Meet Siju Ramakrishnan — Tundra Managed Solutions' New VP of AI & Innovation

We’re thrilled to welcome Siju Ramakrishnan as Tundra Managed Solutions' (TMS) new Vice President of AI & Innovation- a globally respected AI leader known for transforming bold ideas into human-centric solutions across various industry domains.

Most recently, Siju led the development of an AI-powered conversational commerce assistant at Canadian Tire, earning national recognition with the 2024 CIO Canada Award for innovation and business value. 

Beyond his enterprise work, Siju leads Budhhi, an applied research and innovation practice focused on emerging technologies, including agentic AI and machine learning. At Budhhi , he collaborates with global industry experts and academic institutions to explore and test next-gen capabilities - work that often seeds ideas for enterprise implementation.

Siju is also a featured speaker at global summits such as Web3 Toronto, Future Festival, APAC AI Summit in Hong Kong.

We sat down with Siju for an in-depth conversation on his journey, the future of emerging tech, and what’s next for TMS.

Q1. You’ve worked across industries and technologies. When you look back at your career, what are some of the projects or breakthroughs you’re most proud of?

More recently, my work with Canadian Tire shifted the search experience from keywords to conversation, considering user intent, location, and lifestyle as key factors. It won the 2024 CIO Canada Award, but more importantly, we learnt the potential of how AI can reshape how customers engage with digital offerings.

Then there’s the work at Budhhi, where we experiment with technologies ahead of the curve like Quantum Fourier transformations, VR commerce pilots, digital twins, agentic AI and turn those learnings into practical, enterprise-grade tools.

As an example, one that stands out was building Canada’s national payment fraud detection platform, used by Tier 1 and Tier 2 banks. It’s rare to see a system scale nationally and still stay responsive to the threat landscape. I'm very proud of these achievements.

Q2. You speak regularly at conferences and universities around the world. What topics do leaders and students keep coming back to, and what do you think they’re still missing?

There’s a lot of curiosity about generative AI, of course. But the deeper conversations - the ones I get most often are about trust. People ask: How do we know AI is right? Is it ethical? Will it scale safely? No matter what country I am speaking or to which audience, the best discussions come from those asking not just “What can we build?” but “Should we?”

Students and early professionals are deeply curious about agentic AI, a model that is adaptive, learns, and executes.

Another topic that comes up is human-AI collaboration and what that means for the future of technology. We don’t talk enough about what it means to have long-lived agents in production environments, how they learn, drift, and integrate into human workflows. 

Q3. You’ve led projects in areas like AI, Web3, Automation, IoT, and predictive modeling. How do you decide which emerging technologies are worth investing your time and energy in?

It starts with the problem, not the tech. I’ve always believed that innovation must be intentional. If a problem can be solved with a simple spreadsheet, don’t use a Language Learning Model. But if it demands dynamic context, prediction, or personalized decisions, then you evaluate the tech that fits.

I also look for patterns like repeated questions or challenges across industries. When multiple sectors are struggling with similar inefficiencies, that’s often a signal that a shift in technology is due. I would say look at the signal strength, who’s investing, where the open-source communities are active, and what use cases are adjacent to other enterprise needs.

Ultimately, I’m drawn to technologies that unlock new modes of interaction, decision-making, or trust-building, especially when they’re grounded enough to evolve from prototype to production.

Q4. Now that you’ve joined TMS, how do you see your role in helping organizations take the next step with AI and innovation?

My role is to make AI real, responsible, and revenue-generating for organizations that want to stay relevant. The majority of organizations are willing to invest in AI, and many times it's because of the hype, and that’s a trap. So, I want to help them assess if their problem really needs AI or other technology to solve, helping them invest wisely. It’s important to stay relevant but not at the cost of wasting money and hurting the brand, so fail fast and make informed decisions.

My focus at TMS is helping clients bridge the gap between potential and production, shifting from experimentation to meaningful transformation, and advancing how organizations work, serve, and grow.

We don’t just explore tech for the sake of it. TMS gives me the perfect platform to scale the applied research work we do at Budhhi for enterprise environments. At Budhhi , we stress-test ideas across sectors with academic and industry collaborators. With TMS's established technology partners, we can look past the hype and solve real problems.

Overall, our focus is on exploring and implementing frontier technologies. Whether that’s quantum applications, automation, or predictive systems, we put these solutions through rigorous, real-world experimentation before we take it to application. I'm excited for the next chapter and working with TMS's established clients.