From Grunt Work to Creativity: Automating Marketing Tasks - Lutra AI

Jiquan Ngiam, Co-Founder and CEO of Lutra AI, discusses his career journey Stanford University to eventually founding Lutra. He shares how Lutra helps streamline workflows by assisting with data prospecting, lead enrichment, and automating repetitive tasks. Jiquan also explores the balance between AI and human creativity in marketing, highlights his vision for making Lutra user-friendly for non-technical users, and encourages listeners to explore its potential for automating their workflows.

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About Lutra AI

Lutra aims to revolutionise automation and allow users to easily create AI-driven workflows. The platform simplifies complex processes, helping automate tasks and optimise work effortlessly. Whether you’re managing data, streamlining operations, or integrating apps, Lutra makes automation accessible to everyone.

Since its launch, Lutra has been empowering businesses to boost productivity and focus on what matters, eliminating the barriers of traditional workflow tools and delivering a seamless automation experience.

About Jiquan Ngiam

Jiquan Niam is the CEO and Co-Founder of Lutra, an innovative automation platform. Before founding Lutra, Jiquan was a key contributor at Google Brain and studied at Stanford University where he achieved a PHD in Computer Science.

Jiquan Niam is a driving force behind AI-driven automation and is passionate about making advanced technology accessible to all.

Time Stamps

[00:00:18] – Jiquan provides some background to his career and why he founded Lutra.

00:02:44] – Overview of Lutra’s Purpose and Functionality

[00:09:36] – Enhancing Marketing Efforts with Timely Data

[00:15:16] – User-Friendly Interface and Accessibility

[00:20:23] – Marketing Strategy: Product-Led Growth Approach

[00:23:27] – The Future of Marketing Roles with AI

[00:26:19] – Advice for Young Marketers: Embrace Technology

[00:28:30]- How to Get Started with Lutra

Quotes

“I felt like education was this new superpower that I could give people.” Jiquan Ngiam, co-founder and CEO of Lutra

“AI will not replace you, but a person who’s using AI really well is going to do a lot more than you.” Jiquan Ngiam, co-founder and CEO of Lutra

“Help the team understand, investing into understanding this technology and using it… It’s going to be potentially very game-changing.” Jiquan Ngiam, co-founder and CEO of Lutra

Follow Jiquan:

Jiquan Ngiam on LinkedIn: https://www.linkedin.com/in/jngiam/

Lutra AI website: https://lutra.ai/

Lutra AI on LinkedIn: https://www.linkedin.com/company/lutra-ai/

Follow Mike:

Mike Maynard on LinkedIn: https://www.linkedin.com/in/mikemaynard/

Napier website: https://www.napierb2b.com/

Napier LinkedIn: https://www.linkedin.com/company/napier-partnership-limited/

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Want more? Check out Napier’s other podcast – The Marketing Automation Moment: https://podcasts.apple.com/ua/podcast/the-marketing-automation-moment-podcast/id1659211547

Transcript: Interview with Jiquan Ngiam at Lutra AI

Speakers: Mike Maynard, Jiquan Ngiam

Mike: Thanks for listening to Marketing B2B Tech, the podcast from Napier, where you can find out what really works in B2B marketing today. Welcome to Marketing B2B Technology, the podcast from Napier. Today, I’m joined by Jiquan Niam. He is the co-founder and CEO at Lutra AI. Welcome to the podcast, Jiquan.

Jiquan: Thank you, Mike. I’m really happy to be here in a podcast with you. Thanks for inviting me.

Mike: What we’d like to do to start off with is to understand a little bit about you personally. So I don’t know if you can tell us a little bit about your career and why you’ve chosen to found Lutra.

Jiquan: Great, yeah. So my career really started in a deep interest in AI, artificial intelligence technology, all the way back to days in Stanford, actually, when I was working in a PhD program with Andrew Ng as my advisor, looking into deep learning technologies. And this was like 2009, so 15 years ago. So been working on that. And then what I realized back then was, you know, the power of this technology is so amazing. It turns out that I actually took a little detour to try to teach more people about this technology, and ended up starting a startup back then called Coursera. So an ad tech company, where we’re trying to democratize education. Spent many years at Coursera, built the first online machine learning classes, And after that, I went on to Google Brain. And this was around 2017-18 when we saw the transformer technology that you’re seeing in AI start to take off. And then I was in Google Brain for four and a half years, left and started Lutra last year, where we really saw a momentous shift in the technology and what it could do. And so last year, the AI technology went from not only generating content, generating images, but starting to be able to do a degree of reasoning, planning, and understanding how to work with software, work with code. And to me, that was a really exciting moment because it started to highlight the possibility for AI, for the machines to understand what we want to do and translate it into how software could work. And therefore, we might be able to start delegating more and more to the computer to automate to do the groundwork, the manual stuff that I’ve seen my own teams do a lot. We can start to give it to the computer in very natural ways for it to take on instead. And so Lutra AI, that’s what we are all about. Can we help you get more done? Can we help you automate, streamline your work and processes through this technology that allows you to then interact with the software you use, the APIs you use in the backend and so on?

