When we talk about the future of AI, the conversation is dominated by models—LLMs, agents, prompts. But what if we’ve been looking in the wrong direction? According to Malcolm De Leo, Co-founder and Chief Business Officer at GraphIQ, the most overlooked differentiator in AI isn't the model. It’s the data.
In a recent episode of the Ignite Podcast, Malcolm shared the journey behind GraphIQ, a startup aiming to reshape how enterprise teams discover, curate, and act on business intelligence. With a unique blend of experience in chemistry, consumer products, and innovation strategy at companies like Clorox and Orbital Insight, Malcolm offers a rare perspective on building enterprise tools in the age of AI.
From PhD Chemist to Innovation Evangelist
Malcolm’s professional journey began in science, earning a PhD in chemistry. But it was his early experience building prototypes at Clorox—and being tasked with innovation without budget, authority, or team—that ignited his passion for solving big problems with small, scrappy efforts.
This “evangelist mindset” followed him throughout his career, especially in navigating entrenched cultures at legacy enterprises. His insight? Innovation only sticks if you build trust and align with the organization’s culture.
The Origin of GraphIQ: From Geospatial to Global Intelligence
GraphIQ didn’t start with a product. It started with a question: Why is it so hard to find companies to do business with?
After interviewing 40+ companies, Malcolm and his co-founder discovered a consistent pain point: even in the digital age, finding relevant B2B partners is still reliant on Google searches, old networks, or expensive consultants.
GraphIQ’s answer? A knowledge graph that maps over 280 million companies, a billion people, and hundreds of millions of locations and news articles. It turns fragmented public data into a structured, searchable intelligence platform. Think of it as the "Google Maps" of company capabilities.
Why AI is Only as Smart as the Data Behind It
While the market obsesses over models, GraphIQ focuses on the data layer—making sure inputs to LLMs and agentic AI are structured, validated, and traceable.
Malcolm makes a bold claim: "Data is the new differentiator in AI. Models are the same—what matters is what you feed them."
That’s where GraphIQ's value lies: entity resolution, capability fingerprinting, and transparent data sourcing. If you want to know what a company actually does at a specific location—and where to find 100 just like it—GraphIQ delivers.
Product-Led Growth vs. API Strategy: A Balancing Act
While GraphIQ began with a user-facing platform for sales and GTM teams, it’s rapidly evolving into a data infrastructure provider through APIs. They're now serving startups, manufacturers, law firms, and AI companies alike.
Their dual go-to-market motion includes:
Seats for SMBs and startups doing sales and market development
APIs for enterprises and AI builders who need rich, curated business data at scale
Culture as a Strategic Asset
As a self-proclaimed "culture warrior," Malcolm shared the three core principles guiding GraphIQ:
Everyone grabs a shovel, but no one's afraid to ask for help.
Know thy customer—and channel their needs.
When the best idea wins, everyone wins.
These values aren’t just platitudes—they’re tactical levers that shape hiring, product development, and go-to-market strategy.
Lessons in GTM, Fundraising & Happy Accidents
Malcolm gets candid about bootstrapping GraphIQ during a downturn. The plan was to raise VC funding early, but when that fell through, they were forced to rely on revenue and angel capital. In hindsight, this “happy accident” created a more resilient, customer-centric business.
He also offered a strong opinion for early-stage founders: "Don’t confuse closing deals with scalable sales. Scientific sales is about repeatability, not heroism."
The Future of Enterprise Intelligence
Looking ahead, Malcolm sees a world where every worker has access to a personal digital library of curated business data, powered by AI but rooted in human needs. In his words:
"You don’t want narratives stacked on narratives—you want control, traceability, and actionable intelligence."
GraphIQ aims to be that foundational layer.
Final Thoughts
Malcolm De Leo is building more than a company—he’s helping reshape how organizations find, trust, and act on business information in the age of AI. For anyone building in enterprise tech, GTM strategy, or AI infrastructure, his insights are a masterclass in thinking beyond the hype.
Chapters:
00:01 – Welcome & Guest Introduction
01:30 – Shifting from Science to Startups
03:00 – Lessons in Culture and Change from Big Companies
03:50 – The Origin Story of GraphIQ
05:00 – The “Aha Moment” Behind GraphIQ
06:50 – What Makes GraphIQ Different
09:45 – Go-To-Market Strategy and Ideal Customers
12:15 – The Forgotten Power of Data in the AI Boom
14:00 – Trust, Transparency & Attribution in AI Tools
15:00 – Happy Accidents & the Realities of Fundraising
18:00 – Balancing Revenue vs. Vision
20:20 – Product-Market Fit Frameworks
22:00 – Designing Culture on Purpose
25:00 – Remote Teams and Scaling Collaboration
26:00 – What VCs and Founders Get Wrong About Enterprise Sales
29:30 – Facing the Founder Mindset Shift
36:30 – The Next Chapter for GraphIQ
37:40 – The Future of Enterprise Intelligence
38:30 – Rapid Fire Round
44:50 – Lessons from Orbital Insight & Building Smarter
47:00 – Closing Thoughts & Where to Find Malcolm
Share this post