Growing A Soft Skills Assessment Platform For High-Volume Hiring – with Stephane Rivard from HiringBranch

In a recent episode of the HR business marketing podcast, A Better HR Business, Ben and his guest, Stéphane Rivard, talk about the long-standing HR challenges – eliminating bias, replacing traditional interviews, and leveraging realistic, skill-based assessments for high-volume hiring.

Stéphane is the CEO & Co-founder of HiringBranch, an innovative Montreal-based company using AI-powered job simulations to revolutionize the recruitment process.

HiringBranch was founded in 2022, building on more than a decade of innovation that began in 2014 under its original name, LearningBranch. Initially focused on language and soft skills training, the company accumulated years of proprietary data tied directly to real-world performance. This foundation led to the development of one of the first proprietary Soft Skills AI technologies, capable of measuring human skills with up to 99% accuracy. In 2020, the company was awarded funding from the National Research Council of Canada’s Industrial Research Assistance Program (NRC IRAP) to develop and commercialize its AI-driven soft skills evaluation platform. Today, HiringBranch assesses candidates worldwide, tailoring its algorithms by role, industry, and, in some cases, by benchmarking top performers.

Over time, HiringBranch’s Soft Skills AI has consistently demonstrated that evaluating soft skills delivers far more predictive results than language assessments alone or traditional multiple-choice and behavioral tests. People cannot be accurately measured in boxes. By focusing on real skills rather than CVs, interviews, degrees, or years of experience, HiringBranch provides a fair and unbiased approach to hiring. Organizations using the platform consistently see stronger on-the-job performance from candidates selected through skills-based assessments, proving that better hiring decisions start with better evidence.

You’ll hear practical strategies for using AI in consulting, attracting HR clients, and business growth strategies for consultants. Whether you identify as HR, workplace, L&D, OD, recruitment, or people & culture, you’ll discover real stories and actionable advice to attract clients, win contracts, and grow sustainably.

What You’ll Learn in This Episode:

• How AI-powered job simulations are changing skills-based hiring (and why it matters for consultants).
• Strategies for moving beyond traditional interviews and CVs to unbiased, evidence-based hiring.
• Stéphane’s lessons from 20+ years building a global HR tech business, and how to grow through partnerships and client focus.

• HiringBrach website: www.hiringbranch.com
• Stéphane’s LinkedIn: www.linkedin.com/in/stephane-rivard-entrepreneur

Scroll down for the audio version and the transcript.

Ok, onto the show!

Interview – How To Use AI In Consulting To Win High-Volume HR Contracts – with Stéphane Rivard, CEO & Co-Founder of HiringBranch

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About The ‘A Better HR Business’ Podcast

In my HR marketing podcast, I talk with different HR consultants and HR tech companies from around the world to learn about what they do and how they keep their businesses healthy and moving in the right direction.

If you have questions you want to ask me about growing an HR consultancy or marketing for HR tech companies, just let me know or visit the HR marketing services page.

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Enjoy the show!

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Episode Transcript

Episode 303: How To Use AI In Consulting To Win High-Volume HR Contracts – with Stéphane Rivard, CEO&Co-Founder of HiringBranch

Ben [00:00:01]:
Hello, welcome back to the show. Great to have you along, and I’m really looking forward to today’s conversation with Stéphane Rivard. Stéphane is the Montréal-based CEO and co-founder of a very cool company called HiringBranch, which is an AI-powered platform revolutionizing recruitment through realistic job simulation assessments. He and the team are on a mission to eliminate bias and replace traditional interviews with data-driven, simulated, skills-based hiring, particularly for high-volume roles, but for many more as well. But before we get into that, firstly, Stéphane, thanks very much for joining me today.

Stéphane Rivard [00:00:38]:
Yeah, thanks for the opportunity. Excited to be here with you to talk about HR and the problems and struggles with HR companies.

Ben [00:00:46]:
Yeah, absolutely, absolutely. So, I mean, I gave a snapshot, but do you want to just give us an overview of two things? One is what HiringBranch does, but also, I guess, the evolution, because I know it’s evolved over time and into very cool ways. Do you want to give us that snapshot?

Stéphane Rivard [00:01:04]:
Happy to do that. You did a great job, by the way, but happy to do that. We started the journey over 20 years ago working with high-volume, high-risk call centers. And at that time, we were mostly doing customer service training and soft skills training, language training, and also working with educational institutions around the world. And eventually, we realized that most high-volume hiring, especially outside of North America, was using language assessments, which are very good at evaluating your level of language, but this is really only a micro-skill. And more importantly, what we discovered is that your relational skills, or people skills, or soft skills, are really much more important, which we think, in the scheme of things, are really the macro-skills.

