Ramp uses Microsoft Azure AI services and Azure AI Document Intelligence as the backbone of a custom OCR (optical character recognition) solution that automates key finance workflows. Here’s how it works in practice: - A user simply texts or uploads a receipt or invoice into Ramp. - Azure AI Document Intelligence automatically extracts the relevant data (such as merchant, date, amount, line items) from the document. - The system then categorizes and enriches that data, turning unstructured documents into structured information that can flow directly into Ramp’s expense management and bill-pay tools. This approach helps Ramp: - Eliminate repetitive manual data entry for receipts and multi-line invoices. - Maintain speed, accuracy, and security across its platform. - Offer a simple user experience that feels as easy as “swiping a card and texting the receipt,” with Ramp handling the rest behind the scenes. By building on Azure’s prebuilt models and services, Ramp’s lean engineering team was able to design, build, and deploy this custom OCR solution in under a week, and then scale it quickly to support both fast-growing customers and large enterprises.

Ramp’s use of Microsoft Azure AI has led to clear, measurable improvements across its finance workflows and engineering operations. Key outcomes include: - **30,000 hours of manual work saved every month** by automating receipt and invoice processing. - **5 million receipts and 400,000 invoices processed monthly**, with Azure AI handling extraction and classification. - Each automated receipt can save up to **15–60 seconds** of manual effort; at millions of transactions per month, this compounds into significant time savings and operational momentum for customers. On the engineering side, Ramp has extended its Azure footprint into DevOps: - Migrating DevOps processes to Azure and using **GitHub Actions** allows continuous integration pipelines to run in parallel, speeding up testing and reducing blockers. - **GitHub’s hosted runners** reduce the need to manage internal CI infrastructure, freeing up engineering capacity. - **GitHub Copilot** is embedded in daily workflows for almost every engineer, helping them ship code faster with more visibility and fewer interruptions. Overall, Azure AI and the broader Microsoft stack help Ramp’s customers spend less time chasing receipts and reconciling bills, and help Ramp’s own teams move faster while maintaining accuracy and control.

Ramp chose Microsoft Azure as its core AI and DevOps platform based on a mix of technical capabilities, support, and alignment with its growth plans. Key reasons for choosing Azure: - **AI strength and reliability**: Ramp views Azure as a strong option for AI-powered solutions, citing reliability, low latency, and cost benefits as important factors. - **Scalability for fast growth**: Azure’s ability to scale with Ramp’s transaction volumes and enterprise customer needs was critical. - **Prebuilt AI models**: Azure AI Document Intelligence provides prebuilt models that keep Ramp’s teams unblocked, so they can build and iterate quickly. - **Responsive support**: Ramp highlights the Microsoft Unified team’s fast, informed responses as a practical advantage when scaling and troubleshooting. How the partnership is evolving: - Ramp has expanded beyond OCR into **DevOps on Azure**, using GitHub Actions, hosted runners, and GitHub Copilot to streamline engineering workflows. - The company is deepening integrations with Microsoft products such as **Dynamics 365 Finance and Operations** and **Microsoft Entra**, supported by Azure’s security, performance, and reliability. - Looking ahead, Ramp plans to explore more **specialized AI models and agents** on Azure to support new use cases across expense, travel, procurement, and broader finance operations. For Ramp, Azure is not just infrastructure; it is a foundation that helps the company reimagine how finance teams work, while building trust with both fast-growing businesses and larger enterprises.