Case studies

What the work actually looked like.

One per service line — the problem we were handed, what we built, and what changed afterwards.

AI automation

Enquiry triage and first-draft quoting

Professional services firm · Pakistan

Every enquiry landed in a shared inbox and was read three times before anyone could price it. Simple jobs waited behind complicated ones.

What we built

  • Agent reads each enquiry, classifies it and pulls the matching rate card
  • RAG over past proposals so the draft sounds like the firm, not like a bot
  • Draft quote queued for a human to approve, edit or reject
  • Cost caps and full logging on every model call

Outcome

  • Quotes drafted the same hour instead of the same week
  • Nothing leaves the building without a person approving it
  • Pricing decisions traceable back to a source document
  • Python
  • OpenAI
  • Postgres
  • Retrieval

n8n & workflow engineering

Six tools that finally talk to each other

Operations team · Pakistan

CRM, billing, support desk and spreadsheets each held part of the truth. Reconciling them was somebody's Friday.

What we built

  • Self-hosted n8n wiring the systems together, owned by the client
  • Retries, dead-letter handling and alerting on every failed run
  • Written runbook so the team can change a flow without calling us

Outcome

  • Manual reconciliation dropped out of the weekly routine
  • Failures surface as alerts instead of as month-end surprises
  • The workflows stay with the client — no vendor lock-in
  • n8n
  • Node.js
  • Docker
  • Webhooks

Web design & development

A marketing site the team can edit alone

After Realism · Australia

The old site needed a developer for every copy change, so it slowly stopped reflecting what the business did.

What we built

  • Full redesign and rebuild on a headless stack
  • Editable content model the marketing team runs without us
  • Performance and accessibility budgets enforced at build time

Outcome

  • Copy and page changes ship without a developer in the loop
  • Fast loads on the mobile connections most of their traffic uses
One of the best working experiences — kudos to Divlynx.
  • Next.js
  • Nest.js
  • Tailwind
  • shadcn/ui

Full-stack development

A storefront built for campaign spikes

El Club · USA

Traffic arrived in bursts behind marketing pushes, and the previous setup slowed down exactly when it mattered.

What we built

  • Catalogue, cart and checkout rebuilt from the ground up
  • Caching and load paths sized for burst traffic, not average traffic
  • Order flow instrumented so drop-off is visible per step

Outcome

  • Checkout holds up during campaign peaks
  • The team can see where customers abandon and act on it
We enjoyed working with Divlynx and will likely have additional jobs for them.
  • React
  • Node.js
  • Tailwind

Product & subscriptions

Self-serve billing, minus the support tickets

MetaStore · Pakistan

Plan changes, failed payments and cancellations all came through support because customers had nowhere to do them.

What we built

  • Subscription platform with plan management and billing states
  • Self-serve account area for upgrades, downgrades and cancellations
  • Dunning and payment-failure handling wired into Stripe

Outcome

  • Routine billing changes handled by customers themselves
  • Failed payments recovered automatically instead of manually
Execution was swift and outcomes exceeded expectations. Strong recommendation.
  • React
  • Tailwind
  • Stripe

Mobile apps

Fixtures, live scoring and squads in one app

Regional cricket league · Pakistan

Scores lived in group chats and squad sheets lived in spreadsheets, so nobody trusted either by the end of a season.

What we built

  • Live scoring with offline capture for grounds with poor signal
  • Fixture and squad management shared across web and mobile
  • One codebase shipped to both app stores

Outcome

  • One source of truth for a whole season of results
  • Scorers can work through a dead patch of signal and sync later
  • React
  • Express
  • MongoDB

Cloud, data & DevOps

Releases that stopped being an event

Divlynx platform · Global

Deployments were scheduled for quiet hours because a bad release meant downtime and a manual rollback.

What we built

  • Containerised delivery with infrastructure as code
  • Zero-downtime rollouts and automated rollback on failed health checks
  • Monitoring that pages an engineer before customers notice

Outcome

  • Deploys during working hours, not at midnight
  • Bad releases roll back on their own
  • AWS
  • Docker
  • Kubernetes
  • Terraform