- Rivvun AI Raises US$7.55 Million to Recover US$2 Trillion in Enterprise Revenue Leakage
Rivvun AI Inc. has raised US$7.55 million in an oversubscribed seed funding round to deploy an autonomous artificial intelligence execution layer designed to help enterprises recover spend and revenue leakage.
The seed round was co-led by Sitara Capital and 3one4 Capital, and will support the company’s plan to address what it describes as a major structural gap in enterprise financial execution.
According to Rivvun AI, more than US$2 trillion in enterprise value fails to move from obligation to settlement each year because companies lack systems built to identify, enforce and recover money owed under commercial agreements.
The company says the problem is not primarily fraud or poor contracting, but the operational gap between what has been contractually committed and what enterprise systems are able to collect.
Citing McKinsey research, Rivvun AI said enterprise procurement functions lose up to one-third of planned savings during execution, while an additional 3.00 percent to 4.00 percent of total external spend is lost to transaction inefficiency and noncompliance.
Across Fortune 2000 revenues, the company argues, these execution gaps compound into more than US$2 trillion in value that never reaches the bottom line.
Rivvun AI was founded by former Icertis senior executives Anand Veerkar and Niranjan Umarane, who spent the past decade helping scale Icertis to more than US$350 million in annual recurring revenue.
During their time at Icertis, the founders worked on platforms governing some of the world’s largest commercial portfolios. According to the company, they repeatedly observed the same issue across industries: commercial terms were carefully negotiated, but financial execution against those terms remained weak.
In many cases, money owed under negotiated agreements went uncollected not because companies chose to ignore it, but because no system within the enterprise technology stack was designed specifically to recover it.
They are joined by serial entrepreneur Patrick Linton, who brings experience in scaling global operations for enterprise software companies.
Rivvun AI says its platform is designed to sit across existing enterprise systems rather than replace them.
The company argues that enterprise resource planning systems record transactions, customer relationship management tools track relationships and procurement platforms manage approvals, but none of these systems fully enforce financial outcomes.
Its autonomous AI execution layer connects to existing ERP, CRM and procurement platforms, interprets commercial obligations, identifies what has not settled as agreed and initiates recovery at the transaction level.
The company says this approach avoids the need for enterprises to rip out existing systems or introduce a new system of record.
The platform is powered by two agentic AI families.
The first, Spend Assurance, focuses on the buy side. It is designed to recover supplier rebates, pricing commitments and procurement obligations that have not been enforced.
The second, Margin Defense, focuses on the sell side. It targets customer settlement variances, trade term discrepancies and revenue that leaves the profit and loss account without authorisation.
Rivvun AI says its model is built “vertical-first” because enterprise leakage differs significantly by industry.
For example, chargeback mechanics in pharmaceuticals, including group purchasing organisation compliance and government pricing obligations, differ from settlement gaps in banking or trade-term failures in consumer packaged goods and retail.
The company said generic AI tools are unlikely to solve such sector-specific problems because leakage patterns vary across industries.
Rivvun AI therefore deploys vertical-specific agent logic tailored to precise failure patterns in sectors including pharmaceuticals, healthcare, banking, consumer packaged goods, retail and industrials.
Anand Veerkar, Chief Executive Officer and Co-Founder of Rivvun AI, said the enterprise market needs AI that produces measurable financial outcomes rather than broad productivity claims.
“The enterprise has spent years being told AI will transform how it operates. 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,” he said.
Sachin Bhanot, Managing Partner at Sitara Capital, said the investment case for Rivvun AI is tied directly to measurable value creation for chief financial officers.
“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. 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,” he said.
Anurag Ramdasan, Partner at 3one4 Capital, said Rivvun AI reflects strong founder-market fit in the vertical AI category.
“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, which is very critical for enterprise AI adoption,” he said.
He added that the founders’ deep sector expertise gives the company a level of operational discipline that is critical for enterprise AI adoption.
The launch comes at a time when enterprise AI investment is shifting from broad automation narratives toward tools that can prove direct financial return.
For large companies, the next phase of AI adoption is likely to be judged less by experimentation and more by measurable impact on cost savings, revenue recovery, margin protection and working capital efficiency.
Rivvun AI’s proposition is therefore clear: AI should not only help enterprises work faster, but help them recover money they are already owed.
If successful, the company could occupy a growing niche in enterprise technology where contract intelligence, procurement assurance, revenue operations and financial recovery meet.
The wider message for large enterprises is equally direct.
In an environment of margin pressure, complex supply chains and tighter financial discipline, value leakage is no longer a back-office issue.
It is a boardroom problem.
Rivvun AI is betting that autonomous AI can close the gap between what companies negotiate and what they actually collect.