Mike: So, I mean, that’s fascinating. And, you know, it’s quite unusual because actually Lutra is not a marketing tool. It’s a very general purpose tool. So I know it’s used in marketing. We’ll come to that in a minute. But can you tell us a little bit about, you know, some of the customers who are using Lutra and the range of things they’re using it for?

Jiquan: Yeah, great question in there. So some of the customers on Lutra, this is very general too, so we do see a wide set of use cases. But I think one of the most interesting use cases of Lutra right now is data prospecting, gathering information about your leads, the people that you want to reach out to, and really helping you get that data back into your CRMs, your ecosystems, your databases and spreadsheets. And so maybe I’ll give you a few examples of how people have used Lutra. So in one example, normally you have this list, right? And maybe it’s a big list of people attending a conference or maybe a big list of companies there that you might be interested in. And for each of these people or companies, you want to go and get a bit more information about them on the internet. You know, what a company is doing, how big it is, who their CMO is, you know, and maybe who the CTO is, right? And then come bring that data back and say, are these people, are these companies qualified leads for me? So what Lutra can do is to say, OK, take that data, go do that internet research, bring it back into your spreadsheets or your HubSpot, and then figure out that data and whether it fits your criteria. And then once it fits your criteria, you can ask Lutra to do more. For example, say, OK, I found a name, Jerry at this company. Seems like a good fit there. Can you, for all the names in this database I have, go and figure out things like when were they last mentioned in the news? Did they have anything posted recently? And I bring that back again and say, Lutra, can you go and figure out this is the right time to reach out to them? So in this case, some of the early customers we have, what they do is that they have exactly those workflows, which is using Lutra to, in real time, get data from the internet to be able to help their prospecting needs, help figuring out intent signals, very custom to their processes, and use that to drive their lead gen efforts in there.

Mike: That’s really interesting. I mean, you mentioned something there. You said something about being able to go and get data or put data into HubSpot. I mean, I think people were listening to it and thinking, yeah, I’ve seen ChatGPT enrich data before. But actually, you’re talking about working with data in different systems. So tell us how you do that, because that sounds like it’s a bit different from a lot of the other LLMs that we hear about.

Jiquan: So what happens in a lot of LMs that you work with today, the LMs are not really connected into your ecosystem of applications you use. There’s still a gap between there. The LMs don’t fully understand how to get and push data into those systems. So what we find is that people are often copying and pasting stuff into ChatGPT, trying to get something out of it, and copying and pasting it back. And that’s a very slow manual process. It doesn’t scale. You can do that, say, if you had a table of 100 entries, you don’t do that for every single entry. You’re not going to copy and paste 100 times. It’s just not scalable. So what we do is that we enable Lutra to natively understand APIs. And APIs, what it means is, it stands for Application Programming Interfaces. And what it means there is, there is a natural way for software to communicate. In software, you talk to APIs, which are these technical boundaries and how system A and B can interact and understand each other. And what Lutra does is it uses AI to then understand the APIs between systems. So this is how I pull a list in HubSpot. This is how I update a custom property in HubSpot. This is how I can go to the internet and get data. And then this is how I can extract data from it. And so you put it all together, what you get is that Lutra, this AI system, is able to then orchestrate across those possible actions and to achieve tasks for you. So here’s a very concrete one that we actually had a user do recently, which is they needed to update their contact information in a database with what’s going on on the web right now. And this is real estate agents, actually. So what they wanted to do is that they’re just an internal database of HubSpot database of 7,000 real estate agents. And what they needed to do was to look each of them up, go to their websites, figure out if their emails and phone numbers have changed. Sometimes they do update or if it’s a new realtor in there and then update their contact list in their HubSpot to say, OK, that contact has been updated. This is new, right? And so what Lutra is able to do is to say, I understand how to get a list of people from HubSpot. I understand how to go to the internet and browse and go to page one, page two to find the right information. I know how to get the data out. And number three, I know how to push it back into a custom property in your HubSpot. And so it’s understanding all those actions and all those things you can do, and then orchestrating across them to achieve a task for you. And this task could be, interestingly in this particular task, it was a fairly big one. So just like running that process 7,000 times for all those contacts. And it turns out that this process was a process that they ran manually before our solution. And they had people come in for a week and go like, we’re going to do all this data updates today. But now the bulk of it is all automated.

