting but yeah when GPT three appeared uh and it started to become clear that we can take this actually very old notion of agentic AI because it's been in the OR world forever everybody started talking about it only last year but it's a very concept actually it's just that llms give you a very good way to to start building those agents okay so at the time we were building another company uh where rir became an investor uh I started this company with my old partner

from VMware uh mik schwi and and it was completely unrelated to to yeah or even infrastructure world but we started experimenting with the agents uh in frames of that um company and then very quickly I realized that actually building a platform that allows to create any type of agent I want would be really cool I I just basically wanted to play with agents I was reading the search papers I wanted to have agents for myself and that was sort of the prerequisite to creating uh integral um yeah I was was I was going to say so

every every a lot of companies I speak to you know their their founding story or their Genesis is basically from somewhere unexpected right like they're doing something else they're working on something that is completely different and then there's a little spark of something within that and then from from that something grows because you realize hey maybe this is what I should be doing so this this was the spark for you know putting together a few loves of yours and then working out exactly what you wanted to do and thinking that you had

something that you could take to mark and that people could actually get some benefit out of yeah yeah yeah exactly and also you know it's it's a bit of a funny story but uh uh like we were just uh discussing rir timf who be's founder he's really great uh entrepreneur but in general great personality so absolutely I was him after leaving VI as well so I tried to sell some startup to him or some startup idea and I was coming with this with that with this and he he was never interested it's like no I I don't care but then as we started um doing the

CI stuff and I started writing about it on LinkedIn he got interested he called me we brainstormed together and basically that was when integr was born yeah but in terms of inspiration I just wanted to share because I think this is also interesting I I found one research paper uh where a team of scientists created an agent that explored Minecraft world and um my son would love this my son my son is addicted yeah and they had some new really cool ideas there and the most interesting that sort of stood out to me was that they built a library of

skills for this agent where every skill was generated in response to a certain you know environment or whatever and this way this agent was kind of self-learning and it became like the best player in Minecraft so we decided why don't we take this idea and just move it to the real world and that's actually the kind of of you know Advanced the ages that we're building where each of them has a skill Library which they able to develop themselves and this way they become more and more powerful so that was original Vision

which we're coming back to right now that's pretty cool I'll tell my son that literally I think he's playing Minecraft right now so he's basically a bot himself anyways he's really good at it um let's talk about the name is there any significance to integr the actual name or just a just a cool name just yeah it's just a word play that we integrate easily and also there is AI in the name because it's integrate AI lse so combining Ai and Integrations and Ian Holy Grail a little bit as well yeah I was going to say

about that as well that that's what I was kind of like leaning towards but no it's pretty cool like all right it's all good it's a it's a good name anyway so you know we've talked about agents we've talked about you know llms and what and what you're doing so what what is integral's main purpose you know from the point of view of of what's what's the problem you're trying to solve for people and for businesses and organizations yeah that's um I mean that was my original inspiration that that still continues basically I believe that

we had several big technological waves as we all know and uh we actually used it at VMware and I think we used it at Vim as well they had this really nice slide where in it there was invention of computer computers then there was invention of internet then there was virtualization and that's it there were like three big waves yeah I mean if you go back in history there was Industrial Revolution itself like invention of the steam engine and then then you know the G hry Ford Etc so all of these waves really changed the way we do things

quite significantly this AI wave in my strong conviction people very much underestimate the way it will change uh how we do things and maybe we will touch upon some contract examples of of where where we can come to but basically it's a huge wave and I just wanted to you know participate in that wave and enable people uh to create like AI helpers because AI agents are basically AI helpers that they control not some Corporation gives you because when a big huge corporation gives you something they want to make

money on you and I know sounds a bit naive because obviously we're building a business as well but still sort of in our DNA we want to give people full control that it is your AI it acts in your interest you know what's inside of it you know how you build it and so that we want to give people the ability to express their creativity by building those AI agents and you know part of this inspiration also comes from success of mid Journey uh that was the first company that was creating this text to image uh type of things and they create

