TM Systems: Secure Enterprise Cloud, AWS DevSecOps, AI/ML & Cyber

TM Systems empowers data-driven enterprises to build, secure, and intelligently automate their AWS environments — combining DevSecOps practices, cloud-native cybersecurity, and AI/ML into a single unified delivery model. With 5+ AWS-certified engineers across EC2, EKS, ECS, RDS, CloudFront, S3, and Lambda, T M Systems eliminates the tradeoff between speed and security. Your engineering and data teams move faster knowing every pipeline, container, and AI workload is built with security embedded from day one — not bolted on after the fact. What We Help You Achieve Security treated as an afterthought in DevOps pipelines, creating compliance gaps and vulnerability exposure across containerized workloads AI/ML initiatives stalled due to lack of secure, scalable AWS infrastructure to train, deploy, and monitor intelligent models EKS and ECS environments running without hardened security controls, runtime protection, or compliance guardrails CloudFront distributions and S3 assets exposed to threats from inadequate edge security controls Siloed security, development, and operations teams creating friction, slow releases, and undetected risks

Core Capabilities DevSecOps Pipeline Engineering — Security scanning, compliance checks, and automated governance embedded into CI/CD pipelines across EKS and ECS — every release validated and secure before production Container Security & Orchestration — EKS and ECS clusters hardened with runtime protection, network policies, least-privilege IAM, and automated vulnerability scanning AI/ML Infrastructure on AWS — Secure, scalable AI/ML environments on EC2, Lambda, and S3 enabling data teams and CDOs to build, train, and serve intelligent models with confidence Cybersecurity & Threat Protection — Multi-layer security across EC2, RDS, S3, and CloudFront covering IAM governance, network hardening, encryption, and continuous threat monitoring Edge Security & Content Delivery — CloudFront configured with origin access controls, geo-restrictions, and signed URL policies to protect globally distributed content and APIs Serverless Security Automation — Lambda functions automating security event detection, compliance remediation, threat response, and operational security tasks across the AWS stack Engagement Model

Phase 1 – Discovery: DevSecOps maturity, container security posture, AI/ML readiness, pipeline vulnerabilities, compliance gaps. You get: Maturity report · EKS/ECS security assessment · AI/ML readiness audit · Vulnerability analysis · Quick wins. Phase 2 – Design: DevSecOps architecture, container hardening standards, AI/ML design, security control framework. You get: Roadmap · Secure CI/CD design · EKS/ECS hardening blueprint · AI/ML architecture · CloudFront/S3 security design · IAM/Lambda plan. Phase 3 – Build: Hardened pipelines, secure clusters, AI/ML environments, cybersecurity controls deployed. You get: Secure CI/CD operational · EKS/ECS hardened · AI/ML on EC2/Lambda/S3 · CloudFront edge security active · RDS encryption configured · Lambda automation live. Phase 4 – Handover: Validate controls, run compliance checks, document all configurations, transfer ownership. You get: Security validation checklist · Compliance report · Pipeline and container docs · AI/ML runbooks · Knowledge transfer session. Phase 5 – Operate & Optimize (Optional): Ongoing DevSecOps ops, threat monitoring, AI/ML tuning, compliance per SLA. You get: Continuous threat monitoring · EKS/ECS security reviews · AI/ML monitoring · CloudFront/S3 audits · Cost optimization.