Mike: So it’s really interesting because it sounds like what Lutra does is a little bit different to some of the AI tools that people in marketing might be familiar with, is you’ve obviously got access to the public data, the data that the module’s been trained on and information on the web. But you’ve also got access to private data through these APIs. So you can actually access the user’s own data and then merge that with public data. Is that really one of the unique things that Lutra does?

Jiquan: Absolutely, absolutely. So I think it’s this blend between your private information and also public information. But even within your private information, there’s so much we can do. So internally, we have Lutra connected into our own data warehouses and systems. We tell Lutra, like, can you find out in the last two, three days, who are the people that recently subscribed to Lutra? Who’s paying for this? Can you find out, you know, in an anonymous fashion? Like, what are you doing? You know, like, tell us a bit more about activities there. And then, you know, can you send reach outs to them? That’s very customized on like, thank you for subscribing. Notice this, we’d love to hear more about what you’re doing and go from there, right? Now, there’s some processes there that, you know, you could do that, a lot of the things manually. But then I think what the platform, what we are building allows you to do is to quickly get from that point of unscalable process, get a machine to do it, and suddenly you’re able to scale it, right? And so that’s the part in there. And so getting that internal data access really supercharges what the systems can do for you. And I think that’s a great point in there.

Mike: Yeah, and to me, one of the interesting things is you can do data enrichment, but not in terms of just add someone’s email or contact details. But you talked about going out and looking at information. So could you, for example, for someone we’re targeting, tell us if they appear in a news story and add that into the data in, say, HubSpot or whatever CRM you use?

Jiquan: Absolutely. So what Lutra is able to do, I think, what’s really cool about this technology is that being a general purpose assistant that way, As long as Lutra understands how to work with the systems you are working with, the possibilities is somewhat up to our imagination on what we can do. And so what happens here is that we have a use case in which one of our customers have tons of accounts that they are looking at, and they want to figure out the best time to reach out to those accounts, right? So right now, I think, you know, outbound is really hard. for outbound sales, because everyone is doing it. It’s a bit overloaded. We’re all swamped by outbound emails. I get a lot of them myself. But then the ones that are on point, targeted and timely are the ones that work. And so in this particular case, what they wanted to do was to figure out events that are happening to a company. And some of those events might be really relevant for them to reach out. This one happened to be in the biospace. So they were very interested in clinical trial status updates. So did the status of a clinical trial change for a pharma company from phase one to phase two or phase two to phase three? And there’s some phases in there in which their businesses and services makes a lot of sense. what they are saying is that so they’ve all this you know 100 accounts interested in more than 100 actually 100 per rep and there’s no way the rep can be keeping up with all of this every day something’s on the slip and so they’re trying to say hey can Lutra can you every on a weekly basis or a daily basis can you go through all the articles about these companies now use AI to understand if there’s a report on that that’s of interest to us, a phase change in their clinical trials, or an announcement about an audit matter or something like this. If so, highlight it to the rep, and then they can now reach out in a very timely, targeted fashion. I think that’s really powerful because that allows you to bring in the external data with your internal priorities and supercharge your team that way.

Mike: And I think that’s really interesting because from a marketing point of view, particularly, I can see what that does is if you’re running an account based marketing campaign, you’ve got a list of target accounts, you can not only make sure you’re targeting the right accounts, but you also can target them at the right time, which is something, you know, most marketers really don’t have any opportunity to do. But tying it into news, I think is really interesting. So I think there’s a sales use, but also a marketing use potentially there. Yes, absolutely. I’m interested, you know, you talk about pulling in this news about clinical trials. I mean, presumably marketers, as well as generating content for emails, they could use it for more general content generation as well. So as an example, we’ve got another podcast that talks about marketing automation. I mean, presumably Lutro would be able to tell us what’s happened in the last two weeks in marketing automation to help drive the agenda for that podcast.

