Discover our track record of successful partnerships delivering dedicated teams and cybersecurity specialists
Partner Projects
Active Partnerships
Specialists Deployed
We provided a dedicated team of 6 specialists to a multinational e-commerce company facing significant performance challenges across different geographical regions. Our team integrated with the client's existing engineering department to deliver comprehensive traffic optimization solutions.
Our dedicated team included 2 network engineers, 2 DevOps specialists, 1 cloud architect, and 1 team lead. They deployed intelligent edge servers across 15+ countries, implemented advanced caching algorithms, and created a real-time traffic routing system. The team worked as an extension of the client's engineering organization.
The partnership resulted in a 40% reduction in average latency, 60% improvement in page load times, and achieved 99.9% uptime. The client scaled the team from 4 to 6 specialists during peak season and has continued the partnership for 18 months. The system now handles over 10 million requests per day.
A Fortune 500 financial services company needed to augment their security team quickly to meet regulatory requirements. They engaged us to provide a dedicated SOC team and security architects to implement a zero-trust security framework while maintaining 24/7 monitoring coverage.
We deployed 8 security specialists organized in rotating shifts: 4 SOC analysts providing 24/7 monitoring, 2 security architects leading implementation, 1 compliance specialist, and 1 incident response lead. The team integrated with the client's existing security infrastructure and reporting structure.
Since the partnership began, the client has experienced zero security breaches and achieved 100% threat detection accuracy. Response time improved by 80%. The team passed all regulatory audits and blocked over 50,000 malicious attempts. The partnership has grown from 5 to 8 specialists over 2 years.
A major streaming platform needed a sophisticated real-time analytics solution to monitor traffic patterns, detect anomalies, and predict potential issues before they impact user experience. The client was processing over 1 billion events daily and required sub-second response times for critical alerts.
We built a scalable real-time analytics platform using Apache Kafka for event streaming, Apache Flink for stream processing, and Elasticsearch for data storage and querying. Machine learning models were deployed to detect anomalies and predict traffic spikes. Custom dashboards provided real-time visibility into system performance and user behavior patterns.
The platform successfully processes over 1 million events per second with sub-5ms response times. It has prevented 95% of potential outages through predictive analytics and reduced mean time to resolution by 70%. The client achieved 99.9% accuracy in anomaly detection and improved overall system reliability by 40%.
A leading online gaming company was experiencing frequent and sophisticated DDoS attacks that were affecting player experience and causing significant revenue losses. They needed a robust, scalable solution that could handle massive attack volumes while maintaining low latency for legitimate users.
We deployed a multi-layered DDoS protection system combining edge filtering, rate limiting, and behavioral analysis. The solution included custom-built detection algorithms using machine learning to identify attack patterns, automated mitigation responses, and real-time traffic scrubbing capabilities. Integration with CDN providers ensured global protection coverage.
The system successfully mitigated attacks up to 500Gbps in size, with detection times under 30 seconds. Since implementation, the client has maintained 99.99% uptime during attack periods and experienced zero service degradation. The solution has prevented an estimated $50 million in potential revenue losses and improved customer satisfaction scores by 35%.
A traditional retail company needed to modernize their legacy infrastructure and migrate to a cloud-native architecture to support their digital transformation initiative. The migration involved over 200 applications, terabytes of data, and required zero downtime during the transition.
We orchestrated a phased migration strategy using containerization, microservices architecture, and Infrastructure as Code (IaC). The solution included automated deployment pipelines, monitoring systems, and disaster recovery mechanisms. We implemented a multi-cloud approach across AWS, Azure, and Google Cloud for optimal performance and cost efficiency.
The migration achieved 60% cost reduction in infrastructure expenses, 300% improvement in application performance, and 99.95% system availability. The client gained the ability to scale resources dynamically, deploy new features 10x faster, and improved disaster recovery capabilities from 24 hours to 15 minutes recovery time.
A fintech startup required a robust API gateway solution to handle millions of payment processing requests while ensuring security, compliance, and optimal performance. The solution needed to support rapid scaling during peak transaction periods and provide comprehensive monitoring and analytics.
We designed and implemented a high-performance API gateway using Kong with custom plugins for rate limiting, authentication, and request transformation. The system included intelligent load balancing, circuit breakers, and automatic scaling based on traffic patterns. Advanced monitoring and alerting systems provided real-time visibility into API performance and health.
The platform successfully handles over 10 million API requests per day with sub-2ms latency and 99.9% success rate. The intelligent scaling system has reduced infrastructure costs by 45% while maintaining performance during traffic spikes. The client achieved PCI DSS compliance and improved their API response times by 70%.
A large telecommunications company needed comprehensive monitoring of their network infrastructure spanning multiple data centers and thousands of network devices. The existing monitoring solution was fragmented and unable to provide the visibility needed for proactive network management.
We implemented a centralized network monitoring platform using SNMP, NetFlow, and custom agents for deep visibility into network performance. The solution included predictive analytics to forecast potential issues, automated alerting systems, and interactive dashboards for real-time network health visualization. Integration with existing ticketing systems ensured seamless incident management.
