---
title: "Case Studies — TechCircleTeam"
description: "Deep-dive case studies: the challenge, our approach, technology, motion, performance, and business outcomes."
lang: en
json-ld:
---

[![Tech Circle Team logo](/assets/techcircle-mark-DfgULZRi.png) TECH CIRCLE TEAM. ](/)

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Case Studies

# Craft that shows up  in the numbers.

Selected engagements where the work moved the metric.

![Global Aviation Group \[NDA\] — A control tower for a fleet operator](/assets/showcase-aeroflight-DvPQ9dg2.jpg)

CASE / 01 

## Global Aviation Group \[NDA\] — A control tower for a fleet operator

Challenge ·  Legacy tooling required manual entry across five disconnected systems.

Approach ·  Unified command center with real-time telemetry and an AI ops copilot, built by our senior engineers with AI-assisted delivery.

-   Next.js
-   Node
-   PostgreSQL
-   OpenAI
-   Cloudflare

Ops overhead reduced

31%

Delivery

14 wks

Daily users

2.4k

> “They combined AI with genuinely experienced engineers — the result feels bulletproof.”

— Head of Digital, Aviation Group (name withheld under NDA)

![Luxury Fashion House \[NDA\] — Editorial commerce that feels like couture](/assets/showcase-maison-BPcUUCvX.jpg)

CASE / 02 

## Luxury Fashion House \[NDA\] — Editorial commerce that feels like couture

Challenge ·  Stock ecommerce templates diluted the brand at every touchpoint.

Approach ·  Headless, cinematic storefront with scroll-driven storytelling and instant checkout — designed and coded in parallel.

-   Next.js
-   Shopify
-   Stripe
-   GSAP
-   Vercel

Revenue lift (12 mo)

£310k

AOV growth

+28%

Lighthouse

94

> “Every page finally feels like the brand. Conversions followed almost immediately.”

— Ecommerce Director, luxury house (name withheld under NDA)

![Enterprise SaaS \[NDA\] — An AI copilot for their support desk](/assets/showcase-quantum-BN2HgJPe.jpg)

CASE / 03 

## Enterprise SaaS \[NDA\] — An AI copilot for their support desk

Challenge ·  A rising support backlog with 30% MoM ticket growth was overwhelming a small team.

Approach ·  RAG assistant grounded in product docs, tickets and Slack — shipped by AI-augmented engineers in eight weeks.

-   React
-   Supabase
-   Claude
-   pgvector
-   AWS

Auto-resolution

46%

First-response time

\-38%

CSAT

8.9/10

> “Half of our tickets are now solved without a human touching them. That is transformational.”

— VP Support, B2B SaaS (name withheld under NDA)

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