Jiquan: Totally. So maybe taking a step back here, when we think about how we explain Lutra to customers, one thing that I like to do is always to ask them, if you think about your time in the last one, two weeks, what are manual processes? What are things that you’ve been doing that you feel like a robot, clicking around and getting data and figuring out how to, and figuring out in that process, which part of it is essentially grunt work? Every part of it is the creative part that you come in to shape. really help to form the artifacts that you’re working on. And I think this is where, to your question, to your point about Lutra looking into not just figuring out data or content for marketing posts and materials. So maybe an example here is one of the podcast users on Lutra actually uses Lutra to do their research on content that they want to talk about every week on their podcast. And what you can do there is that there’s so much going on on the internet, so much going on in the news, so much going on in announcements, on tools these days. So what Nutra could do for you is to say, hey, go look up all the announcements on, say, B2B marketing automation. Go look up all the news about it. What are people saying about it? and then collect that information, summarize it in a format that you would like that would be useful for your marketing purposes, and maybe even prepare a draft blog post in the style of the previous blog post that you’ve written, or prepare a transcript for a podcast that you might be going to record next week. And so we’ve seen some people do that, and this is really helpful in that grant work, that manual process of research, trying to figure out what to talk about, can then be automated, a first draft can be produced, and then we come in and we bring our creativity to the process and figuring out what is the right way to take that data and frame it for our audience. That’s the step that I don’t think AI can do that well because we know our audience, we know the people we’re reaching to, we know our accounts, but AI is really good at the go and get lots of data and process it, right? And so this is where I think the two come together really nicely in that if we can give more of that you know, manuals, you know, groundwork, the thing that, you know, you have to process lots of data, read lots of websites to the AI, that would help us then spend a lot more time on figuring out what do our audience, what does the audience want to hear, right? And how can we take that data and bring it to them?

Mike: I love the way you still see the opportunity for creativity, the human creativity. And I think that’s a really positive view. I mean, I’m going to have to ask you, because I’m sure a couple of marketers listening to this winced when we mentioned technical terms like API. I mean, how hard is it to use? Is this going to be really tough or is it something where you can literally talk to it as though it’s a chatbot?

Jiquan: Yeah, so our goal is to make it as easy to use as talking to it. Our goal is as easy to use as like, you know, you can bring questions to it. You can ask, what can you do? It’ll respond. You bring your needs to it. Can you read the web about this? It’s like, I can, let me show you how. And then you can say, now can you do x instead and y instead? So very iterative, a way that works with you to get things done. So that’s how it goes to get to that level of ease of use that non-technical users can succeed in this technology. And I think this is a very, very important point, because we have seen a lot of other general purpose automation tools. But they’re really hard to use, usually. You drag and drop little boxes. You connect up the arrows. You type in lots of configuration. Doesn’t work. You have no idea why. And that’s pre-AI automation in many ways. And our post-AI agentic automation is the one where the machine should debug itself. If the automation or the process fails, you talk to it and say, that didn’t go right. Can you try to fix it and try again? And more often than not, what we see Lutra to do is that you try a different approach. It will look at the errors and try to fix it. And that’s really powerful, because then that enables the group of people that can work with this technology to be way bigger than before. And I think that’s really exciting for us, because I think going back in time, maybe to my motivations on this thing, detouring a bit on that, one thing that really motivates me individually a lot is the idea that we can give people new superpowers. So the reason why I actually worked on education, MOOCs and Coursera, MOOCs are massive open online courses. Back in the day, I felt like education was this new superpower that I could give people. If you learn a new skill, you learn a new topic, now you can go out and change a job and do something new. And now I think AI has this moment where we can give the ability to accomplish all this really complex, streamlined technical work to more people. And it’s a new superpower that they otherwise couldn’t have done before. And that really excites me a lot from a personal point of view.

Mike: I love it. I mean, you’re just so positive about the opportunities. And I mean, as I understand it as well, Lutra, once you’ve set up a workflow to do something, you could just tell it to do it on a regular basis. So you don’t have to keep going back in, it will automatically run. Presumably, that has some great applications from cleaning data all the way through to generating summaries of news.

