Hello to Canada’s SaaS Community,
At SAAS NORTH, Founder & CEO of TealBook, Stephany Lapierre delivered a no-fluff fireside chat with Danielle Smith of National Bank, offering practical takeaways and a rare glimpse into what it really takes to build and launch a generative AI product that works.
TealBook is one of Canada’s fastest-growing enterprise SaaS companies, recognized by Forbes and Gartner for its work in transforming supplier data intelligence. Under Stephany’s leadership, the company has raised over $95.2 million CAD from top-tier investors like Ten Coves Capital and BDC, and its technology is trusted by Fortune 100 companies to drive procurement transformation through cleaner, more accessible data.
Her core message at SAAS NORTH? Future-proofing your SaaS company with Gen AI isn’t about trends or hype, it’s about doing the (not so glamorous), foundational work: cleaning your data, solving real business problems, and embedding AI into workflows people already use.
Key takeaways:
- Good AI starts with good data and quality matters more than quantity.
- Focused use cases beat broad ambitions when scaling Gen AI.
- AI should make work easier, not add complexity.
Co-Founder/Producer, SAAS NORTH Conference Editor, SAAS NORTH NOW
Generative AI has become the loudest conversation in SaaS but at SAAS NORTH, Stephany Lapierre, CEO of TealBook, brought the clarity. In a refreshingly tactical session, she unpacked what it took to build and launch Aime, TealBook’s Gen AI-powered supplier intelligence tool.
Rather than leaning into hype, Stephany focused on the operational realities: building with purpose, starting with clean data, and solving real problems inside real workflows. Her approach is a masterclass in how to move from prototype to production, and a reminder that in the age of AI, disciplined execution beats ambition alone.
Here are four lessons every SaaS founder should take from TealBook’s tried and tested approach.
1. With Great Data Comes Great AI
TealBook didn’t start with prompts or flashy models. They started with data; cleaning, structuring, and enriching supplier information across 13 million companies. Before building Aime, they spent years becoming a data-first company.
For Stephany, the biggest blocker to Gen AI adoption wasn’t tooling, it was trust in the data.
She said, “It all starts with good data posture, and if you don’t have a solid good data foundation, it’s going to be really difficult to leverage the technology.”
Aime’s performance depends entirely on TealBook’s ability to deliver accurate, structured data. Instead of massive, messy datasets, they trained on smaller, high-quality sets to ensure consistency and better results.
“If you can use less data, but really good quality… we had to do a lot of testing from open chat to now being more guided in our approach.”
The overriding lesson was simple: don’t invest in Gen AI until your data is ready to support it.
2. PoCs Don’t Guarantee Progress
Most Gen AI initiatives in the enterprise never make it past the prototype stage, as Stephany noted, “90% of the Gen AI PoCs don’t scale beyond the PoCs.”
TealBook avoided that outcome by focusing early. They launched a Tiger Team in May, shipped a working Aime prototype in 30 days, and spent four more months refining and adapting it with customer feedback.
This wasn’t an experiment for the sake of innovation. It was a targeted initiative designed to validate one clear use case and scale it, but many enterprise leaders still assume they need to build in-house.
In fact, “96% of procurement leaders… would say they would build or hire someone to build a Gen AI app versus buying it.”
Stephany cautioned against that assumption. Scaling Gen AI means solving real challenges around data quality, compliance, and team adoption. TealBook succeeded because they stayed focused and built something real.
3. AI Should Empower, Not Overwhelm
Aime wasn’t built to impress. It was built to work. From day one, its goal was to make supplier decisions faster and easier for users across the business.
Instead of introducing a new platform, TealBook integrated Aime into tools teams already used, like Slack, Teams, and intranets.
“That person in marketing could just ask Aime, ‘Hey, which agency have we used for experimental marketing that has a contract?’”
That kind of accessibility made adoption simple. Rather than creating more tools to manage, Aime helped unify workflows and improve operational speed.
“There’s more complexity around having multiple chat bots and multiple Gen AI tools… and so how that’s going to be centralized and leveraged in a way that people don’t get confused.”
Simplicity drives usage, which is why Aime works.
4. In AI, Agility Beats Certainty
Stephany’s final message was clear: in Gen AI, nothing stays still for long.
“What was true three weeks ago is not true anymore. And so how do you keep up with this, especially when you’re in a dynamic building environment.”
TealBook’s ability to adapt came from tight feedback loops, clear team ownership, and a willingness to experiment.
“Just try and play with it and see if it’s the right decision for your business.”
In an environment that evolves weekly, founders don’t need perfect plans, they need momentum and what matters most is getting started and staying flexible.
The bottom line? Gen AI is moving fast, but success still comes down to fundamentals.
TealBook’s journey with Aime shows that data quality, clear use cases, and speed-to-learn will always matter more than hype. For founders building in the age of AI, that’s the model to follow.
SAAS NORTH is THE Canadian hub for rapidly-scaling SaaS founders and their teams. Learn, network, and grow with Canada’s largest in-person SaaS community at SAAS NORTH.