really beautiful images and I cannot draw I I draw like very terrible yeah I'm horrible as well horrible yeah but still like people are creative if you give people the ability to create something and they want to create so I really love bordia I just I type some prompt and I get very beautiful picture so we kind of want to do the same with agents eventually we're not there yet because now you need to you know move the boxes and connect them but version we we are getting much closer just you write the description and the agent is

getting generated for you so it's still in that sort of general direction I think that's a really good um connection and analogy to use because how creative can you be and I know that people that have got some slight level of creativity put that together with what LMS and chat Bots are able to do through prompting um it's it's it's unlimited right it's Limitless because if you've got enough in here to be able to get some information and tell the AI to do something through your fingers and through the chat bot and then if the AI

is capable enough like you said it's it's it's it's it's changing the world it already is right like I know that I've I've been working this week on a little like custombuilt SAS application that I'm going to have because nothing that I've used in in in my role does everything that I want so I thought to myself why can't I just build something with a better help from AI as an example right so I fully believe that this is possible and the thing difference there which I think with integral can actually help is that in myself I have enough

capability to be able to use code you know use Python compile a web server do this do that and kind of put it together myself but the majority of people don't have that so from what I see integral is enabling to give them a platform to not have to worry about too much of the of the ground knowledge that they need and just start building the cool stuff to help them and make their lives more efficient is is that kind of the idea of of the platform yeah definitely but I mean not just that because I mean as we discussed

I also have a developer background and uh I mean I was always sort of interested in solving uh difficult problems and actually I recently finished a book on uh husk language so I mean those who know this is a functional language in which all all of the research in computer science is taking place the problem is the learning curve is a bit stick but I really loved its connection to mathematics and I tried to you know Express a certain way of learning it so I am pretty deep into computer science and development and I understand that

developers like to code however I can bet like with any uh developer I will be developing an agent using integr they will be developing you know using Python and stuff I will be 10 times faster at least and I like coding but it's just so much easier I mean if you can change things here there move stuff around why it's concept no code yeah no code is getting yeah no code is getting popular right and I've seen this more and more in the last 12 months um it's almost how the industry's gone away well not completely but the fundamental idea is

that if you can make something simple and a drag and drop interace that does the leg work for you you know you're just going to become more and more efficient that that's what I wanted to say sorry for cutting you off yeah yeah yeah uh yeah exactly but um also uh what what was my other thought um drag and drop interface and no code okay it'll come back to me that's okay that's okay let's talk about agentic AI first before we get into the interface before we get into you know the components that make it up agentic AI is something that

probably came up what 12 18 months ago people started talk about agents and all of a sudden it was agentic AI a fancy way of saying that the term we're hearing more and more so how would you define it in simple terms and why is it so important for individuals and organizations yeah that's a great question and actually we had lots of arguments internally with uh including with radmir on this topic because I I a bit of an old school like I said actually agents in AI has been forever it's if you read the classical book

artificial intelligence the mod approach I think that now they have the fourth um uh fourth uh iteration of that book uh the first one that included something about deep learning but they started probably 25 years ago so all they talk about is agents and I mean in essence an agent is a very simple thing it's basically someone who can understand the outside world and take an action in it so the best example to think about agents is is as humans we are agents uh because we can understand the world around us using our uh senses uh we can

process what's happening we have some knowledge We Have Skills we can make decisions and then we can make a change in the outside world using you know hands and mouth or whatever else we want so with the agents specifically when we move to llms it it's pretty much the same it's not just the chatboard to to which everybody is now familiar but also you give kind of a brain built out of LMS it can be one llm it can be several LMS that help each other reason that correct each other Etc there are different you know templates you can use

and we provide them as well but in addition to this brain you give them knowledge which is uh your corporate sources or the ability to search internet or just something custom you want to build anything like that can be made available to that LM to make better choices better decisions better responses and then the second most important part is you give it ability to perceive the outside world so in our case all kinds of software and web the environment in which they live but I mean nobody prevents you from building

an agents that works for instance with with Smart House you just need to give some sensors that provide information and it will be able to help you so sensors to understand the information and then tools to make changes in the outside world and in our case it's basically API calls uh through which you can update different systems and also the beauty of LMS and in general gender CI in general is that and and this is actually very new addition to integral just coming out last week we finally created this what we call Universal API

