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FINTECH FRIDAY$ (EP.17-Nov 9): How Artificial Intelligence is Optimizing Sales and the Future of Business AI with Asad Naeem, Co-founder and President, Fortuna.ai

NCFA Canada | Nov 9, 2018

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Ep17-Nov 9:   How Artificial Intelligence is Optimizing Sales and the Future of Business AI

About this episode: On this episode NCFA Fintech Friday's our host Manseeb Khan sits down with the co-founder and president of Fortuna Asad Naeem. They chat about how AI can supplement salespeople, the excitement behind computer vision and the future of business AI. Enjoy!(see Transcript)

Host: Manseeb Khan, NCFA, Fintech Fridays show host

Guest:  ASAD NAEEM, Co-founder and President, Fortuna.ai (view Linkedin)

Bio: Asad is the Co-Founder of Fortuna.ai, a top of the funnel sales automation company. Prior to co-founding Fortuna, Asad spent time with a big 3 bank in Canada, first on the sales team covering the largest financial territory in Canada, and after, with the Data Analysis and Strategic Initiatives Team, providing insight and consulting on sales campaigns. A life long entrepreneur, Asad has consistently been feeding his entrepreneurial spirit ever since starting his first business in Grade 9 and starting and running a couple of start-ups throughout his university days. Having spent over 10 years in and around sales, he is intimately familiar with the problems being faced by sales professionals today and along with his Co-Founder Omer is positioning Fortuna to solve these problems utilizing Machine Learning and NLP.

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Transcription of Interview

Intro: Welcome fintech Friday's a weekly podcast brought to you by the National Crowdfunding and Fintech Association of Canada and partners.Covering all things fintech block chain be AI and alternative finance.

In this episode we cover how AI can supplement salespeople,  the excitement behind computer vision and the future of business AI.

Manseeb Khan: Hey everybody how is you doing today? Manseeb Khan here and you are tuning in to Fintech Friday. Today I have an absolutely incredible guest. Assad. OK from a Fortuna.ai Thanks so much for being here today. I mean this means the absolute world to me.

Asad Naeem: Yeah thank you so much for having me. It's an honor.

Manseeb Khan: So, could you just for a second. Give us a little bit more of what Fortuna is and a little bit more about you and your background.

Asad Naeem: Yeah absolutely. So, I'll start with me with my background so basically, I've done sales all my life I started out in the in the trenches at the future shop and some of the guys have done sales and you know they've gone through that process. They know exactly how that is. So, after that I went to school obviously once you know University  of Toronto for bio and then attended Carlton university for political science. There started my career in the bank. So, I've been all over the place. But with the bank basically stuck around started you know at the lowest level kind of rose through the ranks eventually ended up at CIBC Asset Management. Where I was doing third party broker dealer sales. I did that for about a couple of years and kind of had the genesis of the idea for Fortuna while I was there. Move over to Fortuna. Basically, what Fortuna does is it's top of the funnel sales process automation which is your client discovery and client qualification. So, the entire ethos behind our product and our company is that you know salespeople today are spending but 80 percent of their time doing mundane admin tasks we're using AI to automate that portion, so they can spend more time and you know more focus on higher value consultative of selling processes.

Manseeb Khan: Yeah no I mean I can definitely relate on the sales angle because my first job as a door salesman. So, its sales are brutal 100 percent. So, could you talk a little bit more on the AI the process of it. Do you map it a little bit towards the more to the salesperson like does the AI kind of work like okay  I'm Manseeb and this in my sales style? And I guess my chat bots or whatever we may have you might be tailored towards that. Or is it just more of a generic AI.

Asad Naeem: The way it works is we're employing AI in two spots right now and the first one is a little bit sandbox experimental the second one is actually we're using right now the client discovery portion is basically we're using to figure out exactly who is it that you should be going after. Now this happens by taking a look at your transactional. Let's say you’re a client of ours. We look at take a look at your transactional record, take a look at your sales campaign see where you are having the most amount of success. And then just building models based off of that to see exactly you should be going. Who you should be going after,  the second place where it's really my interest and where I'm paying more attention to is the NLP component of it. The natural language processing where we started the conversation with what your prospects are leads that are coming in. And then we basically lead them down the qualification funnel. we'll and find out you know the three things that you need for any sale to occur is hey is there any interest here. You know do they have the authority to make this decision and then the third one is do they have the budget to make that happen of course. So, we use a conversation and general AI chat bot to figure out those three things based on your own sales playbook for your company. And once we have that component done, we kind of handed off to a real-life human sales agent which will be your sales rep. So, we don't sit in a space where we go you know we're going to use AI to get rid of all sales people, but we actually say that no you know there is a space for AI, there is a space for real sales people. There's a because sales are a very high touch in a lot of industries very high touch. Oh absolutely. You know process, so we want to argument  that process and we want to help the sales people be more productive and more efficient.

