Case studies

Engagements, written up like engineering reports

Each one covers the constraint, the decision, the architecture and the consequence — including the parts that were harder than expected.

Sample contentSample engagement. Illustrative scenario used while the site is in build — not a named client project.

fintech2025
  • Java
  • Spring Boot
  • Kotlin

01European payment service provider (sample scenario)

Payment Platform Modernization

A ten-year-old payment monolith moved from quarterly release windows to weekly deployments, without a rewrite and without a settlement incident.

  • Release cadence moved from quarterly windows to weekly deployments
  • Reconciliation lag reduced from overnight to near real time
  • Java
  • Spring Boot
  • Kotlin
  • PostgreSQL
  • Kafka
travel and hospitality2025
  • Kotlin
  • Spring Boot
  • PostgreSQL

02Multi-property hospitality group (sample scenario)

Enterprise Booking Platform

A booking platform serving multiple properties and channels, rebuilt around a single availability model and a back-office console operators actually wanted to use.

  • Overbooking incidents eliminated in the peak season following launch
  • Channel synchronisation latency reduced from minutes to seconds
  • Kotlin
  • Spring Boot
  • PostgreSQL
  • Redis
  • Kafka
saas2026
  • Python
  • TypeScript
  • LLM integrations

03B2B SaaS company with a large support operation (sample scenario)

AI-Assisted Operations Platform

Document intake and support triage moved to a draft-first AI workflow with human approval, measured against an evaluation set built from two years of historical cases.

  • Routine classification and extraction handled as drafts, with review rather than authoring
  • Quality tracked as a published accuracy metric per task type, not an impression
  • Python
  • TypeScript
  • LLM integrations
  • RAG
  • Vector databases
data and analytics2025
  • Java
  • Kafka
  • PostgreSQL

04Analytics provider in the retail sector (sample scenario)

High-Load Data Processing System

A nightly batch pipeline that had outgrown its window, re-architected into an incremental streaming system with correctness checks that alert before customers notice.

  • Processing moved from a single nightly window to continuous incremental updates
  • Single-day reprocessing without re-running the full pipeline
  • Java
  • Kafka
  • PostgreSQL
  • Redis
  • Docker
saas2026
  • Python
  • TypeScript
  • LLM integrations

05B2B SaaS platform with a distributed engineering team (sample scenario)

Autonomous Incident Response Agent

An AI agent that triages production alerts, reconstructs root cause and opens a reviewed pull request — removing the overnight on-call rota without removing the human approval step.

  • Overnight alerts arrive with a written diagnosis and a candidate fix attached
  • Time from alert to review-ready pull request reduced from an hour of manual work to minutes of review
  • Python
  • TypeScript
  • LLM integrations
  • RAG
  • Vector databases
fintech2026
  • Java
  • Spring Boot
  • Kotlin

06Consumer fintech launching a rewards product (sample scenario)

Card-Linked Rewards Platform

A real-time rewards engine that links card transactions to brand campaigns, with exactly-once attribution and a ledger that reconciles to the cent.

  • Duplicate transaction events provably cannot double-pay a reward
  • Campaign changes shipped by configuration instead of by release
  • Java
  • Spring Boot
  • Kotlin
  • PostgreSQL
  • Kafka
e commerce2026
  • TypeScript
  • Python
  • LLM integrations

07Online retailer with a large gift-card catalogue (sample scenario)

Conversational Product Discovery

Semantic search and an advisory layer for shoppers who know the occasion but not the product — validated with a three-day prototype before any production spend.

  • Previously empty result sets replaced with grounded, explainable suggestions
  • Search behaviour shifted measurably toward full-sentence queries
  • TypeScript
  • Python
  • LLM integrations
  • RAG
  • Vector databases
enterprise software2026
  • Java
  • Spring Boot
  • PostgreSQL

08Marine supply company operating across several regions (sample scenario)

Maritime Procurement ERP

A legacy ERP replaced module by module with a serverless, cloud-native platform — procurement, suppliers, orders and equipment in one system, with no downtime window.

