Ramp Introduces AI Agents to Transform Financial Operations
NEW YORK, July 10, 2025 / PR Newswire / – Ramp, a leading financial operations platform, has unveiled its first artificial intelligence (AI) agents specifically designed for controllers. These agents automate the application of corporate expenditure policies, eliminate unauthorized spending, and prevent fraud. This launch marks the beginning of a series of robust AI-driven solutions Ramp plans to introduce throughout the year, which aim to minimize the manual workload of financial teams.
The Challenge of Manual Financial Tasks
Despite the increasing demand for financial teams to accomplish more with fewer resources, many functionalities remain tethered to manual processes. Research indicates that teams utilizing legacy platforms devote as much as 70% of their time to tasks such as expenses analysis, policy enforcement, and compliance audits. Consequently, reports have shown that 59% of finance professionals encounter multiple errors every month due to these extensive workload demands.
Revolutionizing Expense Management
Ramp’s AI agents for controllers directly address these challenges by automating redundant financial tasks. These agents operate independently to scrutinize expenses and enforce compliance with company policies effectively.
Intelligent Decision-Making with AI
Fueled by OpenAI’s advanced reasoning models, Ramp’s agents exhibit contextual and human-like reasoning capabilities. Unlike traditional automation that relies on simple rule-based logic, these agents proactively manage entire workflows. They apply comprehensive spending policies, immediately curtail violations, and continuously enhance spending directives. Initial users reported an impressive 99% accuracy rate in expenditure approvals1.
A Shift in Financial Oversight
According to Richard Gobea, Director of Finance at Quora, “Before utilizing Ramp agents, we manually reviewed 100% of our transactions. Now, Ramp agents perform the initial screening and flag only the transactions that truly warrant our review. Each decision made is linked to a transparent audit trail.”
Features of Ramp AI Agents
Powered by the Ramp AI platform, these agents automate numerous tasks, including:
- Approving low-risk expenses or providing justified recommendations for approvals
- Flagging suspicious receipts and invoices
- Resolving employee queries regarding spending policies
- Identifying trends related to fraud or excessive spending
- Proposing modifications to corporate spending policies based on user feedback
The Future Implications of AI in Finance
“Ramp agents possess in-depth knowledge of accounting rules and spending policies that employees may overlook,” explained Karim Atiyeh, Co-founder and CTO at Ramp. “Their ability to quickly access transaction details empowers them to act more decisively at every stage.”
With financial teams from leading AI companies like Hex, Sierra, and Quora already leveraging Ramp for improved efficiency and increased accuracy, the future looks promising. Ramp is committed to investing 50% of its budget in research and development to ensure that financial teams, regardless of their size, can harness the latest advancements in AI automation and cognitive reasoning.
Learn More About Ramp
For more information about Ramp’s innovative AI agents, visit: Ramp.com/intelligence.
About Ramp: Ramp is a comprehensive financial operations platform dedicated to helping businesses save time and money. Offering an all-in-one solution that combines payments, corporate cards, vendor management, supply chain oversight, travel booking, and automated accounting with integrated AI intelligence, Ramp maximizes the effectiveness of every dollar spent. With over 40,000 customers, ranging from family-owned farms to space startups, Ramp has helped save $10 billion and 27.5 million hours since its inception in 2019. Learn more at www.ramp.com.
1 Based on Ramp’s internal analysis conducted on July 1, 2025, assessing the percentage of transactions recommended for approval by Ramp agents that were also approved by human reviewers.