Simfoni delivers spend analytics and automation solutions, using AI to streamline procurement processes for global enterprises. Their platform helps businesses optimise purchasing, reduce costs, and modernise procurement workflows.
Challenge
Despite their expertise in AI and automation, Simfoni still relied on manual, resource-heavy processes via virtual machines to manage cloud workflows. This created inefficiencies, slowed product development, and required the team to focus on infrastructure maintenance rather than innovation.
They needed to replace these legacy processes with scalable, automated workflows that would improve data ingestion, categorisation, and enrichment – ultimately enabling their team to prioritise customer-focused product development.
Solution
Firemind developed two proof-of-concept solutions to automate data workflows and modernise cloud-based processes. The first PoC focused on product enrichment through machine learning. Customer data was ingested via SFTP or Amazon S3, grouped by folder prefixes, and converted to Parquet format for more efficient querying. An AWS Lambda event triggered classification scoring, storing metadata in Amazon DynamoDB and enriched datasets in PostgreSQL for use in BI platforms.
The second PoC introduced a data ingestion and transformation pipeline. AWS Transfer fed raw files into Amazon S3, with Lambda functions converting them to Parquet. Data was then processed using AWS Glue DataBrew or Amazon SageMaker for cleaning, modelling, and deployment – before being stored in Amazon S3 for future use. These combined
Services used
- PostgreSQL
- AWS Lambda
- Amazon DynamoDB
- Amazon S3
The Results
- Fully automated, scalable workflows replaced manual processes
- Significant cost savings from reduced manual effort
- Faster time-to-insight with enriched, query-optimised data
- Modern cloud architecture supporting future AI/ML growth
- Freed up internal resources to focus on product innovation
