Tim Tutt Podcast Transcript
Tim Tutt joins host Brian Thomas on The Digital Executive Podcast.
Welcome to Coruzant Technologies, home of the Digital Executive Podcast.
[00:00:12] Brian Thomas: Welcome to the Digital Executive. Today’s guest is Tim Tutt. Tim Tutt is the co-founder and CEO of Night Shift Development, which focuses on helping organizations make sense of their data. Using his background in natural language processing, machine learning, and data analytics, he created and productized a solution aimed at allowing non-technical users to have conversational experience with their data.
Tim Tutt is a proven technical leader with over a decade of software engineering experience focused specifically on developing and deploying large scale search and discovery and data analytics solutions in both public and private sectors. He has a strong passion for operationalizing deep technical capabilities for the benefit of non-technical business users.
Well, good afternoon, Tim. Welcome to the show.
[00:00:57] Tim Tutt: Hey, thank you much, Brian. I appreciate you having me on.
[00:00:59] Brian Thomas: You bet. This is so fun. I love it. And I love really talking to some techies. I’m a techie by trade. I was a developer as well. So, we like to jump in and talk a little bit about tech without boring some of our audience because we have a broad audience, but Tim, this is so awesome.
Thanks for jumping on and we’re going to jump right into these questions. You’ve got quite the career in tech. You’re a software developer, senior executive, and entrepreneur. And now the co-founder and CEO of Night Shift Development. Could you share with our audience the secret to your career growth and what inspires you?
[00:01:32] Tim Tutt: Sure. No, I’m happy to, I think the secret to my career growth really boils down to just always having that knack for wanting to do more and find other interesting ways to leverage technology. I spent a long time as a software developer doing large scale search and discovery systems got to a point where I wanted to build software to help solve some of the problems that I was seeing in the field.
So every time I’d run into a new problem, I’d. Look to build new tech to solve that. Eventually that put me in a space where I was able to start my own company. That’s what Night Shift Development became. We built a product that’s around solving this issue of how people get value from their data in a very simplistic way.
Yeah, I think that the biggest thing that inspires me around all of this is, technology in my mind is meant to be an enabler for anyone. We shouldn’t have the blocks that we have that exist today. For users that aren’t as technical. So, how do we leverage technology in a more effective way that enables those people, the people that understand the business, but don’t necessarily understand the tech to get the same value from the technology that everyone else does.
[00:02:46] Brian Thomas: I love, really do love that we talk about customer experience here all the time. And, back in the old days, it was like, oh, we got to wait on IT. There’s a bottleneck there, whether it’s a report or they need something modified, whatever that is. And I, like you, I believe in, hey, let’s give power to the users, people that really run the business, that way they can have their cake, right? And eat it too, while we can continue to develop and make a better product and better customer experience for them. So, I appreciate you sharing that. And I’d certainly share in the same sentiment. Tim, your product Clear Query has been touted as the platform that is truly analytics for humans, empowering everyone to be able to extract, obtain and tell their data story.
Can you tell us about the genesis behind your platform?
[00:03:30] Tim Tutt: Absolutely, it really boils down back to exactly what I was saying. For a very long while I played this role of the middleman. It was people would come to me. I had about a couple 100 analysts that I was supporting.
There was a team of about 13 of us developers that had access to a massive supercomputer. They’d come, they’d ask questions. We’d go back and get answers from the big data store, give those answers back. But then there was always a follow up. There’s always this, hey, I need to know more.
I need to drill more. And we were really the bottleneck. Instead of them being able to get those answers fast, they had to wait on us and the pipeline of things that we had. At that time, my co-founder and I got into a point where we said, wouldn’t it be great if we could find a easier way for people to get these answers without us having to be stuck in the middle without us being the bottleneck for these individuals.
The reason the name of the company is Night Shift Development is because when we started the company, we both had still had bills to pay and we were, getting running. We bootstrapped the entire company, so we had to work nights and weekends on product until we got to a point where we could actually launch that.
But Clear Query really was born out of that exact issue. How do we help enable people to get the answers that they need from their data without needing to have a technical middleman?
[00:04:52] Brian Thomas: Love that. And that is certainly a success story. Truly, you’re trying to solve a problem for somebody and making the world a better place, as I like to say here on the platform.
