By Rolian Ruiz, CTO Strictly

When I walked into the Elavon 2025 Partner Conference this year, I didn’t just see technology updates or new product demos. I saw the heartbeat of an industry reinventing itself.

Year after year, Elavon brings ISOs, partners, and innovators together like a family reunion, a family that pushes each other to grow, compete, and evolve. And this year, one word echoed through every hallway and conversation: Agentic AI.

From Turing to Tomorrow

The idea of machines that can think and act for us is not new. Alan Turing dreamed about it in the mid-20th century. The 1990s brought “expert systems” that could make basic decisions. Then the 2000s introduced deep learning, neural networks capable of seeing patterns humans couldn’t. But what’s happening today is far beyond that. Agentic AI represents a new era: autonomous systems that don’t just process information, but they reason, learn, and act on our behalf.

It sounds like science fiction until you see it in action. These agents can already schedule appointments, adjust travel plans, rebalance investments, book medical visits, and even make financial decisions, not just reactively, but intelligently.

Imagine this: You simply say,

Strix, change my current flight from San Diego to Miami. I need to stop in Tampa for a day. Also, schedule a meeting with Dr. G, arrange my Uber accordingly, and book my return flight to Miami the following day.

And within seconds, your Agentic AI assistant reads your itinerary, checks available flights, adjusts your calendar, books your ride, and even sends reminders to everyone involved. No clicks. No forms. No confusion. Just intelligence, AND acting on your behalf.

Some fear that this evolution will replace human roles. But history has always shown the same pattern: technology eliminates what is repetitive and enhances what is meaningful. The challenge and opportunities lies in adapting faster, smarter, and with purpose.

Strictly’s Journey into Agentic AI

At Strictly, innovation has always been our compass. Years ago, we developed expert systems that classify card types with over 99.9% accuracy, solving one of the most overlooked but critical problems in payments, correct transaction classification for surcharging and follow card brand rules and regulations. This wasn’t just an internal tool; it became a foundation that helps processors and ISVs using our APIs stay compliant and precise.

At Strictly, innovation has always been our compass. Years ago, we developed expert systems capable of classifying card types with over 99.9% accuracy, solving one of the most overlooked yet critical challenges in payments, ensuring accurate transaction classification for surcharging while adhering to card brand rules and regulations. What began as an internal tool has since evolved into a core foundation that enables ISVs/SaaSs using our APIs to remain both compliant and precise.

But we didn’t stop there. We began applying Agentic AI to solve deeper challenges:

• Strictly Guard, our risk-detection agent, now learns from transaction patterns, from AVS mismatches and CVV failures to chargebacks, and autonomously decides when to block high-risk transactions.
• Scheduling Agents coordinate workflows and automate operations.
• Merchant Churn Agents predict when a merchant may leave, giving partners time to act.
• Reporting Agents autonomously detect and correct surcharge variances, even pennies ensuring precise, error-free reconciliation across every merchant and deposit.

These systems are getting better every day, not because of luck, but because they learn from vast, high-quality data sets enriched through Elavon’s P365 platform and our own data lakes. Our partnership with Elavon gives us not only data, but wisdom, the north star to align innovation with real-world impact.

The Flaws, Risks and Realities of AI Today

As powerful as Agentic AI can be, it is far from perfect. And anyone who pretends otherwise isn’t being honest about the state of AI today.

The truth is this:
AI is brilliant, but it is also inconsistent.
Two identical situations can lead to two different decisions. Sometimes it takes the right action. Sometimes it makes a mistake. Sometimes it takes too long. Sometimes it surprises even the people who built it.

These aren’t just glitches, they’re core challenges of Machine Learning itself. AI models:

• Can interpret the same data differently on different days
• May hallucinate or assume incorrect patterns
• Can produce uncertainty when data is incomplete
• Sometimes “overcorrect,” taking actions that are technically valid but contextually wrong

And when the stakes involve money, risk, and compliance, these inconsistencies cannot be ignored.

At Strictly, we’ve learned that transparency is the antidote to inconsistency.
Every agent we build from Strictly Guard to our Reporting Agents is paired with a full Decision Log, a transparent and traceable record of:

• The inputs the agent received
• The features it evaluated
• The confidence level behind its decision
• The action it took
• Alternatives it considered but did not select
• The model version used
• The data source powering the prediction

These logs allow engineers, partners, and ISOs to audit every decision, just like reviewing a medical chart.
If something goes wrong, we can rewind the exact thought process of the agent step by step and correct it.

Why Data Quality Is Everything

If AI is the brain, data is the oxygen. Poor data creates poor decisions, and that’s dangerous in finance. I often compare it to medicine: you wouldn’t trust a doctor who misses symptoms or misreads a chart. You’d want one who listens carefully, gathers complete information, and provides a precise diagnosis.

Payments should be no different.

That’s why I believe the industry must come together to establish a standard for payment data exchange, similar to HL7 or FHIR in healthcare. Those standards transformed medicine by letting every system “speak the same language.” It’s time we do the same in payments. Only then can our agentic systems truly make the right decisions, at scale, safely and transparently.

A Family of Innovation: The Spirit of Elavon

Conferences like this remind me that progress doesn’t happen in isolation. It’s built through partnerships, through people who share knowledge, challenge ideas, and believe that better technology means better lives.

Every conversation with the Elavon team, every handshake, every exchange, reinforces that sense of belonging. Elavon doesn’t just set the bar; they lift everyone around them. Their leadership encourages ISOs and partners like us to not only compete, but to innovate boldly and responsibly.

To Gail Poders, Terry Chapman, Jimmy Lewis, Edward Searcy, CPA , D.Mac, Ashley Jones, Lisa Brooks Carmichael and the entire Elavon family, thank you. Your mentorship, collaboration, and trust have shaped our journey. Together, we are building not just products, but the future fabric of intelligent payments.

A special thanks to Leigh Cook and her husband from Today Payments for the inspiration, hospitality, and collaboration that remind us why this industry is so unique. From picking us up at the airport in San Diego, to lending us a car, to sharing lunch and ideas, you showed that even in a competitive landscape, partnership and learning from one another make us all stronger.

A Call to ISOs and Innovators

To every ISO and partner reading this, the future is not waiting. Agentic AI is here. It’s learning. It’s deciding. It’s redefining how businesses operate. This is your moment to engage, learn, and experiment. Join the movement. Ask for training. Build the foundation for your own agentic systems. Don’t fear the change, let’s help design it.