Manseeb Khan: Right. So, I mean you guys are pretty much helping a lot of slack time when it comes to just like building a list prospecting, calling and everything you guys are just literally helping streamline that a little bit more.

Asad Naeem: Absolutely, absolutely. All the mundane admin tasks basically the salespeople and they just absolutely hate. Exactly. And that's not their forte. No not at all. Right now, I'm here to sell, I'm not here to put everything in my CRM and make double check and make sure what stage of the sales cycle their on. oh man.

Asad Naeem: At the end of the day if you look at it some sales people are especially high value industries like finance and you know even car sales. Yeah you know there are six figure employees. Absolutely. And then if you're expecting as a company that you're a six-figure employee to be doing admin tasks scraping LinkedIn and all that other stuff their value is really in being able to do that consultation process not do data mining right. But then what happens is companies started to realize this. So now they have you know SDR, as they have L.D. which is lead development reps and now you're paying these people 30 40 thousand dollars a year just to sit there and scraping lists, you know emailing back and forth to figure out if there's interest. Yeah this can be automated. And that's where we come from. And that's our perspective that you know hey let's get your people to do more high valued asked leave the mundane admin tasks to machines essential.

Manseeb Khan: So, I guess what's how do you see the trajectory from here?

Asad Naeem: So right now, you know where we're focused on finance, we're focused on some of the other high value nurses as well. We recently started expanding out. we're doing you know car dealership, we're doing you know automotive companies were doing, you know merchant accounts like alternative to finance things like that but eventually all of us you know like were our aim is to see how this solution fits in organically into other industries and slowly get there. But right now, we're very niche we're very focused because as you can imagine in a building any natural language understanding models you know industries being industry specific helps us because I come from finance, Omar my business partner comes from finance as well. So, we understand the language that's being spoken. Of course, you can train our models based on that as well.

Manseeb Khan: So, I guess how easily you integrate with the current CRM system like the HubSpot’s and the Salesforce is out there because you are seeing, out there that they are slowly trying to build their own model similar to you. How do you how you either integrating with them and how do you see yourself competing with them?

Asad Naeem: So right now, I wouldn't say we are competitors, so CRM I say you know we a more of an asset. Exactly it is more of an asset we hook in. If you look at any CRM system even if you look at HubSpot like HubSpot started out it was very pure it was very minimalist right I mean and you look at it today it's got all these different angles it's got a chat bot it's got a meeting scheduling thing just becoming very big and they're doing a lot of things. So, I haven't seen a direct focus for any of the CRM you know manufacturers right now that are going strictly down the path of just automating conversations using you know natural language understanding and processing. So, we're basically a perfect shoe in and we are  compliment to that strategy. We're not looking to replace a CRM we're looking to enrich the data that's already in there and basically anything else that you put in you know the qualification portion of it we want to handle it.

Manseeb Khan: No, I love that that's very comforting for a lot of the business owners out there knowing that. So, I mean given being AI it's an it's a brand new, it's a very disruptive industry and it's a brand new disruptive potential market. Just saying that you guys are just going to supplement everything else such as a breath of fresh air.

Asad Naeem: Oh absolutely. Absolutely we're not we're not of the mindset you know we're going to replace humans or we're going to you know destroy industries or whatever the case is you know we look at AI as something that can be used for good and you know it can be used to make people's lives easier as technology is supposed to do. Technically you know, and this is where our mindset comes from that we want to use AI and machine learning to help people be more efficient more productive and also just to help companies be more efficient more productive as well.

Manseeb Khan: Right. Right. I mean I can even see that the case of like just having thousands of data sets of sales like you guys could even like potentially pivotal actual sales learning platform. Absolutely right. Just like Hey these are the car dealerships these are everything. like these are the case studies, there are of all the potential objections that you are going to have, this is how you handle them all that kind of stuff, so the potential is there. It's definitely incredible.