Jiquan: Everything, yeah. So I actually don’t read the news anymore because Lutra summarizes it for me and sends it to my inbox every morning. So there’s been a change in my behavior there. But apart from just news summarization, which is a very basic use case, you can start to get very creative with those things. So for example, what some of my teammates have done is they set up Lutra workflows, automations, to look into forums where people are struggling to automate something. And so we have some Lutra bots that are like, hey, let me go through Reddit or different community forums there and look at what are people struggling with and what are they saying about this automation that’s really hard for them. And Lutra looks at them and goes like, hey, do I actually have the integrations to achieve this? And then it flags it to us internally on Slack to say, there’s this post here. We think that we can solve their problem. Maybe we should reach out. And that just runs. And then we just sit back and see those messages come in, informing us about some degree of the market, like what people are seeing out there. And that’s really powerful because this is really custom. That whole process is really custom. Now, if you were to hire a team or engineer or figure out some way to set that up, that’s pretty hard, that whole process. And now productionizing it is even harder. And I think what we do is that we handle two parts of it. Can we create automations about those like this that run automatically? And number two, can we productionize it in a way that runs on a frequent basis for you automatically? And I think that’s to your point, that’s the second part of it is really interesting. And going into maybe use cases a little beyond marketing, one thing that we have seen as well is people doing this for their own emails. their own management of data that’s coming into them, right? So for example, we get lots of emails, we’ve noticed that some people use Airtable as a CRM, and they like to sync those data pieces up. And what we have seen some people do literally is to get Lutra to read all the emails in the last 24 hours, categorize them, sort them out, and then put it into Airtable, where the CRM is being managed. And that’s completely automated in that way. And so that’s also interesting things to think about in there where Not only can we use this to produce content, but if there’s a lot of inbound or a lot of things coming in, can we also use it as a way to manage that as well?

Mike: I think it’s really exciting. We’ve talked about an awful lot. I’m interested in your approach to marketing Lutra. I mean, I know it’s early days, but it seems to me this could be somewhat analogous to Dropbox, where Dropbox basically was used by a lot of individuals to make their lives better, and then kind of got taken up by enterprises when the enterprises realized there were a lot of users. Is that something you see, or do you have another marketing strategy for Lutra?

Jiquan: I think that’s certainly a valid approach that we’re considering too. I think what’s really important for a strategy like when you mentioned individuals using it and then Gantian Enterprise, the product-led approach, is that it needs to be really easy to get onboarded to the platform. The time to value of using this product needs to be instant. I see it right away. Less than five minutes, maybe two minutes, I get something, result from it. And I think that’s possible. I think it’s very possible that you come in, you try something out, and you start to see real concrete value to yourself in the minutes right now, or maybe less than a minute, too, if possible. And I think what we want to do is then say, OK, now, if we had that, Imagine if Lutra was now connected into your own internal enterprise systems. Not just the internet, not just my Google, not just my workspaces, but your back office solutions into your own data warehouses. Now, if it was so easy for anyone on your team to say, hey, go to the data warehouse, figure out what’s going on with this account, pull it out. OK, what else is happening on internet with that account too? OK, let’s figure this out. OK, how should we reach out to them? And getting data from different systems. And I think that’s really powerful because the number of SaaS software that we’re using in enterprises is only going to go up. And it’s been going up at this crazy clip where now there’s data silos in all these places. And sometimes it’s really hard to get data together in the same place. Your calls are in Gong. but they’re not really in HubSpot, and you really want them to be synchronized. So our view of this is actually getting to the point of, can we bring Lutra into the enterprise, connected into your own data systems? And I think that’s the next level of unlock that happens. And the way I think we’ll, maybe to your point, how do we market Lutra? I think one thing about things that are interesting in the AI space today, that’s what I’m noticing, is that people want to play with the software. The way to sell AI software right now, I think, is that people want to experiment, see it work, validate that they can do it before they go and say, I want to buy this now, right? Because there’s so many possible solutions out there, and there’s so much hype and noise in there. And so the way we’re thinking about it is, exactly that, which is get people in, get them successful in a personal use case. I think ChatGPT was that too. And then after that, there’s a next level up story in that, okay, how can we bring this into the enterprise and make it work? But having that success at an individual level starts to open up your imagination quickly. I think opening up that imagination is going to be a big part in how I think we will start to see AI reinvent how businesses operate.

Mike: That sounds so exciting. I mean, you talk about opening up imagination. One of the things I think that anyone who’s in a senior role of VP of Marketing or CMO, they’re going to be wondering how their role is going to change as all this automation comes in. What do you see as the impact? Do you see teams being more automated and having fewer people, or do you see there’s an opportunity to do more with the people you have because you’re freeing up time?