node which allows you to connect to any system that has an API automatically you don't need to do anything you just put documentation and you get a Noe that automatically does what you want so this creates really unlimited stuff you can connect to any system get data change data so now literally the agents you can create are just limited by our imaginations and sometimes we like it so we invite everybody who wants to have ideas to to do that yeah yeah I mean that this is like automation on steroids like you know it differs from

traditional Automation and in our world of infrastructure of code you know automation was to do a certain task but it was typically only to do one task right a very specific task and typically you wrote that automation to do one thing and that was it and then you kind of stepped away let it do its thing and it never evolved just you had to update it every now and again this is this goes beyond that because if you're able to create something that and like like I've seen your platform allows you to connect to multiple LMS um with that with that

node which is I see that as like an API proxy on steroids right like if you've got a little node that I'm really interested to take a look at that by the way and really look at it already I'm thinking about all the ideas that I can do um and that's the great thing about this how does the role of like vector memory rag retrieval augmented generation I mean obviously that's part of it so how does that come together with agents to make someone again more efficient I mean you mentioned the knowledge obviously going out with the

with the retrieval augmented generation it's about getting outside knowledge putting that in context with the LM and and with your prompt to make it smarter and more responsive to that um how do you how do you equate that like in simp terms when people talk about we hear it all the time Vector memory retriev augmented generation agents operators like in context what does that mean right right yeah this is this is a great question and this is actually um a very important question which many people also don't realize like now I see often

in in social media people saying something like well I asked chpt this and it told me this and it just makes me cringe because uh it's a well-known fact that all of the Lambs socalled hallucinate uh which means their architecture the original paper where the architecture of all current LMS was done is called uh Transformers yes what they do and they do very well they transform one type of text to another type of text so it can be structured it can be unstructured doesn't matter they do this job amazingly and and there are very

interesting consequences of for this which we can uh touch upon later but it also creates this problem basically again this architecture just means that you put some symbols some text as input they have to produce output there is no other way so they will produce an output no matter what yes you can give additional instructions fine tune Etc so that it tries not to deceive you specifically but this creates a very big conundrum because if you're not an expert in some area you can never be sure the answer it gives you by itself

is it correct or not and if you are an expert you don't need to ask in the first place and it's like okay so what are they useless no they're not useless and this is where rag or retrieval augmented generation comes in so basically the way rag works is that as part of input there is no black magic that you know there is nothing like uh crazy or rocket science but you ask a question but then as part part of input in the background we give a certain document a PDF file or something from the web or something that we found in

our corporate database by converting first out documents to So-Cal vectory representation because they allow to search much better but the point is we put additional correct context as part of the input to the llm then hallucinations virtually disappear because it uses this context as the primary source to provide an answer answer so basically what people try to do now they create such rag approaches that puts the truthful The Good the correct context as part of the llm interacting with you and then they provide the good answer so this is sort

of the way to overcome this hallucination um issue the next step is you can also fine-tune yours but that's Advanced thing and actually I don't know I think 95% of issues are solved via Rec uh quite efficient yeah yeah yeah and you know and then there's the concept of the actual LM itself whether it be a local one or even you know the ones that are releasing I think today with 4.

5 got released to Pro on on open AI it's just get like you said it's getting quicker and quicker and more advanced the number of parameters that are in the model make a big difference in terms of the amount of knowledge that it has the foundational knowledge to maybe not hallucinate as much but there's still going to be that level of hallucination because to your point that's exactly why they exist exist they they exist to to take an input that they've been trained on and create something from a question and they're not they're not sure that

they're they're correct right so you always have to check it and then adding the thing that made me think a little bit there is even though we inject real information um or or any information from any Source right how does it still how does that make it less likely to hallucinate at the end is it because it knows that it's getting data to work with in that in that instance or is it just something that helps it understand to not search too much for other bits and pieces to augment the information in the response uh yeah it also depends on the

system prompt instructions that that you give to it but normally yes the immediate context llms tend to treat with much higher priority than whatever they have learned internally so even even if you know the internal probabilistic architecture makes them to produce certain answer uh they will take this as as the correcting uh data and so they tend to do something that's much more aligned to the immediate context it's also just the of the I mean it's like we were discussing with you previously I think there is also analogy