Asad Naeem: Yeah absolutely. Building sales playbooks. That's a separate industry. Oh yeah no I mean there's organizations out there you can hire right now that look at your product, who you're selling to your target market. Build sales playbooks for you right. Yeah. So yeah hopefully. I mean that's our primary focus for sure is focused on what we're doing. But you never know what the future holds.

Manseeb Khan: No absolutely agree with you. I'm going to pass this off to you, so I guess you're in the space right. What about AI truly excites you?

Asad Naeem: Oh, the possibilities, the possibilities. Right. I mean we look at we look at natural language processing and  that's the least that I'm really interested in right. It's the we have the understanding component down packed like we can understand intent. we can extract you know what is it that somebody sort of say what is the intention behind it and we can't even go as far down as you know looking at what are the emotional cues, and somebody is writing. okay. You have a great company here in the DMZ shoot out to Trualt. You know they do they do emotional analysis on text. So, you know things like that but where we haven't been able to make a big breakthrough is the generation component. So right now, and you know like if somebody is going you know we use to generate e-mails, or we use to do generate text. Yes and no at the same time it's very vague and it's also a lot of it is template based. Yeah right. It's decision trees they're going OK if somebody says this. This is the intent, you know be extracted out you know use this template to reply back whereas organic language generation. It's still very nascent it's still in the labs, is very academic in its pursuit. So, we're not there yet. I want to see the possibilities of when that occurs where machines are able to communicate back you know organically without using any templates or you know any pre-determined schema in terms of how and what to say. That would be very interesting. I mean aside from that I'm a big fan of computer vision. I think there's tons of possibilities out there. There's a lot of great stuff happening right now. For example, you know crop analysis that's going on there's a new just we're just reading up on it recently as well. There's a company there's a new start up that basically  that that's building computer vision AI to help when people get lost in the woods to help you know like firefighters and forest rangers and things like that to be able to locate people so there's a lot of interesting stuff happening. I mean this is just the tip of the iceberg there's this stuff happening in mining there's stuff happening, and you know like pollution prevention you know doing surveying all sorts of different things. So, computer vision is also very, very interesting.

Manseeb Khan: So, I guess how you see. I mean or just AI sales in general how fundamental do you think it is when it comes to AI business?

Asad Naeem: The thing is deploying AI is becoming kind of a priority for a lot of big enterprises and big businesses. And you know I think sales is an untapped market when it comes to machine learning and being able to learn from historical transactions, online, retail sales you know sales campaigns, marketing campaigns. So slowly we're going to see a lot of activity in this space. Marketing is already kind of seeing it. You know there's a lot of great companies out there that are basically deploying AI to fine tune and help you really personalize the marketing that you're doing. But slowly you're going to see it happening in sales, direct sales as well and whether it's inbound , outbound or whatever it is you need to find people for your business to sell too. Of course. You need to qualify them right. Right now, that is a very human, very labor-intensive job. So eventually I see it being a space where machines excel. where they help you find the people, qualify them and then you know once the actual sales process kicks off a human agent takes on and is able to basically close that process. So, the end result here is that you're going to compress your sales cycles. You're going to make sales more efficient and you know you're going to make your entire organization more efficient because of that.

Manseeb Khan: Yeah and you're going to have a lot of more harder numbers to work off of.  because that's a very tricky thing about sales because since it is so labor intensive and since it's the human error when it comes to sales it's so astronomically high. And it's also laziness, too right? I mean yeah no absolutely, no I absolutely agree with you there just like again like we talked about just manually inputting everything into the CRM it's like OK I emailed them back, it's third touch booking a call-in next Thursday at 4 and let's  see how it goes. And then we just wait.

Asad Naeem: Absolutely dude there's a lot of research out there that says you've got to reach out to your potential prospect like five to seven times, like five to seven touch points and I'm a salesperson. Yeah so have you. I mean how many times can you honestly say that you did seven touch points. It's a lot of work. It's a huge emotional toll too because you're if your hearing no's all day. oh, my goodness. Yeah. The twenty or the twenty fifth or the fiftieth. No, it's like you cringe a little bit. Yes.

