Oro Labs Raises $100M to Overhaul Enterprise Procurement with AI

Oro Labs, a Silicon Valley-based procurement automation platform, has closed a $100 million Series B funding round at a $1 billion valuation, marking the company's entry into unicorn territory as enterprises accelerate adoption of AI-powered purchasing systems. The round was led by TCV, the growth equity firm whose portfolio includes Netflix, Spotify, and Airbnb, with participation from existing investors including PayPal Ventures and Underscore VC.

The financing arrives at a pivotal moment for enterprise software, as companies grapple with legacy procurement systems that often require dozens of manual touchpoints to complete a single purchase order. Oro Labs' platform promises to collapse that timeline from days or weeks to minutes through what the company calls "agentic orchestration"—autonomous AI agents that can navigate complex approval workflows, negotiate with suppliers, and execute purchases with minimal human intervention.

CEO and co-founder Yoav Kutner, who previously built OroCommerce into a leading B2B e-commerce platform before its acquisition, founded Oro Labs in 2021 to address what he saw as a decade-long stagnation in procurement technology. "Most Fortune 500 companies are still running procurement on systems designed in the 1990s," Kutner said in a statement. "We're not just digitizing paper forms—we're fundamentally rethinking how AI can orchestrate the entire procurement lifecycle."

The fresh capital will fund expansion of Oro Labs' AI agent capabilities, including multilingual support for global procurement operations and deeper integrations with enterprise resource planning (ERP) systems from SAP, Oracle, and Microsoft Dynamics. The company also plans to triple its workforce from 120 to more than 350 employees by year-end 2026, with significant hiring in engineering and customer success roles.

The concept of "agentic AI"—autonomous software agents that can perceive their environment, make decisions, and take action—has emerged as the enterprise software industry's next frontier. Unlike traditional automation tools that follow rigid if-then rules, agentic systems leverage large language models and machine learning to adapt to novel situations, interpret unstructured data, and execute complex multi-step workflows.

In procurement specifically, this translates to AI agents that can read a purchase requisition in natural language, identify the appropriate suppliers based on historical performance and current inventory levels, negotiate pricing within pre-approved parameters, route approvals through the correct chain of command, and generate purchase orders—all without a procurement officer lifting a finger.

The market opportunity is substantial. Global enterprise spending on procurement software reached $7.2 billion in 2024 and is projected to grow at a compound annual rate of 11.3% through 2030, according to research firm Gartner. Yet procurement remains one of the least digitized functions in large corporations, with an estimated 60% of purchase orders still requiring manual data entry at some point in the workflow.

That inefficiency carries real costs. A 2024 study by consulting firm Deloitte found that manual procurement processes add an average of 12 days to requisition-to-order cycle times and increase error rates by 23% compared to fully automated systems. For a Fortune 500 company processing tens of thousands of purchase orders annually, those delays and mistakes can translate into millions in lost productivity and supplier relationship strain.

At its core, Oro Labs' system deploys specialized AI agents for discrete procurement functions—one agent handles supplier discovery and qualification, another manages approval routing, a third negotiates pricing and terms, and so forth. These agents communicate through a central orchestration layer that ensures handoffs happen seamlessly and business rules are enforced consistently.

The platform integrates with existing enterprise systems via API connections, pulling data from ERP systems, contract management databases, and supplier relationship management tools. This allows Oro Labs to layer intelligent automation on top of legacy infrastructure without requiring companies to rip out and replace their core systems—a crucial advantage in winning over risk-averse enterprise IT departments.

Early customers report dramatic improvements in procurement velocity. One Fortune 100 manufacturing client reduced average purchase order processing time from 14 days to under 3 hours, while a global pharmaceutical company cut procurement administrative costs by 37% within six months of deployment. The platform also provides real-time visibility into procurement spending and supplier performance through AI-generated dashboards and alerts.

Source: Oro Labs customer case studies, Fortune 100 manufacturing and pharmaceutical clients, 2024

A key differentiator for Oro Labs is its conversational interface, which allows employees to initiate procurement requests in plain English rather than navigating byzantine form systems. A marketing manager can simply type "I need 500 branded water bottles for our Q2 sales conference in Chicago" and the AI agents will automatically identify qualified suppliers, obtain quotes, route the requisition for budget approval, and place the order—providing status updates via email or Slack throughout the process.

For TCV, the investment represents a bet that agentic AI will fundamentally reshape how large enterprises operate across functions—not just procurement, but also IT service management, human resources, and finance. The firm has been actively building positions in AI-enabled enterprise software companies over the past 18 months, including recent investments in workflow automation platform Tonkean and supply chain visibility startup project44.

"We're at an inflection point where AI has moved from experimentation to mission-critical deployment," said David Yuan, general partner at TCV, who will join Oro Labs' board as part of the investment. "Oro Labs is one of the first companies we've seen that's successfully commercializing agentic orchestration at enterprise scale. Their customers aren't running pilots—they're processing billions of dollars in procurement spend through the platform."

Yuan pointed to Oro Labs' retention metrics as a key factor in TCV's decision to lead the round. The company reports a net revenue retention rate exceeding 140%, meaning existing customers are expanding their usage and spending significantly faster than the rate of any customer churn. That expansion is driven primarily by customers rolling out the platform to additional business units and geographies after successful initial deployments.

The company has also demonstrated an ability to move upmarket rapidly. When Oro Labs launched commercially in late 2022, its average contract value was approximately $150,000 annually. Today, that figure exceeds $1.2 million, with several customers having committed to multi-year contracts worth more than $10 million each.

TCV's involvement provides Oro Labs with more than just capital. The firm brings deep relationships across Fortune 500 procurement and IT organizations, as well as operational expertise in scaling enterprise software businesses through rapid growth phases. Several TCV portfolio companies have successfully navigated the journey from Series B unicorn to IPO, including recent public market debuts by Toast, Rent the Runway, and Samsara.

The continued participation of PayPal Ventures signals potential strategic alignment beyond financial returns. PayPal has been aggressively expanding its B2B payments capabilities, including its 2023 acquisition of invoice automation platform Regnology and ongoing development of working capital financing products for enterprise buyers and suppliers.

Oro Labs' platform could serve as a natural distribution channel for PayPal's B2B payment products, embedding financing and payment options directly into the procurement workflow at the point of purchase. While neither company has announced a formal commercial partnership, industry observers note that such integration would create compelling value for both parties—giving PayPal access to high-intent enterprise purchasing moments while offering Oro Labs customers seamless payment and financing capabilities.

Oro Labs enters its next growth phase facing competition from multiple directions. At the high end of the market, established procurement software vendors including SAP Ariba, Coupa Software, and Ivalua have begun layering AI capabilities onto their existing platforms. These incumbents benefit from deep customer relationships and embedded positions within enterprise IT stacks, but also face the technical challenge of retrofitting decades-old codebases with modern AI capabilities.

Meanwhile, a cohort of AI-native procurement startups has emerged alongside Oro Labs, each pursuing slightly different angles on the same fundamental opportunity. Zip, which raised a $190 million Series C at a $1.5 billion valuation in 2023, focuses on intake and orchestration for IT purchasing specifically. Fairmarkit applies AI to tail spend management and supplier discovery. Negotiatus uses machine learning to identify cost savings opportunities in existing supplier contracts.

What distinguishes Oro Labs, according to customers and industry analysts, is the breadth of its agentic orchestration capabilities across the full procurement lifecycle—from requisition intake through contract management and supplier performance tracking. Competitors tend to excel in one or two specific workflow stages while leaving others to manual processes or integration with third-party tools.

"Most procurement software still thinks in terms of automating individual tasks," said Jason Busch, managing director at procurement research firm Spend Matters. "Oro Labs is one of the few vendors architecting for end-to-end agent-based orchestration, where AI handles not just discrete steps but the entire flow of work across systems and stakeholders. That's genuinely differentiated in a crowded market."

Oro Labs has achieved particularly strong traction in manufacturing, life sciences, and professional services verticals—industries characterized by complex, heavily regulated procurement processes and high volumes of both direct materials purchasing and indirect spend. The company has invested in industry-specific AI models trained on procurement data from these sectors, allowing its agents to better understand context-specific requirements around compliance, quality assurance, and supplier qualification.

That vertical specialization creates defensibility as the company scales. Once an Oro Labs customer has integrated the platform with industry-specific ERP systems, supplier networks, and compliance frameworks, the switching costs to a competitor become prohibitively high—even if that competitor offers nominally superior features in isolated areas.

With Series B capital in hand, Oro Labs plans to accelerate international expansion beyond its current base of predominantly North American customers. The company has already established a European subsidiary in Amsterdam and is targeting initial customer wins in Germany, France, and the United Kingdom—markets where procurement digitization lags the United States by an estimated three to five years but where demand is growing rapidly.

International expansion presents both opportunities and challenges. European data privacy regulations, particularly GDPR, impose strict requirements on how AI systems process personal and business data. Oro Labs has invested heavily in privacy-preserving AI techniques and on-premises deployment options to address these concerns, but regulatory compliance will remain an ongoing focus as the company enters new jurisdictions.

The company is also investing in what it calls the "Oro Supplier Network"—a bilateral marketplace connecting enterprise buyers using the Oro Labs platform with suppliers who have integrated their own systems to receive and respond to purchase orders through the same AI-powered infrastructure. This network effect could prove critical to long-term competitive positioning: as more buyers and suppliers join the network, the value of the platform increases for all participants through faster transaction processing and better price discovery.

Early signs suggest the network is gaining momentum. More than 2,800 suppliers across 47 countries have completed technical integration with Oro Labs' systems, and the company reports that purchase orders routed through bilateral AI orchestration settle 68% faster on average than orders sent via traditional EDI or email channels.

"The Holy Grail in B2B procurement is true orchestration across the buyer-supplier boundary," said Kutner. "When both sides of a transaction have intelligent agents working together, the efficiency gains are multiplicative rather than additive. That's where we're ultimately headed."

As with any enterprise AI deployment, Oro Labs faces persistent questions around security, compliance, and accountability. When an autonomous agent commits a company to a multi-million-dollar purchase order, who is legally responsible if that agent makes an error or violates company policy? How do enterprises audit AI decision-making for bias or conflicts of interest? What happens when an agent negotiates unfavorable terms because of adversarial manipulation by a sophisticated supplier?

Oro Labs addresses these concerns through a multi-layered governance framework. All agent actions occur within guardrails defined by procurement policies that customers configure during initial implementation—maximum order values, approved supplier lists, compliance requirements, and so forth. Agents cannot override these constraints, even if doing so would theoretically result in cost savings or efficiency gains.

Source: Oro Labs governance and compliance framework documentation, 2025

The platform also implements confidence scoring: agents assign a probability estimate to each decision they make, and low-confidence decisions automatically escalate to human reviewers for validation. This hybrid approach allows enterprises to capture the efficiency benefits of automation for routine transactions while maintaining human oversight for edge cases and high-stakes purchases.

The rapid ascent of Oro Labs and its peers raises a provocative question about the future economics of enterprise software: if AI agents can automate most of the work that procurement professionals currently perform, what happens to the value equation between software vendors and their customers?

Traditional enterprise software pricing is based on named users or transaction volumes—the more people using the system or the more activity flowing through it, the more the customer pays. But in an agentic model where one AI orchestration layer might replace the work of dozens of procurement analysts, the per-unit economics shift dramatically. Customers complete far more transactions with far fewer human users, potentially reducing their software spend under conventional pricing models.

Oro Labs and other AI-native vendors are experimenting with alternative pricing structures to capture value commensurate with the automation they provide. Options include outcome-based pricing (the vendor takes a percentage of documented cost savings), consumption-based pricing (charging based on volume of spend flowing through the platform rather than number of users), and hybrid models that combine elements of both.

"We're moving away from seat-based pricing because it doesn't align with the value we deliver," Kutner explained. "If we can help a customer reduce their procurement team from 50 people to 10 through automation, we shouldn't be penalized with lower revenue. Our pricing needs to reflect business outcomes, not headcount."

The shift toward outcome-based software pricing could have far-reaching implications for the entire enterprise software industry. If successful, it would represent a fundamental change in how technology companies monetize automation—prioritizing demonstrated business impact over usage metrics. But it also introduces risk: if customers don't achieve the expected results, vendors may struggle to command premium pricing regardless of the sophistication of their technology.

While Oro Labs remains focused on procurement for now, Kutner and his team see agentic orchestration as applicable across virtually every operational function in the enterprise. The same fundamental capabilities—understanding unstructured requests, routing workflows through complex approval hierarchies, negotiating with external parties, and executing transactions—translate readily to IT service management, HR operations, legal contract review, and finance processes.

The company has not announced specific plans to expand beyond procurement, but its technology architecture is designed with horizontal applicability in mind. The agent orchestration engine, natural language interface, and governance framework are largely function-agnostic, requiring primarily domain-specific training data and business logic to adapt to new use cases.

That architectural flexibility positions Oro Labs as a potential platform company—one that could eventually offer a suite of agentic orchestration products across multiple enterprise functions, much as Salesforce evolved from a sales CRM into a multi-cloud enterprise platform. Whether the company pursues that strategy organically or through acquisition of point solutions in adjacent categories remains to be seen.

For now, though, the focus is squarely on scaling the core procurement business. With 40-50% of Fortune 500 companies still running procurement on legacy systems built before the smartphone era, Oro Labs sees years of runway in its initial market before expansion becomes necessary. And with $100 million in new capital and a valuation that positions it favorably for an eventual IPO, the company has the resources to pursue that opportunity aggressively.