Previous Articles

- Modernizing FOIA: How AI Can Reduce Backlogs and Accelerate Transparency

- Hercules and Addewa AI Form Strategic Alliance to Address Manual Process Bottlenecks in Federal Operations

Early in my career, I served as a Senior Financial Manager for HUD during one of the most consequential periods in Washington, DC's housing history, when DC Housing was under federal receivership due to mismanagement. The financial infrastructure was fragmented, oversight was weak, and expense forecasting was little more than an educated guess. By introducing an Activity Based Costing model, I was able to produce expense forecasts that came within 1% of actual results. That level of precision did not just satisfy auditors, it transformed the program's credibility with budget authorities and enabled the operating budget to be increased from $27 million to $93 million. The lesson was clear then and remains true today: when financial data is structured, verified, and governed, it creates the foundation for institutional trust and resource growth. That same principle carried through my time as a Senior Financial Analyst, then a Project Manager at Freddie Mac, where I helped manage the annual budget planning process. The process I inherited was slow, manual, and consumed several months of organizational bandwidth each year. By building automated tools and fundamentally rearchitecting the workflow, I compressed that timeline to six weeks without sacrificing accuracy or rigor. Automation, applied intelligently, does not cut corners. It eliminates the friction that prevents smart people from doing their best work.

My federal financial systems experience deepened further when I joined a support contract at the Department of Defense, first as a Requirements Manager for the Defense Asset Management System, then when I managed the department's Enterprise Resource Planning process. In that environment, the stakes of invoice reconciliation errors are not abstract. Fragmented contract to invoice processes, inconsistent data standards, and manual review bottlenecks create real financial and operational liability at a scale that few organizations outside of DoD can fully appreciate.

The evidence of that systemic liability is well documented at the highest levels. The U.S. Government Accountability Office (GAO) continues to be unable to render an audit opinion on the federal government's consolidated financial statements, citing serious financial management problems at the Department of Defense and many other agencies, and the government's persistent inability to adequately account for intragovernmental activity and balances between federal agencies. This finding has been repeated across multiple fiscal years, underscoring a structural problem that incremental fixes have failed to resolve.

The financial toll of that structural failure is staggering. In FY 2024, 16 federal agencies reported an estimated $162 billion in improper payments across 68 programs, with approximately 84% of that total, or $135 billion, attributable to overpayments alone. Since FY 2003, cumulative improper payment estimates have reached $2.8 trillion, and the GAO has consistently noted that the actual figure is likely significantly higher, as reporting covers only a small subset of federal programs. Separate GAO analysis estimates that fraud, a subset of improper payments, costs the federal government between $233 billion and $521 billion annually. These are not rounding errors. They are the direct and measurable consequence of manual, fragmented invoice and reconciliation processes operating without intelligent verification.

At the transaction level, the operational reality is equally sobering. With the federal government planning to spend $1.8 trillion in 2026, the sheer volume of procurement activity makes reconciliation extraordinarily complex. Many agencies continue to depend on manual reconciliation processes that are error prone and resource intensive, with financial data dispersed across multiple disconnected systems. Currently, only 18% of Americans believe their tax dollars are being spent effectively. That perception gap has a direct cost in public trust, institutional credibility, and political capital.

The federal financial management community is actively responding to this challenge. Treasury released FY 2026 updates to financial management business standards and is executing a broad initiative to migrate agency applications to cloud platforms, work targeted to conclude in late FY 2026. Policy direction is clear: legacy, manual processes must be replaced with scalable, intelligent automation.

Proven in the Most Demanding Commercial Environments

Before bringing this capability to the federal government, Hercules.AI established a compelling and well-documented commercial track record in some of the most financially complex and precision-driven environments in the private sector. The platform has been deployed at several of the largest global law firms, institutions where billing accuracy is not merely a financial discipline but a direct driver of client trust, partner compensation, and firm reputation. In those deployments, Hercules delivered a 10 to 15 percent increase in verified billable totals by identifying billing gaps, rate discrepancies, and reconciliation errors that had previously gone undetected within high-volume, multi-matter invoice workflows.

A published Hercules case study illustrates precisely how this performance is achieved in practice. A global contingent workforce provider, managing tens of thousands of complex client and supplier contracts, each with unique fee structures and frequent amendments, deployed the Hercules platform to address a chronic breakdown in manual invoice validation. Finance teams had been relying on manual reviews, macros, and partial automation to ensure invoices aligned with contract terms. At scale, that approach failed. Teams faced weekly operational fire drills, mounting audit risk, and millions in potential revenue leakage driven by errors that were not detectable through human review alone.