Manseeb Khan: So, I mean especially during the day. Right. Depends like you mentioned car dealerships. Right. Like cold calling 150 people if not more. And it just here. No, no ,no, no, no. It's definitely gets to like cleaning that out. cleaning process out definitely it's going to make it a lot streamline a lot more  easier. I mean you guys are not even like what a year and a half year old. Yeah. Yeah. So, I mean what is the next five years a Fortuna to look like for you and the company?

Asad Naeem: Yeah absolutely. So, like you said you know we're still a very young company so we're in the throes of you know full blown product development now. we had our version one you which the market was  really receptive to. You know we've had the fortune  of being you know revenue positive since day one, since we launched you know where we're making money as well. So  it's a very exciting time to be because we're really taking the feedback that we're getting from our initial batch of clients and fine tuning the product making sure we're you know adding features that there's an actual market demand for and just basically making sure that it's a seamless experience for the sales teams that were getting on boarded and even the individual sales people that we have right now you know they just having a good experience. So right now, we're fully focused on building a product that our customers love and that our customers and our clients are recommending to their friends and they're the people that they have in their network. So that is the short-term goal right now. The next five years honestly it can go a lot of different ways but what  we're aiming at is we're growing our team really rapidly you know 11 people right now the company. But a we're probably going to double by mid-2019. So, you know we're full blown aiming at making sure that we're doing all the right things for our customers making sure that you know our product is on point. And then also just making sure that we're helping as many sales professionals and sales teams as possible you know reduce the workload become more efficient become more productive and hopefully in the next five years you know you can you can hear us as a household name helping sales out everywhere and you know cutting down on the manual boring admin stuff that a lot of sales guys have to do.

Manseeb Khan: I'm very excited of like just more of a personal stand point like from a salesman to a salesman like I'm very excited to like oh thank god like. hey me too you. You're saving I mean the countless number of hours of just you're going to be saving it's just again it's astronomical. Absolutely. Really is it just like it just going to make sales so much more. Salesperson you really use this term lightly because much easier. Oh yeah for sure. And it just a lot more stress-less and just like streamlined right.

Asad Naeem: I mean as long as sales is it going to be hard. even once you qualify somebody there's a lot of you know nuances that go into actually closing the sale. So, it's always going to be hard but as long as we can make the the front-end grunt work a little bit easier and you know at least taken us somewhat off the shoulders of the actual sales people. It gives them the flexibility to be able to focus more on the actual sales process and then being able to you know really being consultative and helping rather than you know just rushing through everything and trying to get to the next guy right. So, the aim really here is that we want to make sure that sales is as it stays as human as it possibly can. But at the same time, you know removing everything that is mundane and basically admin work that that can be automated.

Manseeb Khan: This is probably more of a nitty gritty question but like when it comes to qualifications and just building your models. What is your data sets look like, like where are you really pulling it from and ideally where do you want to start pulling from to get even more tactical data to work with?

Asad Naeem: Yeah absolutely. So right now, presently we're building all our data sets our self because I mean we started out by running the entire sales process for us manually. You know this is this is before we had a product, we were basically kept a record of every communication we've sent out. All emails all, the you know like social media messages whatever it is the response is we've had we've had them tagged internally because we have, we've been lucky enough to work with a with a very brilliant data scientist as well. And she's helped us. You know tag this data, clean this data, and built our models on top of it. So, you know right now we're generating our own data sets and also our clients for the first batch that signed up with us and even the second batch sent out with us. They're helping us build some of these models on as well because you know they've given us permission to use some of the data anonymized obviously to see what the sales process looks like what types of objections you get. What does a rejection look like? What does an ambiguous response look like. So, figuring out are all of these things where we would hope we could get more data is basically you know doing a partnership with a larger organization that has a very heavy focus on sales which I would think it would be every organization. Yeah no. I mean ideally every business should be focusing on sales. Exactly. And then being able to see some of the sales campaigns they have run, and you know using that transactional data essentially to be able to better our models because the more data we can feed into our model they just make the model so much about exact. Yeah exactly. It's a data play

Manseeb Khan: 100 percent is a data plan that's I'm glad you guys realize that. I mean it's a sales thing right. Exactly. It's a numbers game. All it is a numbers game. Law of Averages really. So, Assad. So just to quickly wrap this up would be the best way for people to either contact you Fortuna. Do we e-mail you? Do we tweet you? Do I send you a snapchat? What would be the best way to contact you?

