Blog
From the Blog
Technical breakdowns, architecture notes and case studies from deployed systems.
Featured Articles
Latest Production Cases
Build vs Buy: When to Build a Custom Commerce Platform
Buy an off-the-shelf platform when your needs are standard and speed matters; build custom when your core workflow is your competitive advantage and no platform fits without heavy compromise. Most companies should buy the commodity and build only the differentiating layer on top.
Magento 2 to Hyvä Migration: Step-by-Step Plan and Timeline
A Magento 2 to Hyvä migration runs in five stages: audit and module inventory, theme scaffolding, component rebuild (PDP/PLP/cart), checkout migration, and QA plus launch. For a mid-size store this is typically 4 to 8 weeks, with checkout and third-party Knockout modules driving most of the effort.
All Articles
Articles
Build vs Buy: When to Build a Custom Commerce Platform
Buy an off-the-shelf platform when your needs are standard and speed matters; build custom when your core workflow is your competitive advantage and no platform fits without heavy compromise. Most companies should buy the commodity and build only the differentiating layer on top.
Magento 2 to Hyvä Migration: Step-by-Step Plan and Timeline
A Magento 2 to Hyvä migration runs in five stages: audit and module inventory, theme scaffolding, component rebuild (PDP/PLP/cart), checkout migration, and QA plus launch. For a mid-size store this is typically 4 to 8 weeks, with checkout and third-party Knockout modules driving most of the effort.
Hyvä vs Luma: Magento 2 Frontend Performance Compared (2026)
Hyvä replaces Magento 2 Luma's Knockout.js/RequireJS stack with Alpine.js and Tailwind, cutting JavaScript payload by 90%+ and typically moving Lighthouse mobile scores from the 30s to 90+. Luma remains viable only for teams blocked by legacy module dependencies.
AI Agents for E-commerce Operations: What Actually Works in Production
In production, AI agents earn their place on narrow, high-volume e-commerce tasks: customer support triage, order and logistics exception handling, catalog enrichment, and demand-signal monitoring. The pattern that works is a bounded agent with tool access and a human escalation path — not an open-ended autonomous system.
Reducing latency by 63% in production
Replaced a queue-based architecture with deterministic routing. 14 days implementation, 4.2M daily requests.
Replacing a 400-person support team with AI
From linear scaling costs to zero incremental cost per ticket. 2.8s average resolution, zero failure protocol.
E-commerce Workflow Automation: From Manual Ops to Autonomous Pipelines
E-commerce workflow automation replaces manual, repetitive operations — order processing, inventory sync, refunds, supplier updates — with observable pipelines that connect your systems through well-defined steps. Start with the highest-volume manual process, automate it end to end with logging and alerts, then expand.
Logistics Orchestration: Automating Order Exception Handling at Scale
Logistics orchestration automatically detects and resolves order exceptions — stuck orders, missing or stale tracking, carrier delays, and SLA breaches — across multiple carriers and warehouses. The system monitors order state continuously, applies rules or proposes fixes, and escalates only the cases that genuinely need a human.
Decision Intelligence for E-commerce: Turning Signals into Actions
Decision intelligence connects your sales, inventory, pricing, and marketing data into a system that surfaces what changed, why it matters, and what to do next. Unlike a dashboard you have to read, it monitors signals continuously and pushes prioritized, explainable recommendations to the people who can act on them.
// Operate at production scale
Stop reading.
Start deploying.
These are not hypotheticals. They're production systems running right now. Let's build yours.
No calls. No decks. Just systems.