Our Agentic Infrastructure Platform uses AI agents and deterministic tools to build, govern, heal, and optimize cloud infrastructure from code to compliance, transforming DevOps with self-managing systems.
With 97% of developers using AI coding assistants, software development has accelerated dramatically, but developers remain overwhelmed by infrastructure complexity with 76% reporting cognitive overload on architecture decisions.
Platform engineering teams can't simplify infrastructure processes fast enough to match accelerated development cycles, creating bottlenecks through manual deployment and security processes compounded by expertise shortages.
Developer productivity gains from AI-assisted coding are erased by infrastructure deployment delays, where weeks-long deployment cycles and security reviews eliminate any time-to-market advantages that AI coding provides.
AI agents automatically generate infrastructure code from high-level business intent and deploy it through self-validating pipelines with intelligent rollback capabilities. This eliminates the need for manual template creation and expert-dependent IaC coding that traditionally creates deployment bottlenecks.
Manual template creation, expert-dependent IaC coding, human orchestration with limited rollback (24-64 hours / 3-8 business days)
Intent-based AI generation plus fully automated, self-validating deployment (45 minutes / 0.12 business days)
Continuous AI-driven policy enforcement proactively monitors and corrects security vulnerabilities, compliance violations, and configuration drift in real-time. This replaces reactive point-in-time security scans that slow releases and miss critical issues between reviews.
Point-in-time scanning, reactive security measures (4-8 hours per review / 0.5-1 business days)
Continuous enforcement, proactive policy compliance (Continuous real-time / 0 business days)
Agents detect root causes and resolve infrastructure issues without human intervention, dramatically reducing mean time to resolution. Self-healing systems eliminate the need for manual troubleshooting and emergency response that traditionally requires expert knowledge and extended downtime.
Human troubleshooting, manual root cause analysis (2-4 hours MTTR / 0.25-0.5 business days)
Autonomous issue resolution, self-healing systems (5-15 minutes MTTR / 0.01 business days)
Real-time AI optimization continuously adjusts infrastructure resources based on performance metrics and business priorities without scheduled maintenance windows. This replaces manual capacity planning and performance tuning that can't keep pace with dynamic application demands.
Scheduled adjustments, manual performance tuning (2-4 hours weekly / 0.25-0.5 business days per cycle)
Real-time optimization aligned with business metrics (Continuous real-time / 0 business days)
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Join the companies already using StackGen to accelerate
their DevOps with autonomous, agentic workflows
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