AI-Powered CRE Investment Platform

Challenge

Investment management in private CRE involves complex data processing, risk assessment, and reporting workflows. The client needed a solution to:

Automate manual document parsing and reduce reliance on time-intensive Excel workflows.
Integrate multiple data sources into a unified, scalable system.
Provide General Partners (GPs) with timely, accurate insights for decision-making.
Build a secure, cloud-native platform that could handle large data volumes while supporting seamless user interactions.

Solution we Delivered

The project was delivered as a Minimum Viable Product (MVP) within six months, focusing on automating workflows and optimizing data processing at both asset and portfolio levels.

Automated Document Parsing

AI-driven parsing of Excel files using Python and AWS SageMaker, with structured data stored in PostgreSQL.

Client-Facing Platform

Built with React for intuitive data visualization and interaction.

Seamless Data Interactions

Robust NestJS-based API enabling integration across systems.

Scalable Data Pipeline

AWS-powered infrastructure (S3, SQS, SNS, Lambda) supporting high-volume data handling.

AI-Driven Risk Assessment

Machine learning models for evaluating credit risks, market volatility, and geopolitical exposure.

Data Aggregation and Analysis

Advanced analytics tools providing actionable insights for GPs.

Results at MVP Stage

Processed 500,000 rows of client-submitted data and scaled to store up to 20 million records.
Supported 1,000 concurrent users on the React platform with minimal latency.
Positioned the client for growth with a scalable, secure, and data-driven solution.

Following the MVP launch, the platform is now in Version 1.1 development, expanding functionality to support a wider range of investment workflows and deliver greater value to CRE stakeholders.

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