The consequences of those errors were significant in both directions. Overbilling damaged client relationships and generated costly reconciliation cycles. Underbilling meant the firm absorbed supplier losses without recourse. Following deployment of the Hercules Extract, Transform, and Verify platform, the results were measurable and immediate. Within the first three months, more than 7,000 discrepancies were identified and corrected before a single invoice was issued. Over 100 client accounts were reviewed with high accuracy. More than 50 analysts adopted the platform weekly, with most reporting proficiency in under an hour. On an annualized basis, the platform now validates more than 11 million financial records each year, correcting over 23,000 billing discrepancies before invoices are generated. Billing cycles became faster and more predictable, audit readiness improved materially, and the firm repositioned AI-backed billing accuracy as a competitive differentiator in client conversations.

These were not errors born of negligence. They were the predictable and inevitable result of manual processes operating at a scale that no human team can fully govern without intelligent automation. The Hercules platform did not simply automate an existing process. It built a library of over 24,000 enforceable billing rules, applied them deterministically across every transaction, and embedded compliance logic directly into the pre-invoice workflow. The same architecture, applied to the federal government's procurement and disbursement environment, would deliver comparable and likely more significant results.

If even a fraction of that same performance against the federal government's $162 billion in annual improper payment estimates were achieved, the fiscal impact would be transformational. A 10% reduction in invoice errors and overpayments across the programs currently reporting to GAO would represent more than $16 billion in recoverable value in a single fiscal year. Applied across the full scope of federal procurement spending, including the many programs that do not yet report improper payments, the opportunity is measured not in millions of dollars, but in the hundreds of billions over a budget cycle. The commercial proof of concept exists. The technology is mature. What is needed is the institutional will to deploy it.

Purpose Built for the Federal Mission

Hercules.AI is purpose built for precisely this moment. Hercules is an enterprise AI workflow automation platform that transforms fragmented, document heavy financial operations into verified, audit ready outputs. Through its Extract, Transform, and Verify (ETV) process, the platform ingests structured and unstructured documents, translates contract terms and regulatory logic into executable rules, and automatically reconciles every line item before funds are disbursed. Hercules applies custom rule libraries aligned with FAR, DFARS, and agency specific mandates, automatically reconciling records across legacy databases, ERP systems, and project tracking tools, within a human in the loop framework that keeps senior administrators at the center of every critical decision. And because the data is never moved, the platform is FedRAMP Moderate ready, built to NIST 800-53 and 800-171 standards, and aligned to DoD IL4 and IL5 requirements. And, having passed SBOR Phase I competition, is ready for immediate Phase III deployment.

For federal agencies, the operational implication is significant. Invoices are validated against contracted rates, compliance logic is embedded continuously into financial workflows, and reconciliation becomes a governed, ongoing process rather than a year end scramble. This is not a theoretical improvement. It is the same transformation TFG Technology Solutions' personnel have delivered at more than two dozen other federal agencies, now delivered at enterprise scale through intelligent automation.

TFG Technology Solutions serves as Hercules' exclusive federal government provider, delivering this capability directly to agencies across the federal enterprise. TFG is a Native American, minority owned small business with a demonstrated track record of helping federal agencies modernize mission critical financial operations through governance, intelligent automation, and secure engineering. Our delivery model is designed specifically for the accountability and trust standards the public sector demands.

Reconciliation ensures budget accuracy, supports fraud detection, drives regulatory compliance, and fosters the financial transparency that sustains public confidence in government. The tools to achieve that at scale and with precision are available today, and the commercial results to back them up are already on the books. What has been missing is the right partner to bring them to the agencies that need them most. At TFG Technology Solutions, your success begins with us.

To learn more, visit www.tfg-tech.com or contact our team directly at info@addewa.ai.

TFG Technology Solutions

Addewa.AI

Hercules

SBIR

Sources:

U.S. Government Accountability Office, Federal Financial Accountability — gao.gov/federal-financial-accountability

U.S. GAO, Improper Payments: Information on Agencies' Fiscal Year 2024 Estimates (GAO-25-107753) — gao.gov/products/gao-25-107753

U.S. GAO, Program Integrity: Agencies and Congress Can Take Actions to Better Manage Improper Payments and Fraud Risks (GAO-25-108172) — gao.gov/products/gao-25-108172