Tim, with other platforms like Tableau, Power BI, we’ve all used them, right? Which are now leveraging AI predictive modeling and access to deep learning platforms. What is your plan to stay ahead of your competition?
[00:05:14] Tim Tutt: Absolutely. One of the things that we’ve done historically and from the beginning of our platform, we’ve built this to be secure by default.
So everything that we do is built inside of the product. So, things like conversational analytics that are competitors like Tableau and others or using ChatGPT-4 requires data to be sent outside of the network. We actually do that internally with our own models that are built on the fly, which means a deployment a lot simpler.
It’s a smaller deployment. You don’t have to send your data out to 3rd parties. And then B), you actually wind up with a more deterministic model. One of the big challenges with ChatGPT and others is you still have this hallucination effect and you have things where the results are not always accurate.
We actually provide a view into what’s being generated from a code basis for users that are more technical so that they can validate the queries that are being created. But that’s just one piece of the story. That’s, that’s how we differentiate on our competitors jumping into the space that we’ve been in for a while.
As we’re looking towards the future, we’re also looking at doing things like predictive analytics and prescriptive analytics. So really, how do we help you predict what’s going to happen in the future? And how do we help you make the best decisions for what you need to do in your business? Really driving towards making this more of a decision intelligence platform, rather than just an analysis platform.
And I think as we do that, that’ll allow us to stay ahead of the curve because we’ve already been here and we’ve already beat some of the issues that our competitors are going to run into as they start to leverage these other technologies.
[00:06:52] Brian Thomas: Thank you for sharing that.
That’s awesome. And again I really believe that entrepreneurs are the way to , making life better and easier for our customers when you’ve got your hands on the reins, as far as an entrepreneur business owner, you have more control to really get in there and listen to the customer.
These big platforms sometimes you just not getting what you want as far as a partner, right? So I appreciate you sharing that . Tim. Last question of the day. You’re obviously leveraging some of this new and emerging tech in your tech stack. Is there anything you might be able to share or tease with our audience today?
[00:07:25] Tim Tutt: Yeah, there’s some new things that we are building out. One of the things that we tend to talk about is we don’t leverage large language models. We do leverage language models. And the distinction there is kind of important and it’s really designed around how we help keep these deployments as simple as possible.
How we help make sure that the total cost of ownership for our customers doesn’t skyrocket super high. So, we’re looking at using a variety of language models for a few key things. One, how do we handle unstructured data? Things like unstructured text, audio files, video files. What can we leverage language models and other machine learning models for to extract the right types of value out of those things so that you can perform the analysis and analytics that you would with any given structured data set.
We’re also looking at a variety of language models for doing some automatic translation for users. So, if your data happens to be in another language, you can ask that question in English, but we’re going to translate that appropriately or vice versa, helping that provide this internationalization capability that, doesn’t require a massive team set.
So still being able to leverage some of these cool technologies without necessarily breaking the bank for our customers at the end of the day. Those are some of the things that we’re working on as we look forward to next year. But one last one that I’ll tease and this is very key area for us is the intelligent data cleaning process is one of the things that we’re really looking at as a core feature of the product.
The way we look at Clear Query is we have three key pillars. first being. Data ingestion, 2nd being analysis and the 3rd being data storytelling. We do a pretty good job at those last two, but that first one, we really want to help people get their data cleaned as it’s coming in. So, we’re starting to build some new tech to help identify when data is dirty and what needs to be done to it to help make your analysis story even more impactful without needing to have that long tail of data engineering work ahead of time.
[00:09:25] Brian Thomas: That’s awesome. Thank you. And you are putting in some of those features that should be no brainers, right? Like you said, the language translation obviously is one but the fact that you’re really highlighting throughout this whole conversation today you are truly a partner with your clients.
And that is awesome. We don’t see that a lot anymore. The customer experience, I’ve written a lot of articles about it, and there’s a lot to be learned from some bad customer experiences. So, appreciate you highlighting that. That’s awesome. And Tim, it was a pleasure having you today, and I look forward to speaking with you real soon.
[00:09:59] Tim Tutt: Great. I really appreciate it, Brian. Thanks for having me
[00:10:02] Brian Thomas: Bye for now.
Tim Tutt Podcast Transcript. Listen to the audio on the guest’s podcast page.