Asad Naeem: Yeah absolutely. If anybody wants to get a hold get in touch with us. Just go to Fortuna.ai. So that's www.fortuna.ai, I just contact us there or you can just directly email me, my e-mail is asad@fortuna.ai.

Manseeb Khan:  Asad thank you so much for again sitting down with me today. I mean this is this has been a very fun conversation  I mean salesmen on other salesmen. And again, I'm very excited for your trajectory you guys are definitely inbounds of doing really incredible things.

Asad Naeem: Thanks so much. Appreciate it. Thanks for your time.

Manseeb Khan: Absolutely man cheers. So, on the behalf of Canada's leading international fintech and crowdfunding association. I wish you an amazing fintech Friday and weekend.

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End of Podcast

 

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Sep 14, 2026 Industrial machinery is essential in the manufacturing, construction, processing, agriculture, energy production, and other industries. Unexpected machine failures can have more than repair costs. Production can be halted, deadlines can be missed, workers can face safety hazards, and businesses can suffer financial losses. By knowing the common causes of machinery failure, operators and maintenance staff can identify problems early and take preventive action. Industrial machinery failure can have many causes. Why Industrial Machinery Fails By determining the root cause, businesses can avoid the same issue, minimize downtime, and extend the useful life of valuable industrial equipment. Here are 10 of the most common reasons for industrial machinery failure. Poor maintenance One of the biggest causes of equipment failure is poor maintenance. A machine has many moving parts and interdependent components that must be inspected, cleaned, adjusted, and serviced regularly. Small issues can turn into big ones if they aren't addressed during routine maintenance. A preventive maintenance schedule can help to detect worn components and other issues before they lead to unexpected failures. Inadequate lubrication Moving parts need proper lubrication to minimize friction and heat. Insufficient lubrication, improper lubricants, or not lubricating parts as recommended can cause faster ...
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Sep 5, 2026 | Last Updated Sep 14, 2026 | NCFA Fintech Whisperer | Payments Infrastructure And Money Movement, Digital Assets Blockchain And Tokenization, Digital Identity And Trust, Cybersecurity Fraud And Financial Crime, Digital Banking And BaaS, Capital Markets Infrastructure And Funding, Artificial Intelligence And Data, Cross Border Payments And FX, Wealthtech Investing And Trading, Embedded Finance, Insurance And Insurtech, Lending Consumer Credit And BNPL, Open Banking Open Finance And Data Sharing, Risk Compliance And Regtech, Treasury Liquidity And Cash Management, Regulation And Policy, Data Privacy And Governance This live weekly NCFA intelligence page tracks financial technology developments that significantly affect how fintechs build, sell, raise capital, and operate under scrutiny. Coverage prioritizes Canada and includes global events that directly influence competitive conditions, market access, and execution realities across fintech sectors.  This page will be updated throughout the week with market movers in a live format and then each week we'll close the prior week's contents in prep for the upcoming week, and continue on a rolling basis.  (Missed prior week's Fintech Whisperer?  (December 6-12, 2025, December 13-19, 2025, January 1-9, 2026, January 10-16, 2026, January 17-23, 2026, January 24-30, 2026, January 31-February 6, 2026, February 7-13, 2026, February 14-20, 2026, ...
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September 11, 2026 | NCFA Regulatory Insight | Artificial Intelligence And Data, Regulation And Policy, Risk Compliance And Regtech AI Literacy, Transparency and Agent Governance On September 9, 2026, the Government of Canada launched a National AI Literacy Initiative with the Alberta Machine Intelligence Institute. The $13 million partnership is expected to reach up to 1 million post secondary students and more than 50,000 K to 12 educators, alongside free learning for workers and other Canadians. The program sits under Canada's AI for All strategy and focuses on helping people understand AI, use it responsibly and recognize risks such as bias, misinformation and privacy loss. Ottawa is working on the governance side at the same time. Its AI transparency consultation remains open until September 23 and asks whether Canada needs stronger ways to identify AI generated content, tell people when they are interacting with AI, explain system capabilities, track serious incidents and record what AI agents actually do. The consultation paper says 19.2% of Canadian companies used AI to produce goods or deliver services in the second quarter of 2026, up from 12.2% a year earlier and three times the 2024 level. The federal government has already been working through ...
AI Image – Canada AI transparency, literacy and agent governance

 

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