Case Study: Global SaaS Provider — Splunk ROI & Detection Tuning

Project Scope: License Optimization & High-Fidelity Use Case Engineering

Client Profile: High-Growth Fintech/SaaS

Timeline: Ongoing Managed Engineering (Monthly Retainer)

The Problem (The "Noise")

A rapidly scaling SaaS provider found their Splunk costs spiraling out of control, growing 2x faster than their revenue. Despite the high spend, the SOC was overwhelmed by "false positive fatigue," with over 4,000 alerts firing daily. Critical security signals were being missed because the engineers were buried in noise, and the business was considering a risky, full-scale migration to a cheaper SIEM just to save on licensing.

The Solution (The "Forge")

Signal Forge performed a Data Stream Inventory, identifying that 40% of their firewall and VPC flow logs provided zero security value. We implemented Schema-on-Demand and strategic filtering to move low-value/high-volume data to cold storage while retaining high-fidelity alerts in Splunk. Simultaneously, we replaced "signature-based" alerts with Behavioral Detections mapped to the client’s specific cloud architecture, focusing on lateral movement and credential theft.

The Impact (The "Efficiency")

• ROI: Reduced monthly Splunk ingest by 35%, resulting in a $180,000 annual license savings.
• Signal Quality: Reduced daily alert volume by 80% while increasing "True Positive" detection rates by 3x.
• Platform Stability: Normalized 15+ disparate data sources into the Splunk Common Information Model (CIM), enabling the use of Enterprise Security (ES) features that were previously broken.