Skip to main content
Case Studies

Work that shipped

Real projects. Real outcomes. Here's what we've built and what it meant for the businesses behind them.

FinTech · 2024 - May 2026 (defunct)

MarketAlerts (defunct)

AI-Powered Investment Intelligence

We ran the founding engineering on this product, from the first commit to the wind-down.

AI/ML LLM Integration Real-time Data FinTech

MarketAlerts needed a system that could ingest, process, and classify massive volumes of financial data in real time (news feeds, SEC filings, earnings reports, social sentiment) and turn it into actionable signals for retail and institutional investors.

We designed and built the full pipeline: data ingestion from 20+ sources, LLM-powered signal classification with human-calibrated confidence scoring, a real-time alerting system with per-user filtering, and a dashboard for monitoring and backtesting signal accuracy.

The platform processed thousands of data points per hour with 95% classification accuracy and ran in production continuously from launch until the product was wound down in May 2026. The marketing site at marketalerts.com is no longer operational.

The Challenge

Financial data is noisy, time-sensitive, and high-stakes. The product needed a system that could separate meaningful signals from noise, fast enough to be actionable and accurate enough to be trusted, built from nothing by a founding team.

Our Approach

We started with a focused MVP: one market, one signal type, one alert channel. Validated accuracy against human analysts, then expanded market coverage and signal types incrementally. Each expansion was measured before the next.

Tech Stack

React TypeScript Python FastAPI PostgreSQL MongoDB Redis Airflow AWS GCP

EdTech · 2015 - 2023 (8 years)

ClassCharts

Scaled to Millions of Users

We ran this as an eight-year engagement with Edukey Education, through to the acquisition by TES Global.

EdTech Scaling Cloud Migration Mobile Apps Multi-platform

ClassCharts is the leading behaviour management and seating plan tool used by thousands of schools across the UK. We came in as the first engineering hire after the CTO, when the product was still early stage, and stayed eight years while it grew to serve millions of students, teachers and parents.

Across those eight years the work covered the full stack: the web app used by teachers and school administrators, the parent and student mobile apps, the data pipeline handling millions of daily events, and the infrastructure that kept it running as the load grew from three servers to roughly a hundred instances.

It spanned feature development, incremental modernization from jQuery to React micro apps, a React Native rewrite of the mobile apps, CI/CD and containerization, migrations across Rackspace, GCP and AWS, and mentoring the developers who joined along the way.

The Challenge

School software has extreme usage spikes (morning registration, end of day, report card season) and zero tolerance for downtime. The platform needed to scale reliably while shipping features fast enough to stay ahead of competitors.

Our Approach

Deep integration with the founding team rather than vendor-style delivery: standups, roadmap input, and architecture decisions owned in-house. That long-horizon accountability is the model Corco Labs is built around.

Tech Stack

PHP CakePHP MySQL React React Native Docker Kubernetes

Smart City / IoT · 2024 - 2025 (6 months)

Smart City IoT Platform

IoT Infrastructure

We did the backend engineering inside a multi-vendor programme.

IoT Microservices Kubernetes Enterprise

A consortium was contracted to build the digital infrastructure for a new smart city development. We were brought in to design and implement the backend architecture, the layer connecting physical IoT sensors to the applications that city operators and residents would use.

The platform spans 5+ city domains: smart parking (sensor-driven occupancy and guidance), electricity grid monitoring, water distribution tracking, waste collection optimization, and environmental monitoring. Each domain has its own microservices, data pipelines, and operator dashboards.

We built 20+ microservices on Kubernetes, designed the event-driven architecture connecting IoT gateways to application services, and implemented the data layer handling millions of sensor readings per day.

The Challenge

Infrastructure programmes at this scale have strict requirements: multi-vendor coordination, long timelines, formal documentation, and systems that must run for decades. The architecture needed to be modular enough for independent domain teams to build on.

Our Approach

Domain-driven design from day one. Each city domain (parking, electricity, water, etc.) got its own bounded context with clean API contracts. This let multiple vendor teams build in parallel without stepping on each other.

