Outcomes That Speak for Themselves

The Challenge

A top-10 investment bank was running overnight batch jobs to generate risk exposure reports, leaving trading desks operating on stale data. Regulatory pressure demanded intraday reporting within 15 minutes of any position change.

Our Approach

RHS architected a streaming data platform on Apache Kafka and Apache Flink, replacing the legacy batch pipeline. We built a custom risk aggregation engine and delivered a real-time dashboard consumed by 400+ traders globally.

The Challenge

A national healthcare network operating 47 hospitals was running critical patient management systems on aging on-premise infrastructure. Unplanned downtime was averaging 18 hours per year, with compliance gaps emerging under HIPAA audit.

Our Approach

RHS led a phased migration to a hybrid AWS/Azure architecture with active-active failover. We implemented zero-trust network segmentation, automated compliance controls, and a 24/7 observability stack with sub-60-second incident alerting.

The Challenge

A Fortune 500 retailer needed to build a real-time product recommendation engine ahead of peak season. Their internal team lacked ML engineering depth and a 12-month hiring timeline was not viable.

Our Approach

RHS placed a six-person team — two ML engineers, two backend engineers, a data engineer, and a tech lead — within 72 hours. The team integrated with the client's existing squads and delivered a production recommendation engine trained on 3 years of purchase history.

The Challenge

A federal agency processing over $4B in annual disbursements had a manual fraud review process that flagged less than 0.3% of transactions. Post-payment audits were recovering only a fraction of improper payments.

Our Approach

RHS built a machine learning fraud detection pipeline using gradient boosting and anomaly detection models trained on five years of transaction history. The system scores every transaction in real time before disbursement, with a human-in-the-loop review queue for high-risk cases.