Rivvun AI raises $7.55M for spend recovery

An estimated $2 trillion in enterprise spend and revenue goes unrecovered annually due to gaps between contractual obligations and system execution. Rivvun AI, a startup founded by former Icertis executives, announced today it has raised $7.55 million in seed funding to address this massive leakage.

The oversubscribed round was co-led by Sitara Capital and 3one4 Capital. Rivvun AI is developing an autonomous AI execution layer designed to identify and recover these lost funds.

McKinsey research indicates that procurement functions can lose up to a third of planned savings during execution. An additional 3-4% of total external spend is lost to inefficiencies and noncompliance. This compounds to over $2 trillion across Fortune 2000 companies.

The problem isn't fraud or poor contracts, but a failure of enterprise systems to automatically collect what's owed.

Founders Aim to Fix a Decade-Old Problem

Anand Veerkar and Niranjan Umarane, former senior executives at Icertis, spent a decade building the contract lifecycle management company to over $350 million in ARR. They observed a consistent pattern across industries: negotiated terms were precise, but financial execution was not.

Money owed under agreements went uncollected because no existing enterprise system was built to recover it. They left to build that system, joined by serial entrepreneur Patrick Linton.

A Structural Solution for Structural Problems

Existing systems like ERPs, CRMs, and procurement platforms manage transactions, relationships, and approvals, but they do not enforce outcomes. Rivvun's AI execution layer connects to these systems, interprets commercial obligations, identifies discrepancies, and initiates recovery at the transaction level.

This approach requires no rip-and-replace of existing infrastructure and no new system of record. It's a sophisticated approach to autonomous AI execution.

The platform uses two core agent families: Spend Assurance for the buy-side, recovering supplier rebates and procurement obligations, and Margin Defense for the sell-side, reclaiming settlement variances and unauthorized revenue leakage. This is a novel application of AI decisions.

Vertical-Specific AI for Targeted Recovery

Rivvun emphasizes a vertical-first approach, recognizing that revenue leakage patterns differ significantly across industries. Chargeback mechanics in pharma, for instance, are distinct from settlement gaps in banking or trade term failures in CPG.

The company deploys with industry-specific agent logic tuned to the precise failure patterns in sectors including Pharma, Healthcare, Banking, CPG/Retail, and Industrial.

Anand Veerkar, CEO and Co-Founder, stated, "What enterprises needed was AI that creates direct, measurable impact on the P&L, not productivity narratives, not dashboards. Rivvun closes the gap between what was agreed and what was collected, recovering money that goes straight to the bottom line."

Sachin Bhanot, Managing Partner at Sitara Capital, added, "The winners tie their value directly to a number the CFO can see on the P&L. Rivvun does exactly that with precision rare for a company at this stage."

Anurag Ramdasan, Partner at 3one4 Capital, commented, "They are not pitching a horizontal AI solution and hoping for enterprises to extract value out of it. They are delivering ROI on AI for large enterprises from the first day of implementation." This focus on tangible results is crucial for widespread AI for enterprise finance.