Transcard, a U.S.-based business-to-business (B2B) payments firm, has teamed up with cloud consultancy Coretek to embed artificial intelligence directly into its payment platform, serving up real-time financing recommendations to corporate users. The new AI-driven intelligence layer, built on Microsoft Azure and Microsoft Fabric, appears inside the platform’s Azure Insight Tab, blending transactional data with predictive analytics to suggest financing options mid-workflow.

What Actually Changed

The partnership delivers a tangible upgrade to Transcard’s existing SMART Suite, a cloud-based ecosystem that already spans accounts payable, accounts receivable, and treasury management. With Coretek’s integration expertise, the companies have wired an AI engine into the Azure Insight Tab, a dashboard area that previously offered only descriptive analytics on payment flows. Now, it actively proposes financing actions—think early-payment discounts, short-term loan offers, or dynamic supplier financing—based on a company’s real-time cash position, historical spend patterns, and market data.

Under the hood, the solution leans heavily on Microsoft Fabric, the unified analytics platform that pools data from Azure Data Lake, Azure Synapse, and Power BI. Fabric’s role is to normalize and process vast streams of payment transactions, supplier invoices, and bank feeds without moving data among disparate silos. This “single pane of glass” approach lets the AI model generate recommendations in milliseconds, so a controller reviewing a batch of invoices sees a “suggested financing” card alongside each line item. The system uses Azure AI services—likely Azure Machine Learning and Azure Cognitive Services—to train models on proprietary Transcard data, with Coretek handling the MLOps pipeline and governance.

Transcard’s existing customers gained this feature as a phased rollout starting in early 2025, according to a joint statement seen by Windows News. No additional licensing tier was announced, suggesting the intelligence tab is bundled into existing enterprise plans. However, companies need to have their data sources fully onboarded to Fabric to unlock the advice layer, which may require a light integration sprint for those still on legacy connectors.

What It Means for You

The impact splits along role lines.

For finance leaders and controllers, the most immediate benefit is closing the gap between seeing cash flow data and acting on it. Instead of pulling a report, calling a bank, and negotiating a credit line, the AI surfaces pre-approved financing offers right when an invoice is due. Early adopters in beta reportedly trimmed days sales outstanding (DSO) by up to 15 percent, according to Transcard’s internal metrics, though the company hasn’t published a formal case study yet. The risk, of course, is overreliance: an algorithm that always suggests extending credit could nudge a company toward unnecessary debt, so finance teams still need to apply judgment.

For IT and platform administrators, the headline is tighter Azure integration. Because the AI layer lives inside the Azure Insight Tab, it inherits Azure Active Directory’s identity management, data residency controls, and the compliance certifications of the underlying cloud. That should ease security reviews compared to bolting on a third-party robo-advisor. But admin teams will need to map out Fabric’s compute costs—Microsoft bills Fabric capacity units (FCUs) separately—and watch for any spike when the AI model retrains on large transaction histories.

For developers and data engineers, the build showcases a reference architecture for embedding generative or predictive AI into line-of-business apps. Coretek reportedly used Fabric’s shortcut and mirroring features to avoid heavy ETL, linking Transcard’s operational databases to the analytics engine with zero-copy data sharing. Teams considering similar projects can study the approach to cut their own integration time.

How We Got Here

Transcard has been a quiet giant in B2B payments since 2001, powering digital disbursements for airlines, insurance carriers, and logistics firms. The company’s shift toward embedded intelligence reflects a broader market: McKinsey estimates that embedded finance—banking, lending, and insurance woven into non-financial software—could generate $230 billion in annual U.S. revenue by 2025. Transcard’s move follows similar plays by Stripe, which launched Stripe Capital, and Square’s (now Block’s) instant loans, though those target small businesses rather than mid-market supply chains.

Coretek’s involvement is less about brand-name buzz and more about delivery muscle. The Farmington Hills, Michigan-based consultancy carries multiple Microsoft Gold competencies and has deep experience migrating financial workloads to Azure. The firm previously built a clinical analytics hub on Microsoft Cloud for Healthcare, so its refactoring of AI models for regulated payment data isn’t a moonshot.

On the technology side, Microsoft Fabric reached general availability in May 2023, but only in the past 18 months have independent software vendors (ISVs) begun weaving it into vertical-specific apps. Transcard’s adoption signals that Fabric is mature enough for mission-critical payments—no small feat given the ACID compliance and sub-second latency that B2B money movement demands.

What to Do Now

If you’re a Transcard customer with a dedicated customer success manager, reach out to schedule a walk-through of the Azure Insight Tab’s new AI module. Ask these questions:

  • Data prerequisites: Which on-premise or legacy ERP connectors need updating to feed Fabric?
  • Opt-out controls: Can a finance user dismiss a recommendation, and does that feedback improve the model?
  • Cost monitoring: How does Transcard meter Fabric capacity, and are spikes in AI inference billed separately?

For organizations still evaluating AI in payments, treat the Transcard-Coretek announcement as a blueprint, not a one-off. Audit your own payment workflows: Where do manual handoffs occur between insight and execution? If you’re already on Azure, schedule a briefing with your Microsoft account team about Fabric’s real-time analytics capabilities. The same pattern—data lakehouse plus embedded AI—can be applied to accounts payable automation, dynamic discounting, or even reconciliation bots in your own environment.

Businesses using competing payment platforms (Coupa, Tipalti, Airbase) shouldn’t expect to be left behind. Most major procure-to-pay suites are either building or white-labeling similar AI advisors. Your job as a buyer is to press vendors on model transparency: Will you see the data that trained the recommendation engine? Can you adjust the risk tolerance? Without those answers, the AI is a black box, and in finance, black boxes don’t pass audit.

Outlook

Transcard’s financing recommendations are a stepping stone toward fully autonomous treasury management, where machines not only suggest but also execute cash transactions within preset guardrails. Microsoft’s deepening pile-in—via Fabric, Azure AI, and its Dynamics 365 Finance suite—means the $12 trillion B2B payments market is inching closer to a point where every invoice comes with an instant, AI-calculated financing option. For now, though, the human-in-the-loop remains essential. Watch for case studies and regulatory guidance on AI-driven lending advice over the next two quarters; both will determine how fast CFOs adopt the technology.