Rivvun AI Secures $7.55M to Plug Enterprise's $2 Trillion Financial Leak

SEATTLE, WA – June 10, 2026 – In the intricate world of enterprise finance, a staggering amount of value quietly vanishes. Now, a new company, Rivvun AI Inc., has secured $7.55 million in an oversubscribed seed round to build the technology that catches it. The round, led by Sitara Capital and 3one4 Capital, will fund the deployment of an autonomous AI platform designed to recover the estimated $2 trillion that evaporates annually in the chasm between contractual agreements and financial settlement.

Founded by enterprise software veterans Anand Veerkar, Niranjan Umarane, and Patrick Linton, Rivvun AI is not targeting fraud or bad deals. Instead, it’s aiming its advanced technology at a more pervasive and structural problem: the money that companies are owed but their existing systems were never built to collect.

The $2 Trillion Chasm

The scale of enterprise value leakage is immense, a figure often relegated to the footnotes of financial reports. Research from McKinsey finds that up to one-third of planned procurement savings are lost during execution, with an additional 3-4% of total external spending disappearing due to transaction inefficiencies. Compounded across the world's largest companies, this amounts to a multi-trillion-dollar black hole.

Independent research reinforces this sobering reality. Studies show that businesses lose, on average, 9% of their annual revenue due to non-compliance with their own contracts, a problem that can cost a single large company over $14 million a year in fees, disputes, and lost opportunities. For many large enterprises, this leakage can climb as high as 20% of their total revenue annually. This value isn't stolen; it’s lost in translation between departments, systems, and spreadsheets. The problem is structural, rooted in the very architecture of enterprise technology.

Enterprise Resource Planning (ERP) systems are built to record transactions. Customer Relationship Management (CRM) tools track sales pipelines. Procurement platforms manage approvals and vendor selection. While each is a powerful system of record, none were designed to be a system of enforcement. They lack the intelligence to autonomously cross-reference a complex supplier rebate clause against millions of transaction lines and initiate a recovery for a discrepancy. This gap is where value disappears—in uncollected rebates, unenforced pricing commitments, and misaligned trade terms.

A New Breed of AI: The Autonomous Execution Layer

Rivvun AI’s solution is not another dashboard or analytics tool. The company has developed what it calls an “autonomous AI execution layer,” a system designed to act as a financial sentinel that sits between a company's commercial obligations and its financial systems.

Instead of requiring a costly and disruptive “rip-and-replace” of existing infrastructure, the platform connects to a company’s current ERP, CRM, and procurement systems. Its AI agents then interpret commercial obligations codified in contracts and agreements. The system identifies what hasn't settled as agreed and, crucially, initiates the recovery process directly at the transaction level.

Two families of AI agents power the platform:

• Spend Assurance: Operating on the buy-side, these agents focus on recovering value from suppliers. They tirelessly monitor for unenforced procurement obligations, such as volume-based rebates, early payment discounts, and negotiated pricing commitments that were missed in the payment process.
• Margin Defense: On the sell-side, these agents protect revenue. They identify and recover funds lost to customer settlement variances, discrepancies in trade term execution, and revenue that left the profit and loss statement without proper authorization.

“The enterprise has spent years being told AI will transform how it operates,” said Anand Veerkar, CEO and Co-Founder of Rivvun AI. “What it 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.”

From Industry Insiders to AI Innovators

The credibility of Rivvun’s ambitious mission is anchored in the deep industry experience of its founders. Anand Veerkar and Niranjan Umarane spent the last decade as senior executives at Icertis, a global leader in contract lifecycle management (CLM). There, they helped scale the company to over $350 million in annual recurring revenue and gained a unique, front-row view of the world's largest commercial portfolios.

Across every major industry, they saw a consistent pattern: companies would invest heavily in structuring precise terms of trade, only to see significant value leak away during financial execution. The problem wasn't the contracts; it was the lack of a system designed to enforce their financial outcomes automatically and at scale. They left to build that missing system, joined by serial entrepreneur Patrick Linton, who brings critical experience in scaling global operations for enterprise software companies.

This background provides what investors call exceptional “founder-market fit.” As Anurag Ramdasan, Partner at 3one4 Capital, noted, “The team at Rivvun is one of the strongest founder-market fit we’ve seen in the vertical AI category so far. 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.”

Vertical-First: Why Generic AI Fails in Complex Finance

Rivvun is consciously avoiding the pitfalls of generic, one-size-fits-all AI. The company is deploying with a “vertical-first” strategy, recognizing that financial leakage is not a generic problem. The mechanics of a pharmaceutical chargeback involving government pricing obligations bear little resemblance to settlement gaps in banking or trade promotion failures in the consumer-packaged goods (CPG) industry.

To address this, Rivvun's platform uses vertical-specific agent logic tuned to the precise failure patterns of each sector it serves, including Pharma, Healthcare, Banking, CPG/Retail, and Industrials. This specialized approach allows the AI to understand the unique regulatory frameworks, contractual nuances, and operational workflows that define each industry, leading to more accurate and effective recovery.

This strategy positions Rivvun at the forefront of a trend toward highly targeted AI applications that deliver concrete, provable returns over the broad promises of general-purpose platforms.

Investor Confidence and the Future of Financial Recovery

The oversubscribed $7.55 million seed round signals strong investor confidence in Rivvun’s team and technology. For venture firms, the ability to directly quantify a solution's impact is the gold standard.

“We’ve invested in enterprise technology for years. The winners tie their value directly to a number the CFO can see on the P&L,” added Sachin Bhanot, Managing Partner at Sitara Capital. “Rivvun does exactly that with precision rare for a company at this stage – and with a founding team that has already built a category-leader in this space.”

By moving beyond mere analytics and into autonomous execution, Rivvun AI is offering a tangible solution to a problem that has silently drained enterprise value for decades, promising to turn theoretical savings into recovered capital that hits the bottom line.