Sprinklr Gains Runtime Visibility into Application-Layer Threats
One of the differentiators for me was Upwind’s ability to look at things across the full stack, including the application layer, and build those stories."
About Sprinklr
Founded in 2009, Sprinklr is the AI-native platform for Unified Customer Experience Management, helping large organizations unify teams, tools, and data across customer-facing functions. Today, Sprinklr empowers enterprises to engage, listen, and respond across 30+ digital channels from one platform.
As a global, publicly traded company serving top enterprises, Sprinklr’s product security team is responsible for protecting a complex, rapidly evolving software environment.
Sprinklr uses Upwind to understand cloud, application, and API activity at runtime, detect application-layer threats, and turn disconnected signals into clearer stories for investigation.
Challenges
- Keeping pace with rapid development: As engineering velocity increased, Sprinklr’s product security team needed deeper runtime visibility to keep security aligned with how applications were changing in production.
- Limited visibility into runtime behavior: Their existing approach provided posture visibility, but needed deeper context into how applications were actually running, communicating, and behaving at runtime.
- Detecting application-layer and API threats: The team needed visibility into API activity and application-layer attacks, not just cloud, network, or file-level activity.
- Managing alert complexity: As runtime detection surfaced more signals, Sprinklr needed a way to connect alerts into a clear story for investigation.
- Understanding APIs and sensitive data flows: The team needed to inventory APIs across environments and understand where sensitive data, including PII, was moving between components and applications.
- Gaining visibility into AI adoption: As AI capabilities expanded, Sprinklr needed a way to understand what AI agents and capabilities existed across the environment before they could secure them.
Solutions
- Runtime visibility across applications: Shows how workloads and applications behave at runtime, helping the team validate what is actually happening in production.
- Application-layer threat detection: Detects threats at the application-layer, where cloud, network, and file-level tools can miss important context.
- API and sensitive data visibility: Inventories APIs across environments, shows how they are used, and identifies where sensitive data, including PII, moves between components.
- Correlated investigation stories: Connects related signals across the full stack into clearer investigation stories, helping the response team understand what happened, what was affected, and where to act faster.
- AI observability: Provides the visibility needed to understand what AI agents and AI capabilities exist across the environment, including how they run and behave, helping the team understand and secure AI adoption in context.
Upwind's pace of innovation was very impressive and that's what made me and everybody else feel comfortable."
Why Sprinklr Chose Upwind
Sprinklr’s product security team was looking for a partner that could help address the next layer of complexity by showing what was actually happening across applications and APIs at runtime. With eBPF-powered runtime visibility, Upwind surfaces application-layer activity, API behavior, and cross-stack signals that are difficult to capture with traditional cloud security approaches.
As development velocity increased, visibility into posture alone was not enough. The team needed to detect application-layer threats, understand API activity, and make sense of the growing volume of security signals generated across their environment.
Upwind stood out for its runtime visibility, application-layer detection, and ability to correlate signals into a clearer picture of exploitable risk. Rather than force teams to investigate individual alerts in isolation, Upwind connects activity across the stack for faster investigations and clearer next steps.
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