Skip to content

Case studies

Enterprise Software Development, with the architecture decisions shown

Four engagements written the way we would explain them to your CTO: the constraint we walked into, the decisions that turned out to matter, and the numbers the client reported afterwards. Every client below agreed to be named, and will take a reference call.

  • Retail & Commerce
  • Healthcare
  • Logistics
  • Financial Services

How to read these

Each study follows the same three-part structure, so you can skim four engagements without re-learning the format.

The challenge
The situation as it actually was, including the parts that were nobody’s fault and the parts that were.
What we built
The architecture decisions that mattered, in the order they were made. Not a technology list.
Business outcomes
Numbers the client reported to their own board. Where a figure is a range or an estimate, we say so.

The work

Four engagements, start to production

Financial services, healthcare, logistics and retail: different industries, the same delivery standards.

Orbital Retail Group

Retail & Commerce

20267 core technologies
  • TypeScript
  • React Native
  • Next.js
  • Go
  • Kafka
  • PostgreSQL
  • AWS

A dedicated dev team that took a checkout rewrite from stalled to shipped

Seven embedded engineers owning the checkout domain end to end, including on-call, across a seven-month engagement.

The challenge

A checkout replatform had been in progress for eleven months with no production traffic. The in-house team was carrying the legacy system’s incident load and could not get a clear run at the new one. Conversion on mobile was eleven percent below the sector benchmark and the cause was unknown.

What we built

  • Dedicated team took full ownership of the checkout domain including its on-call rotation
  • Progressive rollout by traffic percentage and market, with automated rollback on conversion regression
  • Payment orchestration layer abstracting three regional providers behind one idempotent interface
  • Real user monitoring wired to the conversion funnel, making the mobile regression visible within a week
  • Contract tests between checkout, pricing, inventory and fulfilment, removing the shared staging bottleneck

Business outcomes

+19%
Mobile checkout conversion
2.5 days to 4 hours
Time from approval to production
-73%
Checkout error rate
14
Client engineers onboarded to new stack

Northwind Health Systems

Healthcare

20266 core technologies
  • Python
  • FastAPI
  • pgvector
  • Azure OpenAI
  • Azure Kubernetes Service
  • Terraform

A retrieval assistant clinicians actually trust, inside a HIPAA boundary

AI & cloud solutions applied to 40 years of clinical guidance, with an evaluation harness that gates every release on measured retrieval quality.

The challenge

Clinicians were searching four disconnected repositories of protocols, formulary rules and local policy, averaging six minutes per lookup. An earlier vendor pilot had been withdrawn after clinicians found confidently worded answers that cited protocols which had been superseded years earlier.

What we built

  • Document ingestion with version-aware chunking so superseded guidance is never retrieved as current
  • Hybrid retrieval - dense vectors plus BM25 - with a cross-encoder reranker tuned on clinician-labelled pairs
  • Golden set of 640 real clinician questions, annotated by practising staff, executed on every pipeline change in CI
  • Mandatory citations with deep links to the source paragraph, and an explicit abstention path
  • Entirely inside the customer VPC, with private model endpoints and no data leaving the compliance boundary

Business outcomes

94.1%
Recall@10 on golden set
6 min to 40s
Median lookup time
0.7%
Unsupported claims in audit
71% of eligible staff
Clinician weekly active use

Atlas Freight Network

Logistics

20257 core technologies
  • TypeScript
  • Next.js
  • Node.js
  • PostgreSQL
  • Redis
  • GCP
  • Terraform

Rebuilding a carrier portal that had outgrown its own database

Full-stack web engineering for a multi-tenant platform serving 4,200 carriers, moving from nightly spreadsheets to real-time visibility.

The challenge

The carrier portal ran on a single shared Postgres schema with tenancy enforced in application code. Two cross-tenant data exposures in eighteen months had reached the board. Peak-season load produced 40-second page loads, and the largest twelve customers had contractual data residency requirements the platform could not meet.

What we built

  • Tenancy moved behind a single data-access seam, then to row-level security with transaction-scoped tenant context
  • Dedicated database tenancy for the twelve largest accounts, behind the same routing layer
  • Next.js front end with server components and streaming, replacing a client-rendered single-page application
  • Read models projected from the operational store for the reporting views that caused the worst load
  • Load testing wired into the release pipeline with peak-season traffic profiles

Business outcomes

40s to 1.4s
p95 page load at peak
Zero since launch
Cross-tenant exposure incidents
-38%
Infrastructure cost at peak
+54%
Carrier self-serve adoption

Meridian Financial Group

Financial Services

20257 core technologies
  • Java 21
  • Kafka
  • Debezium
  • PostgreSQL
  • Kubernetes
  • Terraform
  • AWS

Moving a 22-year-old lending platform off the mainframe, one product at a time

A staged legacy system modernization that replaced batch-driven loan origination with event-driven services, without a single cutover weekend.

The challenge

Loan origination ran on a COBOL core with overnight batch settlement. New products took nine months to launch because every change required a coordinated release across four teams, and the two engineers who understood the batch scheduler were both within three years of retirement. Regulatory reporting was assembled by hand from four sources each quarter.

What we built

  • Routing seam in front of the core, with per-product traffic rules flippable without a deploy
  • Change data capture from DB2 into a Kafka log, giving new services a replayable event stream
  • Product-by-product extraction into Java services with Postgres ownership, dual-written and reconciled hourly
  • Event-sourced ledger for settlement, replacing overnight batch with continuous posting
  • Automated regulatory reporting derived from the event log rather than from nightly extracts

Business outcomes

9 months to 6 weeks
New product launch time
Overnight to under 90s
Settlement latency
78%
Production traffic on new services
Zero
Cutover incidents

In their words

What the people who signed the contracts said afterwards

Named leaders at the organisations above. We will arrange an introduction to any of them during your evaluation.

  • Our own engineers are visibly better at this than they were two quarters ago. The knowledge transfer was not a slide deck at the end, it was pairing every week from the first sprint to the last.
    Rafael MonteiroHead of Platform Engineering, Vectra Mobility
  • Discovery cost us three weeks and about four percent of the programme budget. It surfaced two integrations with no sandbox and a data model nobody had looked at in a decade. I have stopped agreeing to projects that skip it.
    Hannah LindgrenProgramme Director, Nordkap Insurance
  • The dedicated team took on-call from day thirty and never handed it back. That is the difference between a vendor and a team - they lived with their own decisions.
    Tom BradshawDirector of Digital Products, Orbital Retail Group

Your engagement

Most of these started as a problem nobody wanted to write down.

If your situation looks like one of the four above, a system nobody wants to touch, an AI pilot that never cleared review, a platform that has outgrown its own database, that is exactly the conversation to have.

Direct line:moeed@moreinns.com