And so we started working on this. We developed our own small language model, our native AI, and it really focuses on evaluating people in a role. So we put them in the role. They talk to customers that are very closely aligned to the role that they’re applying for.

Stéphane Rivard [00:02:06]:
So this could be in a contact center, it could be a sales organization, it could be online, it could be retail, in-person retail, or as far as banking. And they would have to respond to questions, interact with a customer that is as close as possible to reality. And within this framework, we evaluate their language skills, their soft skills, their critical thinking skills. And the magic of what we do is that this is all done instantaneously and in conjunction with all these skills. So it’s not an empathy assessment, it’s not an active listening assessment. You just do your best and demonstrate the skills you have, regardless of your background. And this really is incredible because it correlates incredibly well to performance — the quality of hire. This is the metric that we find the most interesting.

Ben [00:02:58]:
I love it. I love it. So what do companies, employers, and hiring teams get wrong when it comes to skills-based hiring?

Stéphane Rivard [00:03:05]:I can tell you a story. We worked with a customer that does — they’re a sales organization. They work with charitable organizations like Doctors Without Borders, the Red Cross, and UNICEF. And they wanted to hire empathetic people, and they raised funds for them. And after we ran it through our platform, we realized that empathy was a nice-to-have skill, but this was not the skill that was able to raise money, charitable giving, to these organizations. There were other ones, and it was a combination of fluency, building rapport, handling objections, that if you could find candidates consistently with those skills, then you could really outperform in those campaigns. So that gives you an idea, even though we have a thesis that customers do — and we see this over and over and over again — which is really fascinating.

So that’s why you need a modern architecture with a skills-based model that evaluates hundreds and hundreds of skills, including acoustic features. So, in conjunction with the magic, you get great candidates.

Ben [00:04:09]:
I’m thinking something like tenacity or something like that would come out as some sort of function in those sort of roles.

Stéphane Rivard [00:04:15]:
Yeah, I think tenacity — yeah, exactly, I agree. And building — not tenacity — perseverance, grit, critical thinking. So all these little skills that are difficult to measure when you’re doing multiple-choice questions really come out when you’re doing our type of assessment, which is completely speaking, open-ended.

Ben [00:04:32]:
And I guess that gets you past the halo effect or the — what’s the — is the HiPPO, the highest-paid person’s opinion in the room or something? You know that term that says whoever’s the most highly paid, that’s the opinion that wins in a discussion. So if that person is empathetic, then they’re going to say, “Look, we need to be hiring people that are empathetic because I did that job.” Once you’re talking about data, your actual results, I really like that approach.

Stéphane Rivard [00:04:57]:
Yeah, and that’s exactly it. And it’s not static. As the world changes, so does your business problem, the products that you’re offering, and you need to evolve. So with this, it’s completely blind — the technology is completely blind — from the point of view of background.

And also HR. So what it does is that you get this great profile of that candidate, which is completely unbiased. It gives the candidate a candid, fair opportunity to get the job because really they feel confidence in the process. And more importantly, once they’ve done this and you have this report about the candidate, it gives you an opportunity to do a better interview because you’re already informed about the skills they have and the skills they may not have. So skills gap analysis, this happens on the fly. So it really answers that. And they’re always surprised by who they get to hire and the outcomes they get with the people they’re hiring.

Ben [00:05:51]:
Absolutely. So why do you think job simulations haven’t become standard, even though they’re clearly more predictive or better than CVs?

Stéphane Rivard [00:06:00]:
We’re in a very traditional business. I was reading a quote before that was saying something like people really believe in their skills — the interviewers. And I think that is difficult. Even this customer, and many of our customers, are very skeptical at the beginning that this standardized way to evaluate people does better. So we say: „you don’t need better interviews or interview skills.” And I need to put a caveat: this is for high-volume, customer-facing jobs. You’re not hiring a CEO using an AI robot. You’re hiring someone who probably is at a university, a fresh graduate out of university. You don’t need better interviews, you need better evidence. You need data that supports your decisions.

I think once you do the pilot and you get beyond that plateau, it becomes quite obvious that this is a great way, especially at the top of the funnel, to filter candidates for the skills you need.

Ben [00:06:52]:
For someone listening to this who might want to use it for their workforce, or maybe for a consultant who might refer it on to a client, how does it actually work? Is it that you would choose packages off the shelf? Are you taking position descriptions and turning it into learning and then assessing from there? How do you do it?

