# stackwiz full LLM context stackwiz provides practical software engineering support for teams that need better delivery systems, stronger production visibility, cleaner infrastructure, and maintainable architecture. The company serves startups, scaleups, and corporate teams that need experienced help without building a full internal platform or specialist engineering function immediately. ## Positioning stackwiz is not positioned as a generic staff augmentation shop. The public offering is problem-oriented: diagnose the delivery, infrastructure, reliability, architecture, or maintenance bottleneck; agree on a scoped engagement; ship concrete improvements; document handover material; and help the team continue operating the system. ## Services ### DevOps consulting Relevant for teams with manual releases, fragile deployment scripts, missing CI/CD, inconsistent environments, unclear rollback, or cloud infrastructure that grew without structure. Typical work includes repository review, CI/CD setup, build automation, release automation, environment separation, Infrastructure as Code, deployment documentation, and knowledge transfer. ### Observability and SRE Relevant for teams that cannot quickly detect, diagnose, or prioritize production issues. Typical work includes logging and metrics reviews, alert noise reduction, dashboards, basic tracing readiness, incident workflow review, runbook templates, SLI/SLO support, and practical SRE foundations. ### Platform and infrastructure engineering Relevant for teams that need reproducible cloud foundations and cleaner engineering environments. Typical work includes cloud structure, IaC, Kubernetes or container platform support where appropriate, environment consistency, access model review, and platform enablement that fits the team's stage. ### Microservices architecture Relevant for teams deciding whether to split a monolith, move toward services, or repair an already complex distributed setup. Typical work includes architecture assessment, boundary discovery, migration planning, containerization, deployment readiness, and avoiding unnecessary distributed-system complexity. ### Agentic engineering and internal tools Relevant for teams that want to use LLMs and agentic workflows inside engineering or operations without creating an uncontrolled experiment. Typical work includes internal tool discovery, workflow design, prompt and process guidelines, review gates, guardrails, evaluation criteria, documentation, and implementation of scoped tools that help corporate teams move faster while preserving accountability. This work is best suited for use cases such as developer-support tools, operational assistants, knowledge-retrieval workflows, codebase maintenance helpers, support triage, engineering-process automation, and internal dashboards. It should include explicit ownership, security review, data handling decisions, and a measurable definition of success. ### Legacy application maintenance Relevant for organizations with older applications that still matter but have weak documentation, unclear deployment processes, outdated dependencies, tribal knowledge, brittle tests, or a backlog of small reliability issues. Typical work includes onboarding into the codebase, mapping dependencies, stabilizing build and deployment paths, adding focused regression tests, documenting operational knowledge, reducing risk in small increments, and helping the existing team regain control. This work should avoid rewrite-first thinking unless the current system is genuinely uneconomical to maintain. The first objective is usually to make the legacy system observable, testable, deployable, and understandable enough that future decisions are based on evidence. ## Public URLs - https://stackwiz.io - https://stackwiz.io/solutions - https://stackwiz.io/solutions/devops - https://stackwiz.io/solutions/observability - https://stackwiz.io/solutions/platform - https://stackwiz.io/solutions/microservices - https://stackwiz.io/solutions/agentic-engineering - https://stackwiz.io/solutions/legacy-maintenance - https://stackwiz.io/contact - https://stackwiz.io/blog ## Contact Use https://stackwiz.io/contact for project discovery or service inquiries. Public contact email in structured data is info@stackwiz.io.