We combine deep performance testing expertise with OctoPerf's cloud-based and on-premise load testing platform to ensure your applications meet business demands under real-world loads.
Our turnkey offering pairs our performance testing expertise with OctoPerf's load testing platform to help you validate that business-critical systems can handle production demands. We enable organizations to test applications under real conditions before users experience problems.
What we deliver
Production-Scale Load Testing
Test with production-level loads reaching millions of concurrent users using cloud resources or on-premise infrastructure.
Geographic load distribution
Distribute load from multiple geographic locations to mimic real-world traffic patterns and assess end-user experience across regions.
Complete infrastructure testing
Test your entire infrastructure including web servers, application servers, databases, and operating systems under realistic conditions.
Performance insights & analysis
Get real-time monitoring and in-depth analysis to identify bottlenecks, validate improvements, and optimize application performance.
CI/CD integration
Build continuous performance testing into any CI/CD pipeline to catch performance regressions before they reach production.
Flexible infrastructure options
Choose between cloud-based testing for scale or on-premise infrastructure for security and control. Add or remove load generators as needed.
OctoPerf platform capabilities
On-premise testing
Host your own load testing infrastructure with as many load generators as needed. Easy setup via Docker images with configurable resources to control costs.
Cloud integration
Use cloud resources for large-scale tests that mimic real traffic from multiple locations, providing accurate assessment of end-user experience.
Monitoring & APM integration
Monitor web servers, application servers, databases, and systems in real-time. Integrate metrics into your existing monitoring or observability stack.
External reporting
View OctoPerf load test data in real-time within your organization's monitoring solutions through live external reporting.
Scalable architecture
Scale up to 1 million concurrent users on cloud-based infrastructure with flexible licensing that maximizes efficiency and minimizes costs.
Tool-Agnostic Approach
Create automated load testing scripts using industry-proven methodologies, not vendor lock-in. Focus on outcomes, not tools.
Only 1% of companies call their generative AI rollouts mature and more than 80% say they aren't seeing earnings impact at enterprise level according to McKinsey.
Gartner projects 40% of agentic AI projects will be canceled by 2027. Experienced AI implementation partners help manufacturing navigate safety rules and regulatory demands - delivering production-ready systems that survive on plant floors where consumer AI shortcuts fail.
Sergey Ilin
VP of AI
What our experts say
Most manufacturers operate with fragmented data ecosystems including legacy MES and SCADA systems, siloed PLC data, and inconsistent sensor quality. The average organization utilizes only 23% of available data for AI applications.
Strategic data engineering partners with formal governance programs deliver 3.2 times higher success rates, building unified data platforms that precede meaningful AI deployment and Industry 4.0 transformation.
Lucas Hendrich
CTO
What our experts say
The US manufacturing sector could need 3.8 million new employees by 2033 yet without significant changes more than half these positions - 1.9 million jobs - could go unfilled.
92% of hiring managers expect challenges with 45% citing difficulty finding qualified candidates. Expert development partners accelerate digital transformation initiatives while internal teams focus on production operations rather than custom software development for emerging technologies.
Egor Goryachkin
CDO
What our experts say
By 2030, all manufacturing industries will accumulate 92 exabytes of data from multiple internal and external sources, underscoring the importance of unified data platforms.
AI adoption remains cautious yet accelerating as it sits atop CIO and Chief AI Officer agendas. Specialized analytics partners treat AI as a core element of digital transformation; integrating cloud platforms, big data analytics, and emerging technologies while overwhelmed internal teams lack bandwidth for comprehensive modernization.
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