Stéphane Rivard [00:07:11]:
Yeah, originally, we would take a job description and build an algorithm for that. But we’ve been at it for a while now, and we have algorithms and profiles and benchmarks around the world for a variety of different roles, including banking, finance, retail, financial ops, and risk management. So now when you start with a new client and we have an idea of the profile, we can go with those right out of the box, and we just tailor as time goes on. The AI is fully adjustable according to the requirements and the outcomes you get until you get to a level of high confidence. I wish I could say perfection, but, you know, AI — just like humans — is not perfect. But we’re more reliable for these jobs than a human interviewer who’s maybe having a bad day.

Ben [00:08:00]:
Absolutely. Well, we can talk about some business growth stuff in a minute. But I think that’s quite a good moat, almost, because as you say, you’ve been in business for 20 years or something and you have a lot of data. Whereas a new company coming along, they’re going to rely on what’s out there — just public data and stuff. Whereas you’ve accumulated that, which then can feed your system, and you can also track that back to who’s a good hire versus a bad hire, as opposed to just data at the top of the funnel. Am I right in thinking that?

Stéphane Rivard [00:08:26]:
You’re absolutely right. And we’re seeing a lot of companies emerging, and they’re using LLMs – large language models from all the major providers. And we’ve done analysis, and you have to think about all this: the data out there for LLMs is only text-based. They don’t evaluate how you speak, the acoustic features. So they’re really great at understanding — even if you complete half a question, they sort of figure things out.

Ben [00:08:59]:
Fill in the blanks.

Stéphane Rivard [00:09:00]:
Yeah, fill in the blanks. LLMs are great for that. So the way we approach it is that you’re using a small language model focused on skills, and we have millions and millions and millions of pieces of data. You get much, much better results, and they’ve been proven to correlate to performance or outcomes.

Ben [00:09:17]:
I noted that it was a while back you got funding from the federal government to develop and commercialize an AI soft-skill evaluation tool, which is huge because AI is kind of everywhere. A few years back, they used to joke that you could be a café and call yourself a blockchain café and double your sales because everyone thinks, well, isn’t that cool? And now everything’s AI — even though it’s probably not. Whereas you’ve actually been trusted by the government to do it properly. So how did that work, and how do you see your product developing as time goes by?

Stéphane Rivard [00:09:52]:
We’re thankful to be based in Canada. The Canadian government has a thorough vetting process, and they have something called the National Research Council of Canada, and they will fund projects of deep science. And when we started off back five – seven years ago, this is how we got off the ground. We were only a few people with an idea. The small language model didn’t exist — these terms didn’t exist. But we went ahead and built it, and we’ve grown to over 30 people now with this kind of backing.

We are also doing another project that we’ve just recently launched with the Canadian government again, through the NRC, for the next generation of assessments. I would say it’s not easy building something from scratch, but if you want the outcomes, it’s sort of mandatory because you need that deep science — the linguistics. We have linguistics PhDs and psychometricians on our team dedicated to this. So yeah, it’s exciting, and it’s good to be backed by third parties that validate that what we’re doing is right.

Ben [00:10:56]:
Yeah, absolutely. So to clarify for people listening who, as I said, may either have a company that would potentially be using HiringBranch, or they have clients and they could refer it on: who are the ideal types of customers or clients or companies that would use HiringBranch?

Stéphane Rivard [00:11:16]:
So typically we like to work with companies that hire in high volume. So any consultancy, anyone that works — and more importantly — they have a customer who is trying to raise the bar on customer service globally. So this was really a big outcome. We’re working with another one — it’s the same thing. They have operations around the world, they can be in any kind of vertical. But the most important thing is that they want to have a data-driven approach to hiring. They need better evidence, and they want to standardize this through their organization.

And we work with all kinds of organizations. We work with some who are BPO consultancies, we work with ATS vendors, we work with video interview tools — anything that’s complementary where we can help the consultant or service provider and their customers make better-informed decisions to reach outcomes. We’re perfect partners for that.

Ben [00:12:14]:
Yeah, that’s good. And for others listening to this, I think that’s an excellent tip. There is that partnership — that complementary, not competing, company approach — that can work wonders in the HR tech space. Over the many years you’ve been in business, you’ve acquired customers not only locally but internationally. I’m very curious — how did you get your first customers? And then how has that evolved over time to where you guys are now? How do you do it?

