ImagineX has been named one of Consulting Magazine's 2026 Best Firms to Work For, ranking #7 among Small Firms nationwide. This marks the ninth consecutive year ImagineX has earned this recognition — a reflection of the culture, people, and commitment that define the company.

ImagineX is on the 2026 Inc. 5000 — our fourth time on the list — with a 52% CAGR and 4× revenue growth since 2021. Read on to hear from our CEO and COO on what's driving it.

ImagineX has acquired Payteros, expanding its capabilities to help enterprise clients modernize, simplify, and scale digital operations. The acquisition combines ImagineX's expertise in AI, strategy, design, and engineering with Payteros' deep digital transformation capabilities — together accelerating innovation for clients across Financial Services, Retail & Hospitality, Energy & Infrastructure, and beyond.

Winning an enterprise payment deal is momentum. But in large SAP environments, revenue does not start when the contract is signed -- it starts when transactions begin flowing through the ERP. The integration strategy inside SAP is what determines how fast that happens.

AI is showing up inside enterprise payment platforms -- not as a replacement for finance teams, but as a layer that reduces the friction those teams have learned to live with. The impact tends to land in three places: routing decisions, reconciliation, and visibility into what is actually happening. But it only works when it connects properly to the ERP.

The conversation about stablecoins in enterprise finance rarely stalls on the technology. It stalls on what happens after the payment moves -- posting, reconciliation, exceptions, and audit. Understanding what stablecoins actually require from a finance organization is a better starting point than debating whether they will succeed.

The payment rail can be instant. The finance process behind it usually is not. Real-time payments solve the speed problem -- but enterprise teams that have not prepared the back office often discover a faster path into a slower exception queue.

AI agents are beginning to move beyond recommendations -- they are initiating, managing, and executing payments with delegated authority. The promise is real. But enterprise finance teams will not adopt agentic payments because the technology works. They will adopt them when they can prove it works within the company's rules.

Most organizations have invested heavily in ERP modernization -- and the results speak for themselves. But one critical financial process consistently gets left behind: payments. Here's why that gap exists, why it matters more than ever, and what closing it actually looks like in practice.

In this episode, Travis sits down with Don Wedington to discuss how relationships are the key to sales, even in our new AI world.

Secure your AI tools with cross-cutting governance. Learn how to manage access, runtime security, and compliance across your Enterprise AI Framework.

Transform your business with mission-critical AI. Discover how engineers use multi-agent value streams and developer platforms to scale.

Discover what happens when AI workflows hit the no-code ceiling. Learn how technical teams build complex agentic workflows and IT-grade applications.

Empower your non-technical teams to build their own AI workflows and citizen apps. Learn how to eliminate IT bottlenecks safely with the AI Framework.

Explore the 'No Build' layer of the Enterprise AI Framework. Learn how Knowledge Assistants and Agentic Desktops deliver immediate value to employees.

Solve AI tool sprawl with an Enterprise AI Exchange. Learn how to create a unified, discoverable portal for employees to find and rate AI capabilities.

Overcome AI tool sprawl with the Enterprise AI Framework. Learn how to structure your AI strategy across four capability layers with centralized governance.

Move from scattered AI experiments to a governed, enterprise-wide platform. Read our 7-part series on building an AI Framework that empowers users and secures your data.

After years of experience across the software engineering spectrum, I saw firsthand how AI tools can boost code output by ten-fold—but only if you rethink how you work. AI doesn’t replace human expertise; it shifts our role from writing every line of code to defining requirements, guiding AI, and rigorously reviewing results. To truly benefit from this acceleration, teams must upgrade not just tools but their entire development systems—improving testing environments, CI/CD processes, communication, and quality checks—so speed doesn’t come at the cost of stability.

AI works best when it’s predictable. This post explores how breaking complex tasks into clear phases—with checkpoints for review—turns AI from a black box into a reliable collaborator. If you want agentic workflows you can actually trust, it starts with how you structure the work.