Jiquan: Yeah, no, totally. I think I think the code I like to get to is AI will not replace you, but a person who’s using AI really well is going to do a lot more than you, right? So I think what happens here is really thinking about training, which is how can I educate my staff to get really good at using this technology? A lot of it is very nascent, a lot of it’s very early, but the more you can get familiar with how you use it quickly, the faster you accelerate your process of adoption. And the teams that adopt it are the teams that are going to be ahead. I’m going to take an analogy to what’s on the technical end, because I’m very familiar with the site, and then we can map it to the marketing end. In the engineering space, you might have heard of co-pilots or engineering assistants. Today, my team actually uses AI a lot in their engineering time. most of our software turns out to be written with AI assistance right now. In fact, most of the code is, more than half the code is actually AI generated. It’s really good at that. Now, if I had an engineer on my team that was not doing that, they’re going to be falling behind. They’re going to be like, you know, 3x slower than anyone else on the team. And so the same thing’s going to happen in different industries as we figure out how this technology gets more embedded into our workday, our knowledge. And the same thing is going to happen there, which is the people on your team who figure it out are going to be so much more effective than those that don’t. And my encouragement to the, you know, if you are a marketing leader or any leader really in this space is help the team understand, investing into understanding this technology and using it. It’s going to be potentially very game changing and really figuring that out and accelerating that. Now, I think the effect of it, of what we are doing, Lutra, is I hope that if your day was spent in, like, 50% grant work and 50% productive work, or maybe 30% meetings and 20% productive work, really, right? We can expand that and say that 50% grant work starts to go away, you know, the machine is running, doing something for you, you get coffee, you come back, you go like, great job, keep going. And then that 20% of productive work just massively increases, because suddenly you can do a lot more.

Mike: Yeah, I mean, that sounds so positive. One of the things we always like to ask people, and I think I know the answer to this is, you know, what would be your advice if you are talking to a young person thinking of a career in marketing? I guess it’s going to be to learn how to take advantage of the technology.

Jiquan: Totally. I think to a young person, learning marketing and its resources. I think figure out figure out where the technology comes in and is really good at, and figure out where two parts of it, right? As a user of technology, that’s certainly very important. How do I use it? But also, what am I bringing into the table that is beyond using technology? What insights am I getting, right? And so increasingly, I think, being really in touch with your customer base, really having good intuitions on their audience and what they’re looking for, what words resound with them, right? those are things that the technology doesn’t have access to. You know, going out there, having those conversations and developing that intuition, you don’t have that, right? That’s something that the technology doesn’t have the context that you have, that you have gained, you know, working in a place or seeing what’s out there. And I think really understanding those pieces, not just like accelerating your work, but bringing that differentiating factor that’s beyond technology, right? I think that’s a key part of it. So for example, even with us, we’ve been working with this technology day in and day out, trying to get things to be more efficient, really understanding what users are trying to do is a critical part of it. The AI is never going to tell us to chase down a particular route. It can collate lots of data for us, but then really understanding, hey, our users is really the part of it. And I think for marketing, positioning, figuring out how to explain this, that’s the part I think that’s really critical in there. And then if you find yourself spending lots of time doing manual groundwork, that’s where you’re like, you should go figure out technologies that can help you with that.

Mike: Yes. I really like that. I think that’s great advice, Naeem. And you’re really positive as well that even young people can take advantage of this. And perhaps, you know, it’s almost a bigger challenge for the more senior people to get that adoption. So I think it’s great. One thing I’ve got to ask you, you mentioned a little earlier in the podcast that, you know, the most important thing is for people to be able to try the tools so they can use their imagination to see what they can do. So, I mean, if somebody’s listened to this and they’d really like to automate some grunt work tasks, how can they do that with Lutra?

Jiquan: So, I think one is like go to lutra.ai. That’s where we are. You can find us, you can sign up. We’re in a, I’ll call it open beta right now. You can play with it and see what it does for you. Reach out to me. You can find me on LinkedIn and Twitter, Axe, and love to chat about your use cases and all. And I think for us, the one thing that we are looking at is understanding the integrations, what people need, how can they get their things done, what’s the rough spots in there. Reach out, I’d love to have a conversation with you to really dig in into some of these processes and work streams that we can help with.

Mike: Well, thank you so much, Naim, for your time. I mean, it’s been really interesting and I’m looking forward to playing with the tool and trying to get rid of all those nasty manual tasks that we don’t like and spending more time on the fun. So thank you so much. I appreciate you being a guest on the podcast.

Jiquan: Thank you, Mike. This is awesome. I’m super glad to be here and I hope what we’ve built is going to be really useful to all of you guys. Thank you.

Mike: Thanks so much for listening to Marketing B2B Tech. We hope you enjoyed the episode. And if you did, please make sure you subscribe on iTunes or on your favorite podcast application. If you’d like to know more, please visit our website at napierb2b.com or contact me directly on LinkedIn.