to humans so there is all the knowledge I know I learned during my life but then if you think about it how much of this knowledge you don't even think but it's based on false assumptions like you read a headline in some media uh that you know referenced maybe some report by by British scientists and you think this is true but then maybe several reports came out that adjusted this this data or or maybe even completely overturned it you have no idea you still think this is true yes sort of the thing that happens with llm

they learned a bunch of stuff during training they try to produce what they know based on this learning but then if you talk to me and you ask me a specific question and I do research I open a book I read it I find papers I put it kind of in my operating memory right and then I give you a response based on this knowledge that's fresh and new in my mind this is kind of what what D does so yeah that's an augmentation situation yeah let's move quickly to um you know building AI applications is traditionally complex right well when I

say traditionally only the last few years because that's what when it's really taken hold but from a generative point of view so what makes integrals no code Studio and how does it sort of democratize this AI for businesses yeah you know this is a great question because actually what we found is that it is difficult for people to break down what they want into a flow so if if a person knows how to break down the process they're working on for instance or their job description or something into a flow like first I do

this I take some data from from my CRM then I read an email then I make this decision if they're able to do that they would be able to build an agent very fast because it's basically one-on-one mapping but what we found is that uh a lot of people struggle with that so what we are trying to do now we want to simplify our interface even further we're actually using a lot of generation under the hood right now our new version comes out in May uh with the new architecture and uui is there as well so basically there we will not ask people

to connect you know specific fields to some specific fields which can be a bit daunting uh but we will just say okay here is the first box read my last 10 emails the second box like sort them by I don't know date or whoever sent them the second lolm box do this and that so basically just natural language sort of interaction with what you want to build and even on top of that we want to have sub generative assistance to give people ideas uh what is possible which systems you you can connect with etc etc basically again our big vision and the

movement towards is simplifying as much as possible and that's what we want to continue doing and that I was going to ask you give me a a sort of real world example but you just have like in terms of that so the question that I've got to ask as we as we're running out of time but I I want to really ask this is where does this leave humans like in terms of in 12 to 18 months we we talked about you know maybe we can't go as far as 5 years because everything is moving so quickly but if we're going to make everyone's life automated through agents

and this is I believe this is the this is going to happen like people are just so leaned into this because what I've seen going to Microsoft conferences listening to how people are talking about the whole premise is based on people doing less people being lazy people you know making their lives a little bit more comfortable right like I think it touches a really interesting psyche in in our human sense this whole world right um so where do you think how far does this go if we get if you get Adent right if intergr Mission succeeds

what what are people's jobs going to look like yeah you know this is this is a great question which a lot of people uh debate from different angles u i mean to me the way I see it is that um AI agents are able to take out the boring the mundane from your lives from your jobs because the first jobs we automate are really you know data entry I mean it's demeaning to people you you you take some PDF you read it you type it like and there is in corporations there is probably millions of jobs like this but this can be done by agents very

easily so what we want to do we want to free up humans for Creative work because still finding out and creating really new things even though some people will argue with me but still llms will not be better than humans and that and this is where what is fulfilling what is gratifying and then we can you know solve difficult problems we can make tough decisions Etc and then we will have agents that do the gr work for us and it kind of if you know what you're doing if you're willing to take that step if you're willing to learn yes it

requires some learning it's not it's not going to be easy but if you become that person and you have a team of Agents working for you you become you know 10 times more powerful 100 times more powerful so that's kind of the problem I I I get that I have had that answer and I've heard that response I think a couple of episodes ago I've had it even last year at some point similar response to automation makes us more efficient ai ai generative Ai and agents allows us to free up ourselves to become better at being more creative and actually being

more um more forward thinking and maybe even more technically Advanced ourselves because now again like you said we don't have to worry about the mundane we can almost unlock the creativity that makes us think further ahead which potentially we don't get to do because we're so bogged down by all the other stuff right so will that mean and that that creates a a flywheel effect of you know we're getting we're going to write more and more agents to make us more efficient we become more efficient we write more agents to create that to make it more

