A cloud-native deployment is optimal for funds using modern data platforms like Snowflake or Databricks and seeking elastic, API-first reporting. The workflow orchestrates serverless functions (AWS Lambda, Azure Functions) to trigger on a schedule (e.g., quarter-end), pulling normalized valuation and performance data from a cloud data warehouse. A templating engine (e.g., Jinja2 with WeasyPrint or a headless Chromium instance) binds this data to branded HTML/PDF report structures. Secure distribution is handled via pre-signed S3/Blob Storage URLs, with access logs and audit trails integrated into the fund's IAM and SIEM. The primary operational upside is the elimination of manual data wrangling and report assembly, turning a multi-day process into a few hours of automated runtime, while scaling effortlessly with portfolio growth. Implementation requires building idempotent data pipelines, embedding approval gates for final numbers, and establishing rollback procedures for any pipeline failures.