This US-based SaaS company delivers a cloud-native Accounts Payable (AP) automation platform designed specifically for healthcare providers. Hospitals, multi-specialty clinics, and healthcare networks across the nation rely on this subscription-based platform to process hundreds of thousands of supplier invoices every month, manage vendor relationships, and maintain compliance with strict healthcare financial regulations.
The client contacted SunTec India about a year after the product launch, when early adopters began reporting frequent mismatches in purchase order references, missing line items, and occasional misread CPT codes. Around 10–12% of invoices were consistently landing in exception queues, forcing provider finance teams to step in manually. This created delays in reimbursements, late supplier payments, and rising dissatisfaction among users who had subscribed with the expectation of end-to-end automation.
The platform's AI extracted invoice data but lacked strong multi-level validation logic. Totals, tax fields, CPT codes, and PO references weren't always cross-checked, resulting in reconciliation issues for providers.
10–12% of invoices processed by the platform triggered exceptions (ambiguous line items, vendor mismatches, duplicate submissions). Clients often had to step in manually, eroding the "hands-free" automation promise.
The platform generated AI confidence scores, but without healthcare-specific thresholds. This created false positives (over-reviewing clean data) and false negatives (letting errors slip through), undermining trust.
Healthcare providers reported longer approval cycles, strained supplier relationships, and risk of late-payment penalties when exceptions were unresolved.
As the subscriber base grew, exception rates threatened SLAs, platform performance metrics, and ultimately customer retention.
They engaged our team to address these quality and exception-handling gaps through invoice processing services so that the platform could deliver error-free, compliance-ready outcomes at scale.
The client already had an AI-powered invoice processing platform in place. What they needed was a dedicated human layer of quality control to validate edge cases, handle recurring exceptions, and provide transparent reporting that healthcare providers could trust for compliance and audit purposes. SunTec India bridged this gap by introducing field-level data validation, structured exception resolution, and rigorous reporting protocols.
The project involved a team of 30 domain-trained QA specialists with expertise in healthcare invoice processing, with a dedicated project manager.
Every AI-processed invoice was subjected to line-item level checks by our QA specialists. This end-to-end invoice validation process ensured data integrity and eliminated common data leakage points that previously led to reconciliation delays for providers.
Instead of letting exceptions pile up for the client's or the end-user's (healthcare firms) AP teams, we built a structured exception management process around the client's platform. This approach reduced exception backlogs and ensured providers received "clean invoices" ready for payment runs.
In addition to invoice data validation services, we also delivered structured QA and exception reports back to the client and their healthcare customers. These reports gave the SaaS provider a clear view into platform performance while providing the end users with audit-ready documentation for compliance teams.
Because the invoices contained sensitive healthcare billing data, we maintained compliance-grade security protocols throughout the process:
By directly addressing the gaps that had surfaced post-launch, our intervention restored user confidence in the client's AI SaaS platform for automated invoice processing.
Data Accuracy Restored
99.95%+ invoice data accuracy achieved through field-level invoice data validation.
Exceptions Backlog Reduced
80% drop in pending exception cases with invoices delivered in a payment-ready state.
Confidence Scores Validated
100% of low-certainty fields double-checked, eliminating false positives/negatives and restoring trust in the platform.
Scalability with Accuracy Secured
2x processing capacity added to the client's AI SaaS product without increasing error rates.
SunTec helped us take our AP automation solution to the level our healthcare clients expected. The improvement in accuracy and reconciliation speed has been a turning point for adoption.
- VP, Product Management
Our invoice processing services are embedded with a human-in-the-loop (HITL) layer, which ensures that:
Low-confidence AI outputs are validated by specialists, so invoices with ambiguous fields never bypass compliance safeguards.
Manual corrections are looped back into the system, enabling the client's AI to learn from real-world edge cases and steadily improve accuracy.
End users of the AI solution gain more trust in the system - In this case, we ensured that invoices were both automation-fast and audit-ready, strengthening the client's vendor relationships and reducing friction in payment cycles.
In this project, it was not a question of replacing AI, but of balancing automation with expert oversight. This balance positioned the client's SaaS platform as a credible, compliance-aligned AP solution for healthcare providers — one that could scale without sacrificing reliability.
Our invoice validation services work alongside your AI to: