Vijay Raina stands as a distinguished authority in the enterprise SaaS landscape, bringing years of expertise in software architecture and the evolution of digital financial tools. As the industry pivots toward autonomous systems, his insights into how large-scale platforms transition from static databases to active intelligence layers have become invaluable for both developers and venture capitalists. In this conversation, we explore the fundamental shift in enterprise resource planning through the lens of Rillet’s recent $1 billion valuation. We delve into the concept of agentic operating layers, the architectural departure from legacy systems like Oracle and SAP, and the tangible impact of AI on the scale and efficiency of modern finance teams.
Rillet recently reached a $1 billion valuation after its third funding round in a year. How does this aggressive capital infusion reflect the current shift in how enterprises view their financial infrastructure?
This level of funding—specifically a $100 million Series C led by ICONIQ—signals a massive loss of patience with the “system of record” model that has dominated the last twenty years. Investors and enterprises alike are realizing that simply storing data after it has already happened is no longer sufficient in a market that demands instant visibility. By bringing the total funding to more than $200 million in such a short window, the market is betting on Rillet’s ability to replace aging giants like NetSuite and Microsoft Great Plains. We are seeing a fundamental transition where the ERP is no longer just a digital filing cabinet, but a living harness where structured data flows through native integrations into a real-time general ledger. This capital is the fuel for a race to move financial operations from a monthly batch process to a continuous, 24/7 stream of activity.
Rillet describes its platform as an “agentic operating layer” rather than just another accounting tool. Could you elaborate on the architectural significance of having AI agents work directly within the general ledger?
The brilliance here lies in vertical integration; while many companies try to “bolt on” AI to existing systems, Rillet has built the intelligence into the ledger itself. Traditionally, the real work of finance happened in external spreadsheets because legacy ERPs were never designed for the complexity of automated agents. By having agents and humans share the same financial truth and accounting policies in one environment, the system maintains a complete audit trail that is often lost when data is shuffled between disparate tools. This architecture allows AI to perform increasingly complex financial tasks while the human team retains the ultimate approval authority. It creates a seamless loop where the software doesn’t just watch the money—it actively helps manage the movement and categorization of it with full context.
We see Rillet expanding rapidly from tech and AI startups into sectors like biotech, healthcare, and logistics. What challenges do legacy giants like Oracle or SAP face when competing with this new breed of AI-native platforms?
Legacy giants are currently struggling with the weight of their own technical debt, as their platforms were built in an era where data was static and silos were the norm. When a company doubles its new ARR in just three months, as Rillet has done, it proves that there is an urgent hunger for systems that don’t require massive “implementation” periods or endless manual entry. In sectors like biotech and healthcare, where precision is non-negotiable, the ability to close books continuously rather than waiting weeks after the month-end is a competitive necessity. These legacy systems were designed for a world of human data entry, whereas Rillet’s 600-plus customers are looking for a platform where the software itself acts as the primary operator. It is incredibly difficult for a legacy provider to pivot from being a passive database to an active agentic layer without a complete, ground-up rebuild.
The idea of a multi-billion dollar business operating with a finance team a tenth of the traditional size is striking. How does this collaboration between humans and AI change the daily reality for finance professionals?
We are seeing a radical shift in the “math” of human labor within finance, exemplified by companies like Mercor that scale past $2 billion in ARR with a team of only three people. The daily grind of a finance professional is moving away from the sensory exhaustion of manual reconciliation and toward high-level strategy and oversight. Instead of spending hours hunting down discrepancies in a ledger, these professionals now act as the final check in an automated workflow, exercising approval authority over work already completed by agents. This creates a more rewarding environment where the focus is on analyzing the business’s future rather than documenting its past. The result is a finance function that feels more like a command center than a back-office processing unit, operating with a level of agility that was previously impossible.
Rillet’s alliance with Ernst & Young and its partnerships with over half of the top 20 CPA firms suggest a deep integration into the professional services ecosystem. Why is this buy-in from traditional auditors so critical for an AI-first company?
Trust is the ultimate currency in finance, and for an AI-native platform to succeed, it must be “auditable by design.” By partnering with firms listed in the Accounting Today top 20, Rillet is ensuring that the world’s most rigorous gatekeepers are comfortable with how their agents process data. These alliances prove that the “system of context” Rillet is building actually strengthens the audit trail rather than obscuring it behind a “black box” of AI logic. When an auditor can see exactly how an agent applied a specific accounting policy within the ledger, the friction of the annual audit begins to evaporate. This professional buy-in is the bridge that allows Rillet to move from being a “disruptive startup” to being the foundational infrastructure for the next generation of global enterprises.
What is your forecast for the evolution of the ERP market?
Within the next two to three years, the very concept of a “monthly close” will become an artifact of the past, as every serious enterprise moves toward real-time, agentic financial operations. We will see a massive consolidation of the finance stack, where the messy middle-ware of spreadsheets and “bolt-on” AI tools is swallowed by vertically integrated platforms that own the ledger. The divide between “tech companies” and “traditional companies” will disappear in this context, as even the most established firms in logistics or healthcare will be forced to adopt agentic layers to keep pace with the speed of global trade. Ultimately, the ERP will no longer be seen as a cost center for compliance, but as the primary engine for real-time strategic decision-making across the entire organization.