Stéphane Rivard [00:12:39]:
Especially nowadays, we’re seeing it’s a different market. There’s a lot of noise. There’s a lot. But we started off really by attending conferences, making sure that every customer we have is a success. Like, this is really — we put all our efforts into making sure that we align with their outcomes, make sure that they’re satisfied. So word of mouth has really grown, especially with these Fortune 100 companies — that we’ve grown organically within these organizations. So being dedicated to the art of what you’re doing is really important.

And then, of course, we use SEO, which is becoming very useful, especially now, because we’re seeing a lot of people are looking through LLMs like ChatGPT, OpenAI, Gemini, looking for — and this is quite remarkable. But it’s being focused, making sure what your vertical is, which is always difficult at the early stage because you try to pivot too much. But try to focus, attend conferences, and get out there and meet people. I have a mentor, and he said, “Can you come and speak to this new cohort of startups?” And he said, “Well, I’d love to, but I can’t this week because I’m going to be in India.” And he said “How much have you traveled in your life?” And he says, “Well, I’ve traveled millions of miles. I’ve never hesitated to go meet a customer face to face.” This is exactly the message to the younger generation, you know, these startups. You need to go talk to people. You need to talk to customers or potential customers and find out what their problems are and see if you can solve them.

And I think that’s why I’ve been an entrepreneur since university, and this is what makes me the happiest — solving real problems and getting real outcomes. If I get that, then I get really excited.

Ben [00:14:23]:
I love that. And that’s an old favorite phrase from the tech world: “get out of the building.” Get out of the building. Learn what your customers’ problems are. And then, if you are selling in, how are they using your product? What could be better? What annoys them? Because both in the tech and the consulting world, I often find that if services are similar, there are always little aspects of your service that you could either white-glove, automate, or remove, or give them scripts for things — or even just management decks or presentation decks to explain the latest updates and things like that. Find little angles that you can use to help spread the word about the product and so on. And you mentioned the LLMs and SEO. I see that ChatGPT says that they’ll be doing advertising soon, so I wonder if you’re thinking about that.

Stéphane Rivard [00:15:15]:
Surprise, surprise. Yeah, yeah.

Ben [00:15:17]:
Shock, horror.

Stéphane Rivard [00:15:18]:
Shocking. Yes. What I hear is OpenAI has to invest a trillion dollars to be able to keep up.

Ben [00:15:31]:
Wow.

Stéphane Rivard [00:15:32]:
And I forget what their revenues are, but they’re nowhere near. It’s like it’s the most successful startup in the world and I think they’re around 20 or 30 billion. Which is incredible. And this data may be out of date, but I, it’s not surprising and they have to evolve and to be able to have this incredibly powerful tool, advertising and is a good way for them to do it. Do I have an opinion on that? I think it’s unfortunate. This is the way the world goes.

Ben [00:16:01]:
It’s always going to happen.

Stéphane Rivard [00:16:02]:
Yeah, it’s always going to happen.

Ben [00:16:04]:
I’m always curious hearing from founders. Any marketing mistakes, anything that you tried and just that didn’t go so well and any lessons from that.

Stéphane Rivard [00:16:13]:
I have to get my book out. There are so many of them. I think like we have our marketing person. I think marketing is a bit like the weatherman. You don’t always get it right, but you have to experiment.We’ve been to conferences which is just not a fit and the other ones we go to and it turns out to be incredibly successful. You have to experiment with different things.

We experiment constantly with different things. What we’ve noticed is that the world is becoming noisier. So you’re probably like: „I get so many emails, I get so many calls constantly.” And you have to break through that somehow. We’ve done some cold outreach. The success rate is very, very low. Is it because we’re not talking to the right acp? Is it because we’re trying. These are all we constantly ask ourselves.

The advice is that you have to experiment, you have to make sure that you keep it cost effective to quickly experiment, measure, see if it works, if it doesn’t work, then move on. So we do that quite a bit. But I still think for us the most success is back to getting out there and talk to people, whatever it may be a networking event. I belong to a founders club. I go talk to young founders. It’s fascinating. We go to financial conferences, we get invited. You reach out to your network.

Talking to people is always incredibly useful and the person you’re going to meet will come out with some new knowledge and so will you. And this will help you grow your business. Just get out there.

Ben [00:17:51]:
It’s not just getting new ideas, particularly if you’re speaking to customers or people in your target market. It’s also the repetition. You start to see certain themes arising, certain pain points or success points, whatever, and you realize, ah, everyone’s talking about that or it’s more often that they’re talking about it. We should play to that or fix that, whatever it may be. But if you just have three or four conversations and you hear three or four different things and yeah, you’ve got some ideas but you don’t get the signal from all that noise.