efficient and then so on so it's actually an interesting trajectory that we head towards as as Humanity um I've heard all sorts of people talk about this and terms of where it's going with with sentient Ai and AGI and whatnot I think at the short term your platform allows people to be really good and really efficient at their jobs at those tasks without having to know any coding because that's the whole point of it having a no code drag and drop and like you said you're even going to get to Natural language interface to help

them build that out which is taking it one step further I think that's really going to be helpful is are there any industries that you're targeting specifically to start with is is there any any more is there any one industry that's paid more attention to you guys than any other that you've noticed already I mean finnally enough we have a bit of bias to financial industry but there's no specific reason behind it uh I mean the agen you can create a pretty um hor horzontal but we just probably had more interest from those

guys for some reason yeah well you just like we haven't even really we didn't really talk about and it's it's bad of me for doing this usually I would say this straight away the founding was only just last year right like in September roughly I think yeah we launched end of September yeah right yeah yeah yeah yeah yeah and then obviously um recently as much as a week ago when when as this recording is done ratmir um we talked about kof and V and entrepreneur and very successful and a great guy um um you secured 10 million of seed funding

you know through that vehicle as well so and you also appointed a new a new CEO um so talk a little bit about that and how that helps you in this next phase yeah thanks that's that's a great point because uh uh also you probably noticed there are lots of platforms that you know try to do similar things that we do where we sort of pride ourselves is that both R and myself become from Enterprise by we know how to work with Enterprise customers how to build big companies working in partnership with the channels

which is another big thing which kind of s made people forget and that's what we're trying to do here so with the arrival of Peter GTI who is our a new CEO he has tons of experience in the ipace he worked for companies that were doing that quite successfully in the development space software development I mean and basically we are targeting them entprise Market we're building a very strong Professional Services Consulting team because again what we realized is that people don't really know where to start okay uh everybody's talking about

AI people have budgets but they don't know okay what do we do so we come we help them find we don't do like know gr strategies we help them find two three use cases that bring huge Roi right away we build them and then we sort of expand from there and that's our strategy at least for the upcoming year then we will see and just quickly as well just to so people understand it's it's a SAS but there's also is there also an on-prem version that can be deployed as well exactly we we are focusing on on Prem yeah uh we started

with kind of a mixed mode but we realized that for Enterprise customers and especially in Europe actually on Prem is a magic word so this is what we are moving towards yeah that's but the but the SAS platform will still be there um as well to basically build out and then what you're talking from an Enterprise perspective when you get customers obviously from a data privacy point of view maybe they want to connect to a local LM of their own that they've trained it makes more sense to to have a the platform Deployable on Prim as well

it's a full hybrid hybrid setup yeah I mean for SAS initially we started like full Bown s but uh since we're switching to this Enterprise friendly architecture we will keep the S version but it will be more like what WordPress is doing right so you take your own instance you put it somewhere in the cloud you can work with it so that's pretty cool and I think that's also quite a unique outlook on it as well right and maybe a bit of a poin to where things are going within this world at the same time where again

everyone talked about SAS being the end game and everyone was going to go SAS because it was just better but you know from the way that we and this this mirrors what people thinking about with just hybrid cloud in general is that on Prem is actually more as important to consider for larger businesses because of again all the all the compliancy all the regulation and this the the data security because we are talking about you know very serious um data that is going into it and very serious work you mentioned financial institutions so you

know this isn't just asking a chatbot to get the weather yeah exactly awesome well hey this has been fantastic just just finish off by you know if you were going to sum up in in in a minute you know um where people should go for integral what they should expect um and what you guys are doing in the next six to 12 months just just finish this off with that yeah so basically again we are moving very much towards simplifying with further how to build agents because again our DNA our initial Vision remains we want everybody to build as many agent

as they want to help them you know in life in business anywhere else and actually this is something I encourage everybody to start thinking about because if you're not using a agents in your life and job today you are becoming more and more at risk of you know being left out it's just you have to there is there is no other way around it and whether you use Integra or something else up to you of course we encourage you to use integr because we love it and believe it's good but uh in general just go there no matter what you do do AI

yeah great stuff great finish hey thanks for being on the show it was it was a great episode as I thought integr going to do some great things looking forward to seeing where you go thank you very much thank you Anthony

Agentic AI and No-Code Automation with Integrail | Episode #95

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