12+ years of operator experience
E-commerce infrastructure and AI delivery systems — founder-led, hands-on.
We build and stabilize revenue-critical commerce systems for teams that need stronger delivery, cleaner infrastructure, and less operational chaos.
We operate in the layer where uptime, release flow, observability, and platform decisions directly shape commercial outcomes.
Magento / PWA / Akeneo · Symfony / Pimcore · AWS / Azure / Hetzner · CI/CD / IaC / Containers
99.95% stability target across release-critical paths
| Area | Stack | Details |
|---|---|---|
| Provisioning | Terraform / Terragrunt | Hetzner Cloud, AWS, and hybrid VPS setups |
| Automation | Containerized Ansible | Repeatable provisioning and server management |
| Delivery | CI/CD with zero-downtime | Validation, rollback readiness, and zero-downtime release patterns |
Security — Access, secrets, backups · Recovery — Rollback ready · Observability — Full-stack visibility
| What defines our work | What that means in practice |
|---|---|
| Operator mindset | We care about uptime, release safety, recovery, and delivery speed — not presentation theatre. |
| Automation first | We replace tribal knowledge with Terraform, Ansible, Docker, CI/CD, runbooks, and repeatable workflows. |
| Commerce-native thinking | We understand catalog, checkout, search, queues, cache layers, integrations, and peak traffic realities. |
| AI with guardrails | We use AI where it shortens lead time and makes knowledge reusable, but keep humans in control of decisions. |
- Releases that are too risky because the platform depends on heroics.
- Infrastructure that grew fast but was never standardized.
- Magento or PWA performance problems that leak revenue and slow product work.
- Missing operational discipline: poor observability, weak rollback paths, undocumented flows.
- AI experimentation without governance, traceability, or integration into real delivery work.
We work directly in the application layer where performance and stability affect revenue — from catalog and checkout to search, cache, feeds, and multi-store operations.
- Checkout layer — Magento 2 platform engineering for B2C and B2B commerce. Headless and PWA storefront architectures with intelligent middleware proxies.
- Search / Cache — Varnish, OpenSearch, queue, and cache tuning for high-traffic stores.
- PIM / Data flow — Akeneo PIM integration and data flow design.
- Ops coverage — Multi-store architecture, production diagnostics, traffic-ready releases, monitoring + incident loop.
We build internal operating systems that help technical teams move faster. Tooling, memory, agents, retrieval, and delivery rules — assembled into systems that multiply engineering output without losing control.
| Layer | Stack | Details |
|---|---|---|
| Toolkits | Claude / Cursor / Windsurf / Copilot / Gemini / Cline / Roo Code / Aider | AI coding toolkits with common rules, reusable prompts, and deployment-safe workflows |
| Knowledge | RAG + CRAG + multi-hop + vision | RAG-based knowledge bases with semantic search, CRAG, multi-hop reasoning, and vision support |
| MCP | Jira + knowledge retrieval | MCP server integrations for Jira and knowledge retrieval |
| Orchestration | Approval gates + human-in-the-loop | Agent orchestration flows with approval gates and human-in-the-loop control |
| SDK | AI-assisted e-commerce ops | SDK and workflow components for AI-assisted e-commerce operations |
- Diagnose — Audit architecture, release flow, performance risks, operational pain points, and where the team is losing speed or control.
- Design — Define the architecture, automation boundaries, environments, observability, and measurable success criteria.
- Codify — Codify infrastructure, containerize services, standardize pipelines, and document the path so the team can repeat it.
- Ship — Small reversible changes, validation-first workflows, rollback readiness, and clear operational checkpoints.
- Transfer — Monitor, tune, document, and leave behind SOPs, runbooks, and tooling that survive beyond one release window.
- Direct and measurable — Clear goals, clear trade-offs, clear ownership.
- Strategic but hands-on — Architecture decisions backed by implementation.
- Three options, not one guess — We compare paths before committing.
- Documentation as leverage — If a process matters, it should be reusable.
- Focus on the real bottleneck — Not the loudest symptom.
| Stage | Deliverables |
|---|---|
| Architecture | Target topology, migration plan, dependency map, risk list |
| Implementation | Terraform modules, Ansible automation, Docker images, CI/CD changes |
| Validation | Syntax checks, deployment verification, rollback path, health checks |
| Operations | Monitoring, alerting, runbooks, cost and performance improvements |
| Enablement | SOPs, KB articles, AI assistant workflows, team-specific tooling |
| Repository | Description | Status |
|---|---|---|
| ai-toolkit | Claude Code toolkit — skills, agents, hooks, and knowledge base integration | PUBLIC |
| jira-mcp | MCP server for Jira integration — multi-instance, caching, bulk operations | PUBLIC |