According to PYMNTS.com, Hal Lonas, the Chief Technology Officer at identity verification firm Trulioo, highlighted the critical role of data partners as the “unsung heroes” of digital security. He explained that Trulioo’s rapid growth in business verification and know-your-business services is powered by a massive increase in the volume and variety of data it captures and analyzes. The company doesn’t just query external data sources; it ingests and maintains that data at scale to enable real-time analysis. This orchestration allows the platform to support flexible verification methods that adjust dynamically to different customer risk profiles. Looking ahead to 2026, Lonas is focused on the emerging challenge of verifying autonomous agents in “agentic commerce” and plans to expand into deeper graph-based insights to reveal business relationships.
The Data Kitchen Behind The Scenes
Here’s the thing most people don’t get about digital identity: the smooth “verify with one click” experience is a massive illusion. Or, more accurately, it’s the result of insane backend complexity. Lonas is spot on. Companies like Trulioo are essentially building a giant, constantly-updating data kitchen. They’re not just ordering takeout from a few government databases. They’re bringing in terabytes of raw ingredients—public, private, government—and then cleaning, prepping, and combining them to cook a complete meal: a verifiable identity signal.
And that shift from “pinging” sources to “ingesting” them is everything. A simple lookup is brittle. It’s a yes/no answer that fails if the data source is down or lagging. But maintaining that data internally? That’s what allows for the real data science, the pattern recognition, and the high-speed retrieval they’re talking about. It turns raw data into what Lonas calls “meaning.” Customers don’t want a spreadsheet of records; they want a clear, actionable signal that says “this is probably legit” or “you need to look closer.”
Abstraction Is The Real Product
The most valuable service Trulioo and its competitors provide isn’t data access. It’s abstraction. They’re selling the removal of operational burden. Think about a merchant or a fintech app. The last thing they want to do is manage contracts with 200 global data providers, build cleansing pipelines, and stand up specialized databases for high-performance retrieval. They just want a clean API that says “verify this person.”
This is where the whole low-friction versus high-assurance flexibility comes from. The platform can start with a simple, data-only check because it has that rich, pre-processed data pool ready to go. If something looks off, it can seamlessly escalate—suggesting a document check or a biometric scan—without the user or the client company having to rebuild the workflow on the fly. That orchestration is pure, behind-the-curtains magic. And in a world of increasing global compliance complexity, that abstraction isn’t just nice-to-have; it’s the only way to scale.
The Trust Challenge Of Agentic Everything
Lonas’s point about 2026 and “agentic commerce” is fascinating, and honestly, a bit scary. We’re already struggling to verify human identities consistently. Now we have to verify the AI agents that might be shopping, negotiating, or managing finances on our behalf? The questions are profound: Who made this agent? Who does it truly represent? Is it acting within its defined boundaries?
This opens a whole new frontier for digital identity. It won’t be enough to just verify the human at the end of the chain. You’ll need to cryptographically verify the agent’s provenance, its permissions, and its audit trail. This seems like a natural, if challenging, evolution for a company already linking complex business graphs and ownership structures. The unsung heroes of today—data and infrastructure—will become the absolutely critical heroes of that autonomous future. The race to solve agent trust is quietly starting now.