The system now monitors over 10,000 network devices across 50+ locations with 30-second detection times for critical issues. Predictive analytics have enabled 95% of potential network problems to be resolved before impacting users. The client has reduced network downtime by 80% and improved mean time to resolution by 65%.
A multinational corporation with over 50,000 employees needed advanced network segmentation to protect critical assets and prevent lateral movement in case of security breaches. The existing flat network architecture posed significant security risks and made compliance with industry regulations challenging.
We implemented a comprehensive network segmentation strategy using software-defined networking (SDN) and micro-segmentation technologies. The solution included automated policy enforcement, dynamic security groups, and real-time threat detection. We deployed identity-based access controls and implemented a zero-trust network architecture with continuous monitoring and adaptive security policies.
The network segmentation platform successfully secured over 10,000 endpoints with 99.8% threat containment efficiency. The solution reduced the attack surface by 85% and prevented three major security incidents from spreading across the network. The client achieved SOC 2 and ISO 27001 compliance while improving network performance by 30% through optimized traffic flows.
A Fortune 500 company required unified security management across multiple cloud providers (AWS, Azure, GCP, Oracle Cloud, and Alibaba Cloud) with disparate security tools and policies. The challenge was to create a single pane of glass for security monitoring, incident response, and compliance management while maintaining each cloud's native security capabilities.
We developed a cloud-agnostic security orchestration platform using microservices architecture with automated threat detection, policy enforcement, and incident response workflows. The solution included real-time security event correlation, automated compliance checking, and unified identity management across all cloud environments. Machine learning models provided predictive threat analysis and automated security posture optimization.
The platform achieved 99.95% threat detection accuracy across all cloud environments with 2.3-second average response time for security incidents. Security operational costs reduced by 60% through automation, and compliance audit time decreased by 85%. The client gained unified visibility into their multi-cloud security posture and improved mean time to resolution (MTTR) by 75%.
A high-traffic social media platform was experiencing performance bottlenecks and uneven load distribution across their server infrastructure. During peak usage periods, some servers were overloaded while others remained underutilized, leading to degraded user experience and increased infrastructure costs.
We implemented an intelligent load balancing system using advanced algorithms that consider server health, response times, current load, and geographic proximity. The solution included health checks, automatic failover, session affinity, and predictive scaling based on traffic patterns. We also integrated with their existing monitoring systems for comprehensive visibility.
The new load balancing system reduced average response times by 50% and achieved 99.99% availability. The platform now efficiently handles over 5 million requests per hour with optimal resource utilization. The client reduced infrastructure costs by 30% through better resource allocation and improved user satisfaction scores by 45%.
A major streaming service required a custom Content Delivery Network (CDN) solution to reduce content delivery costs and improve user experience across global markets. The existing third-party CDN was expensive and didn't provide the flexibility needed for their specific use cases and geographic requirements.
We built a custom CDN infrastructure with edge servers strategically placed across 200+ locations worldwide. The solution included intelligent caching algorithms, content pre-positioning based on viewing patterns, and dynamic routing optimization. We implemented advanced compression techniques, image optimization, and adaptive bitrate streaming to maximize performance and minimize bandwidth usage.
The custom CDN achieved 80% bandwidth cost savings compared to the previous solution while improving content delivery speeds by 60%. The system now serves over 5TB of data daily across 200+ edge locations with 99.9% cache hit rates. The client improved their profit margins by 25% and expanded to 15 new markets due to cost efficiencies.
An e-commerce platform handling sensitive customer data and payment information required a robust Web Application Firewall (WAF) solution to protect against various web-based attacks including SQL injection, cross-site scripting, and bot attacks. The solution needed to operate with minimal latency impact while maintaining high accuracy in threat detection.
We deployed a comprehensive WAF solution with custom rule sets tailored to the client's specific application architecture. The system includes machine learning-based threat detection, behavioral analysis, rate limiting, and geo-blocking capabilities. We implemented real-time threat intelligence feeds and automated rule updates to stay ahead of emerging attack patterns.
The WAF has successfully blocked over 1 million attack attempts with 99.95% accuracy and less than 1ms added latency. The client has experienced zero successful web application attacks since implementation and achieved PCI DSS compliance. The solution prevented potential data breaches that could have resulted in millions of dollars in losses and regulatory penalties.
A global enterprise with 15,000+ employees across 45 countries needed to transform their traditional perimeter-based security model to a zero trust architecture. The challenge was to eliminate implicit trust while maintaining seamless user experience and ensuring continuous verification of every user, device, and application attempting network access.
We implemented a comprehensive zero trust framework with identity-based access controls, micro-segmentation, and continuous security monitoring. The solution included software-defined perimeters (SDP), privileged access management (PAM), and AI-powered behavior analytics. We deployed network access control (NAC) systems and integrated with existing identity providers for seamless single sign-on while enforcing strict verification protocols.
The zero trust implementation achieved 95% reduction in security breaches and lateral movement attempts. Network uptime improved to 99.8% with enhanced visibility into all network traffic. The client reduced security incident response time by 80% through automated threat detection and response. Employee productivity increased by 25% due to improved secure remote access capabilities.