// Case Studies

Real engagements. Measurable outcomes.

Every engagement is scoped against a specific business KPI. Here's a snapshot of three recent programs — full technical readouts available on request.

Case 01E-commerce EngineeringHalden & Co. · DTC Menswear

Replatforming a legacy storefront into a headless commerce engine.

The challenge

Halden's Magento 1 storefront was slow, expensive to maintain, and unable to support the merchandising velocity the team needed. Mobile Core Web Vitals were failing, and every campaign push required an engineer.

The solution
  • Migrated to a Next.js + Shopify Hydrogen headless architecture on Vercel edge.
  • Rebuilt the product data layer with type-safe GraphQL and Algolia-powered search.
  • Introduced a component library that let merchandisers ship new landing pages in hours, not weeks.
  • Implemented server-side A/B testing and edge personalization for repeat visitors.
336%
Rise in items sold
1.2s
Median LCP (from 4.8s)
-58%
Infra & maintenance cost
Case 02SEO & ConversionMeridian Labs · B2B SaaS

Rebuilding organic acquisition around technical SEO and CRO.

The challenge

Meridian was ranking on brand terms only. Their marketing site had crawl issues, thin category coverage, and a demo funnel converting at under 1%. Paid channels were eating margin.

The solution
  • Full technical SEO remediation: sitemap architecture, internal linking, and Core Web Vitals pass.
  • Programmatic SEO layer targeting 800+ high-intent long-tail queries with human-edited templates.
  • Rebuilt the demo funnel with progressive profiling and iterative CRO across five landing systems.
  • Attribution model rewired to reflect assisted organic conversions.
2.5×
Qualified inbound leads
4.7%
Demo conversion rate
18k
New non-brand sessions/mo
Case 03AI OperationsNorthwind Logistics · 3PL

Autonomous AI agent swarm for customer operations.

The challenge

Northwind's support team was drowning in shipment-status enquiries — 4,000+ tickets per week, average wait time over 40 minutes, and CSAT sliding. Adding headcount was economically untenable.

The solution
  • Built a coordinated swarm of specialised AI agents: intake classifier, tracking resolver, exception handler, and human-escalation router.
  • Grounded the language model in a private vector index over shipment, CRM, and knowledge-base data.
  • Deployed evaluation harness with weekly red-team runs and continuous fine-tuning.
  • Integrated a human-in-the-loop console for edge cases and quality auditing.
-70%
Customer wait time
82%
Tickets fully autonomous
+11pt
CSAT improvement

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