Our Mission

We enable you to monitor threats and prevent supplier
disruptions, automatically.

Prevent Supplier

Your suppliers can reduce production disruptions by 60% by addressing SRS risk prevention actions. That’s proven by our vast database of millions of threats and mitigation actions.

We founded SRS in Silicon Valley in 2007 with a mission to lift entire supply chains to exceptional resilience standards through proactive risk prevention. We were the first software company to provide third-party supply chain risk management as a cloud-based service.

SRS remains the only software to measurably prevent supply chain disruptions.

Prevention Case Study

A Fortune 50 manufacturer asked whether SRS could improve their supplier chain risk program. They had a traditional program:

  • data collection of site locations and BCP
  • threat monitoring
  • contingency planning
  • mitigation through buffer stock and multi-sourcing.

But they were missing the most essential risk tool: Prevention.


Suppliers Addressed Risks

The customer mapped, assessed, and monitored their global multi-tier supply chain nodes.

Suppliers soon understood their risks and took risk prevention actions to make production sites resilient, ultimately cutting the percentage of High Risk suppliers by more than half.

Massive Time Savings

Automating proactive risk prevention and digital response saved them massive efforts.

Fewer Disruptions

Disruptions fell as supplier put in place specific protections at their production sites.

Our Founders

Patrick Brennan
CEO & Founder

Patrick is a technology entrepreneur based
in Silicon Valley and a leader in the field of cloud predictive risk technology. Patrick founded Supply Risk Solutions in 2007. 

Patrick earned an MBA with Honors from
the University of Chicago, held
management positions at Oracle Corp and Accenture, and was awarded patents in scaling predictive risk prevention across unlimited suppliers and partners (US
Patents 8,515,804 and 10,853,754).

Kate Novykova
Chief Data Scientist

Kate is a trained data scientist who
optimizes the PredictLens™ engine that powers SRS Machine Learning models.

Kate earned a Masters in Computer
Science, holds multiple Microsoft and
Oracle certifications, and brings analytics experience from several software startups. Kate joined us in 2007.