How AI is Revolutionizing Accounting with Digits and Google Cloud
Customer Company Size
Startup
Region
- America
Country
- United States
Product
- Digits Transaction Review
- Vertex AI Model Registry
- Vertex AI Pipelines
- Vertex AI Streaming Ingestion for Matching Engine
Tech Stack
- Google Cloud
- Vertex AI
- Kubernetes
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Productivity Improvements
- Digital Expertise
- Innovation Output
Technology Category
- Analytics & Modeling - Machine Learning
- Platform as a Service (PaaS) - Data Management Platforms
- Application Infrastructure & Middleware - API Integration & Management
Applicable Industries
- Software
- Finance & Insurance
Applicable Functions
- Business Operation
- Quality Assurance
Use Cases
- Predictive Maintenance
- Process Control & Optimization
- Remote Asset Management
Services
- Cloud Planning, Design & Implementation Services
- Software Design & Engineering Services
- System Integration
About The Customer
Digits is an AI accounting startup founded in 2018, focused on leveraging machine learning and cloud services to transform accounting workflows. The company aims to simplify and expedite accounting processes for businesses, enabling them to better understand and act on their financial status. Digits offers products like Digits Transaction Review, which uses machine learning to categorize and verify expense transactions, providing context for ledger entries. The startup is known for its innovative approach to integrating machine learning into accounting, making the entire pipeline faster and smarter. With a team of experts, including Hannes Hapke, a Google Cloud Champion Innovator, Digits is dedicated to revolutionizing the accounting industry by aligning teams, streamlining processes, and scaling models effectively.
The Challenge
The primary challenge faced by Digits, an AI accounting startup, was to efficiently scale its machine learning operations to serve paying customers. While the company had developed innovative machine learning models, the complexity of building scalable systems and MLOps processes was a significant hurdle. The team needed to manage and deploy models efficiently, handle infrastructure management, and streamline MLOps tasks without incurring high engineering overhead. Additionally, they required a solution that could support parallel processing, use of GPUs, and implementation of different MLOps processes, which their existing systems could not handle without significant engineering effort.
The Solution
Digits turned to Google Cloud's Vertex AI to overcome its challenges in scaling machine learning operations. By utilizing Vertex AI Model Registry, Digits streamlined the management and deployment of models, reducing the engineering effort required for introducing new models and scaling resources. This allowed the team to focus on building innovative ML models and products rather than infrastructure management. Vertex AI Pipelines further helped Digits enforce governance, troubleshooting, and MLOps tasks, standardizing models as they moved toward production. The platform facilitated deployment through a CI/CD system, ensuring compliance and efficiency. Additionally, Vertex AI's Streaming Ingestion for Matching Engine enabled real-time data updates, allowing Digits to deliver features and analysis promptly. This capability was crucial for products like Digits Boost, which automates manual quality control tasks, providing immediate feedback to customers.
Operational Impact
Quantitative Benefit
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