Case studies

Cub Care is developing novel models of healthcare by combining the best of people, process redesign and technology. The service launched on 6 Oct 2020 with the mission of reimagining what urgent healthcare for kids can be.

Their vision is to build an integrated digital children’s healthcare service that supports families before, during and after their urgent healthcare needs.

As global automotive accessories manufacturer, EGR sought to expand its digital footprint with a bespoke e-commerce website that would seamlessly integrate with its existing software and business processes.

The project began with in-depth user interviews to capture the unique requirements of various stakeholders. These insights drove the design of user flows and mockups, ensuring that the website's architecture would not only support a logical and intuitive user journey but also reflect the sophisticated brand image.

In 2020, GPs urgently needed a lightweight, secure way to video call patients — existing tools were clunky or inappropriate for clinical use. The team behind Cub Care worked with Stacktrace early on to create a purpose-built platform, launched within weeks.

Initially free for doctors during the pandemic, GP Consults still runs today — with essentially maintenance-only engineering since 2025.

etrainu partnered with Stacktrace on a new strategic project to accelerate accelerate roadmap away from previous-gen technologies by providing modern reference-applications for replication going forward.

This included implementing Infrastructure as Code using Terraform CDK in TypeScript, integrated Typescript CLI and a NextJS-based Checkout Service.

Conformance against an external standards body is a documentation problem before it is an engineering one: dozens of test scenarios, payload schemas that change between versions, and feedback that arrives buried in email threads. Every claim a vendor makes must be evidence-backed and traceable to source, and a single stale reference can sink a submission cycle.

Stacktrace built an agentic knowledge base that ingests every artifact a vendor receives or produces, extracts and captions even the screenshots, organises it into isolated knowledge graphs, and lets AI agents answer questions with a citation back to the exact source document — then verifies each submission against the standard before it goes out.

Many companies desire to use generative AI but have concerns around security of data and the ability to customise performance to their specific documents. In a recent proof-of-concept, we created a secure cloud-hosted Q&A system with a chat interface enabling a variety of LLM models.