Tech Stack

TypeScript Node.js PostgreSQL Cassandra Kafka Kubernetes Grafana Keycloak

EdTech · 2015 - 2023 (8 years)

ProvisionMap

Nationwide School Provision Tracking

Part of the same eight-year Edukey Education engagement.

EdTech SaaS Compliance Data Reporting

ProvisionMap helps schools track and manage student support provisions, from one-on-one tutoring to group interventions, and measure whether those provisions are actually working. It's used by thousands of schools across the UK for Ofsted reporting and SEND compliance.

We led the engineering across the same eight-year Edukey engagement: the core mapping engine, the reporting dashboard used by SENCOs and headteachers, and the data export pipeline that feeds into government compliance systems.

The platform grew alongside ClassCharts, sharing infrastructure while keeping its own domain-specific features, and was rolled out nationwide across a Mediterranean country. The work ranged from performance optimization under peak reporting loads to the audit trail system required for regulatory compliance.

The Challenge

Education compliance software has zero margin for error. Schools rely on it for government inspections. Data accuracy, audit trails, and uptime during reporting periods are non-negotiable.

Our Approach

Embedded with the product team rather than delivering from outside. Features were built incrementally and validated with real schools before national rollout. Shared infrastructure with ClassCharts kept costs down while maintaining separation of concerns.

Tech Stack

PHP CakePHP MySQL React Docker Kubernetes

FinTech · 3 years

Metis

Financial News Intelligence at Scale

Our own product, built and run in-house.

AI/ML Big Data NLP FinTech

Metis is our own financial intelligence platform: it ingests news from hundreds of sources worldwide, classifies each article using hierarchical AI models, and surfaces the most relevant signals to investment professionals. We built it in-house, which is why we can show the architecture in full.

We designed and built the entire pipeline: a distributed crawler that ingests 100K+ articles per day, a multi-stage AI classification system using GPT models for entity extraction, sentiment analysis, and topic categorization, and a search interface powered by Meilisearch for sub-second full-text queries across millions of documents.

The system runs on an event-driven architecture with BullMQ for job orchestration, Clickhouse for analytics queries across billions of rows, and a React dashboard that lets analysts drill down from macro trends to individual articles in seconds.

The Challenge

Financial news moves fast and comes from everywhere. The system needed to process massive volumes with low latency, classify accurately across dozens of categories, and make everything searchable in near real-time.

Our Approach

Started with ingestion reliability (no dropped articles, ever). Then layered AI classification incrementally: basic categorization first, then sentiment, then entity extraction. Each layer was validated against human analysts before adding the next.

Tech Stack

TypeScript React NestJS PostgreSQL Clickhouse Meilisearch Redis

Energy / Technology · 4+ years

Enterprise Energy Platforms

Philips, RWE & Innogy Digital Products

We built these for Philips, RWE and Innogy through Cuibono Media Network, the agency that held the accounts.

Enterprise Interactive Tools Energy B2B

Over several years we delivered a run of digital products for major European enterprise brands, contracted through the agency Cuibono Media Network GmbH. For Philips, the Metronomis LED Configurator: an interactive B2B tool that lets customers design and visualize custom LED lighting poles before purchase.

For Axxerion, MyENMS: an energy management platform giving facility managers real-time visibility across connected energy sources, with virtual and physical meters, alerting, and reporting. For RWE, the Mint Music Awards app, an interactive voting and nominee-browsing campaign platform. For Innogy, a 2D room planner for laying out rooms with doors, windows, and furniture.

Each project ran inside enterprise constraints: strict brand guidelines, accessibility requirements, multi-language support, and integration with backend systems owned by someone else.

The Challenge

Enterprise brands need pixel-perfect brand compliance, accessibility standards, multi-language support, and integration with legacy systems, all while keeping the end-user experience simple and fast.

Our Approach

Rapid prototyping to align on UX before building: interactive prototypes early, iteration with stakeholders, then production-grade code that met enterprise quality gates.

Tech Stack

JavaScript TypeScript PHP WordPress MySQL CSS

Your project could be next

Tell us what you're building. We'll tell you honestly whether we're the right fit and what we would ship first.