  • Procurement, suppliers, orders and equipment consolidated in one platform
  • Legacy data migrated with quality checks rather than assumptions
  • Java
  • Spring Boot
  • PostgreSQL
  • React
  • TypeScript
saas2025
  • TypeScript
  • React
  • React Native

09Location services startup expanding into B2B (sample scenario)

Digital Addressing Platform

A product weighed down by technical debt refactored into a modular platform, with subscriptions, a business dashboard and public APIs added on top.

  • Feature work stopped competing with firefighting
  • Web and mobile behaviour converged onto shared logic
  • TypeScript
  • React
  • React Native
  • GraphQL
  • PostgreSQL
enterprise software2025
  • Java
  • Spring Boot
  • TypeScript

10LegalTech startup serving litigation teams (sample scenario)

Legal Scheduling Automation

Court date coordination reduced from a half-hour of manual email work to a single confirmation, with permissioned mailbox access and no public availability API to rely on.

  • Scheduling reduced from roughly half an hour of manual work to a short confirmation step
  • Follow-ups tracked automatically rather than living in someone's inbox
  • Java
  • Spring Boot
  • TypeScript
  • React
  • PostgreSQL
saas2026
  • Python
  • PyTorch
  • LLM integrations

11EdTech provider serving primary school classrooms (sample scenario)

Domain-Tuned Model for Children's Learning

A small, self-hosted language model tuned for age-appropriate tutoring — cheaper to run than a frontier API, and reviewable by educators before it reaches a child.

  • A model small enough to self-host affordably, tuned to the target reading level
  • Prompt engineering no longer required from the product team
  • Python
  • PyTorch
  • LLM integrations
  • AI agents
  • Docker
e commerce2026
  • Python
  • FastAPI
  • PostgreSQL

12Online fashion retailer with seasonal traffic peaks (sample scenario)

High-Load Support Assistant

A grounded support assistant answering catalogue, delivery and returns questions at sale-day traffic — with sub-ten-second worst-case responses and no invented policy.

  • Worst-case response time held under ten seconds at peak request rates
  • Service sustained sale-day load in rehearsal without degradation
  • Python
  • FastAPI
  • PostgreSQL
  • LLM integrations
  • RAG
enterprise software2025
  • Architecture review
  • Due diligence
  • Load testing

13Public cultural institution running a large digital platform (sample scenario)

Platform Audit & Remediation Plan

A three-week audit of a platform built by four vendors over eight years — architecture, code, performance, security and accessibility — ending in a costed, ordered remediation plan.

  • Bottlenecks identified with evidence, and fixes modelled to an order-of-magnitude throughput gain
  • Infrastructure rightsizing plan projecting a substantial recurring cost reduction
  • Architecture review
  • Due diligence
  • Load testing
  • Static analysis
  • Java
fintech2025
  • Java
  • Spring Boot
  • Vue

14Asset manager running a retail investor product (sample scenario)

Investment Analytics Replatform

An on-premise analytics application rebuilt on serverless infrastructure to carry a million daily users, with portfolio, screening and market comparison features added during the migration.

  • Peak-day capacity handled without pre-provisioning hardware
  • Infrastructure cost tracked per request instead of per rack
  • Java
  • Spring Boot
  • Vue
  • Nuxt
  • PostgreSQL
saas2025
  • Python
  • TypeScript
  • PostgreSQL

15Property marketing agency publishing to many portals (sample scenario)

Listing Distribution Automation

Rental listings distributed to partner portals through official feeds and APIs, driven by a self-updating desktop agent and a cloud pipeline with per-portal delivery status.

  • Publishing moved from manual repetition to a scheduled, monitored pipeline
  • Per-portal delivery status visible for every property in one place
  • Python
  • TypeScript
  • PostgreSQL
  • Docker
  • Terraform

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