Tech company builds contract and procurement analysis platform on MongoDB Enterprise Advanced to help banks eliminate complexity and manual processes.
Their Challenge
When Xlrt’s customer—a global bank—needed to pull finance forecasts quickly, data silos, and inconsistent manual processes slowed it down.
Our Solution
Xlrt built a flexible platform using MongoDB Enterprise Advanced, MongoDB Atlas, and MongoDB Vector Search. The bank uses it on-premises.
Outcome
The bank is 60% more efficient with faster document analyses supporting procurement processes, and Xlrt is continuing to improve the platform.
Industry
Computer Software & Technology
Financial Services
Product
MongoDB Enterprise Advanced
MongoDB Atlas
MongoDB Atlas Vector Search
Use Case
Analytics
Content Management
THEIR CHALLENGE
Data silos disrupted forecasts
Xlrt is a fintech software company delivering intelligent document processing. It aims to enable financial services companies to make better decisions based on a holistic view of each customer’s financial health. The company uses artificial intelligence (AI) to process unstructured data and turn it into valuable insights for its customers.
Xlrt works with a global multinational bank with more than 40 million customers and operations in around 60 countries. The bank’s reliance on time-consuming, manual processes to check contracts and track procurement workflows was risking its ability to respond quickly to changing market conditions.
When the US imposed tariffs on global markets in early 2025, the bank needed to generate a three-month cash flow forecast just as quickly. However, data was scattered across systems and continents, and each market had different tariff impacts and currencies, making it difficult to consolidate consistent data for forecasting.
The bank turned to Xlrt to develop a contract and procurement analysis platform and create a single source of truth. It needed to be able to handle multiple currencies, consolidate reports from different regions, and simplify tracking and comparing forecast iterations. It also wanted to speed up vendor performance monitoring and contract renegotiations, which were adding further complexity and increasing the risks of manual errors.
“MongoDB was the natural first choice. Our product handles a large volume of confidential customer information, making reliability and robust performance non-negotiable.”
Raj Mukherjee Co-founder and CEO, Xlrt
OUR SOLUTION
AI-powered contract analysis
Xlrt decided to build an AI-driven contract and procurement analysis platform, called ContractUS™. It had already developed a proven AI-driven document analysis engine for financial statements, so used this as a foundation and enhanced it to handle contract and procurement documents. The company needed a database that could handle vast volumes of unstructured data quickly and that could be deployed either on-premises or in the cloud. This is particularly important for the financial services sector, where many banks deploy on-premises to retain control over their infrastructure and data sovereignty. However, Xlrt also needs to cater to customers who prefer managed cloud services.
It chose MongoDB Enterprise Advanced for the bank’s instance of ContractUS™, and offers the platform on MongoDB Atlas for other customers. The database provides online transaction processing (OLTP) for managing and executing high volumes of transactions in real-time, which supports procurement, compliance, and corporate use cases.
“MongoDB was the natural first choice. Our product handles a large volume of confidential customer information, making reliability and robust performance non-negotiable,” said Raj Mukherjee, Co-founder and CEO of Xlrt. “Additionally, many banks are already MongoDB customers, which means established operational processes and data center integrations would already be in place. From a technical perspective, the nature of the data we process is largely unstructured, making a document database like MongoDB the most suitable option.”
ContractUS™ connects to existing systems through non-invasive API integrations. It currently ingests feeds from five different systems across seven countries, each with their own currency, and can handle English, Spanish, and Simplified Chinese. Its cloud-first, cloud-agnostic architecture supports rapid deployment and scalability, accommodating newer document types and organizational needs. A user-friendly interface enables easy document review and processing while maintaining a complete audit trail of user actions for accountability.
The bank uses ContractUS™ to analyze procurement contracts and identify critical tariff clauses. It automates the process by analyzing purchase orders, invoices, credit notes, and financial plans to deliver precise cash flow projects for every business function. For example, the bank’s team used the platform to calculate payable aging, which is a report that summarizes bills and invoices owed by each customer, broken down by vendor and due date. This revealed more than $17.75 million in delayed obligations, which were primarily related to one division, allowing the finance team to understand and address the root cause of systemic delays.
While this addresses the bank’s challenges, Xlrt is continuing to evolve ContractUS™ for other customers. It plans to use knowledge graphs to visualize the relationship between different entities, such as statements of work, vendors, and obligations, while MongoDB Atlas Vector Search will support semantic searches on data. Customers will be able to rapidly find relevant data and use large language models (LLMs) to summarize and generate reports to speed up decision-making while improving productivity.
Process Flow Diagram: High-level overview of the bank’s procurement workflow, illustrating data sources, document processing steps, and real-time reporting outputs across key business units.
“Leveraging MongoDB technology, we provide our clients the flexibility to choose the platform that best suits their requirements. The results speak for themselves: greater visibility, better decisions, and faster outcomes.”
Raj Mukherjee Co-founder and CEO, Xlrt
OUTCOME
75% faster financial planning
With MongoDB Enterprise Advanced powering ContractUS™, Xlrt has enhanced the bank’s procurement process significantly, which is particularly beneficial with a volatile global market.
As Mukherjee enthused, "Thanks to MongoDB, ContractUS™ can provide a 360-degree view of all vendors and suppliers in 75% less time and 60% more efficiency. This comprehensive view includes patterns, trends, and risks.”
Representative Dashboard: Unified view of fragmented cost data, highlighting month-on-month trends, 180+ day ageing risks, and the transformation of complex, siloed data into structured, actionable insights.
The platform has reduced the effort required for financial planning, from collation of data points to cash flow forecasting. Processes that once took 15 days now take just three, which is 75% faster and more cost efficient.
AI-driven analysis and standardized processes have increased accuracy and reliability, which helps the bank make more informed decisions. The platform also enhances risk analysis, which simplifies enforcing compliance and speeds up identifying geopolitical threats.
"With ContractUS™, we can equip our clients with a next-generation solution that turns procurement from a cost center into a strategic advantage. Leveraging MongoDB technology—be it MongoDB Atlas for a fully managed cloud-based experience or MongoDB Enterprise Advanced for on-premises needs—we provide our clients the flexibility to choose the platform that best suits their requirements,” explained Mukherjee. “The results speak for themselves: greater visibility, better decisions, and faster outcomes!"
And as it looks to the future, MongoDB is firmly at the center of Xlrt’s plans. With a powerful AI-enabled data platform at its core, the company is working on broadening the scope of the platform to address complex procurement challenges and automate more of the time-consuming manual processes at the heart of its customers’ pain points.
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