Stéphane Rivard [00:18:18]:
I have to agree with you. Many founders fall in love with their idea and sometimes you may have a great idea that will serve you really well, but you need a market and you need a common problem and you need to go out there and listen to people. So I agree with you. New ideas will emerge and sometimes you will pivot. If you look at how these companies like Shopify started off, the problem he had is that he was trying to collect money for his online snowboard shop. And Tobias now has a multi billion dollar business because he created an online shopping technology. And you will hear this over and over again. He’s still passionate about snowboarding, but this is not what pays the bill.

Ben [00:19:01]:
I’m just on the conference thing. So if I went to Google and said, tell me some conferences to attend, I’d get a massive list back. And you’ve talked about going to so many and you’ve gone to some that have been good, some that have been bad. And you, you never quite know is there, are there some guidelines, some rules you try to follow that that helps you choose because it costs money and it costs time, right?

Stéphane Rivard [00:19:22]:
What we do now is that we print, send someone to go walk the shows prior, now we’re at the stage when we will go and we’ll pay a pass and you go talk to people, you get a lot of insight, insight information you can reach out to. Surprisingly enough, if you go to a conference, talk to all your colleagues that attend shows that have similar technology, even if they’re the same thing, what works for you, what doesn’t work for you. It’s always surprising that it’s very collaborative even though that you’re competing against someone. The more people are in the space, the more successful you are. It’s like back to the restaurant. If you see one restaurant in the middle of nowhere, you’re not going to go, but if you see 10 restaurants on a strip, you’ll pick one of those. So you’re trying to create a community of like minded and this attracts like minded consumers.

Ben [00:20:06]:
So grow the size of the pie. And what kind of questions would you ask whether it be them or people in that field. When you say you send people ahead to walk the floor and ask questions, what kind of questions would you be asking?

Stéphane Rivard [00:20:17]:
We would try to figure out people that are close to our business that deal with either close to HR could be an ats, vendors close to the buyers. And I would ask them what shows do you attend, what kind of feedback do you get? What is your most challenging show? So always ask them the ways that they’ll open up. What was the most challenging show you attended? They’ll say why. “And tell me your best show.” They may not tell you your best show but be clever about your questions and you’ll find the right answers.

Ben [00:20:55]:
So any final either marketing or business growth advice for other people in the HR tech space that they can take away from what you’ve learned so far?

Stéphane Rivard [00:21:05]:
I can talk about what excites me and I’ll lead you some thoughts. I think what excites me going forward is that you need, people need a fair access to opportunity. You probably hear this now. We work with companies that are getting 800,000 thousand applicants for 5,000 jobs and there’s no way of a CV screening tool. So I think that what’s exciting and when you really think about, you need a fair access to opportunity, less resilient reliance on pedigree like resumes are becoming especially for customer fit, they’re not really a good source of truth. Better matching for roles, people to roles. Sometimes people are good at sales but not good at customer service, vice versa. And really HR people need to be moving from an admin function to a strategic function and you need the tools to do that.

And the last thing: everyone in this space need to think about the companies that win won’t hire faster. We’ve had a big push about efficiency and screening nowadays. They’ll hire smarter, they’ll hire more consistently. And you need proof, you need the evidence. This is how we’re positioning our company as a HR leader.

Ben [00:22:22]:
Love it. And I have seen that in some of the resources on the website. So you’re doing a great job. If people want to learn more about hiring branch, what should they do next?

Stéphane Rivard [00:22:31]:
Well, they can either reach out to our website www.hiringbranch.com or if they want to talk to me. Always happy to talk to anybody. It’s stephane@hiringbranch.com.

Ben [00:22:46]:
Very good. Well, we’ll have the hiring branch website and details on the in the show notes. But Stephane, thank you so much for sharing your story and telling us how you built and how you’re growing the business. It’s certainly an amazing product and helping create new opportunities and helping companies bring in better people and happier, more engaged people. Thank you very much.

Stéphane Rivard [00:23:09]:
Thanks, Ben, for the opportunity. I appreciate your time.

Topics covered: using AI in consulting, how to win corporate contracts, HR consultants, recruitment & talent consultants, business growth strategies for consultants.

Note: Get More HR Clients has some affiliate referral partnerships with software and service companies and may receive compensation accordingly. However, we only ever recommend products and services that we have reviewed carefully and that we trust. In most cases, we use them in our own business too.