Qfact runs a SaaS platform that thousands of people use every day to work through complex analysis processes. We were on it from 2018 to 2024, six years, first building it and then leading the team that did, across design, architecture, delivery and the people work that holds all three together.
Developers led as direct reports, across design, implementation and delivery
Long term hires we interviewed and brought into the team
A platform that thousands of people rely on daily has to scale without losing data integrity, and it has to stay comprehensible to the team maintaining it. Both get harder every year the codebase grows.
Delivery was the other half of the problem. There was no measurable velocity, so nobody could say what a sprint would produce, and certain user facing bugs kept coming back release after release.
Qfact came away with a platform that scales horizontally, a delivery process the business could plan against, and a team that had grown in both size and capability.
A system that reads user uploaded documents, extracts what matters and generates project suggestions from it, built on large language models.
The indexing and full text search foundation underneath QIntelligence, built on Python and Elasticsearch and designed to outlive the requirements it started with.
A performance focused redesign of analysis functionality, with configurable reporting that took 25 or more frequently requested use cases off the development backlog entirely.
Tell us what you are building and where it hurts. We will tell you straight whether we are the right partner for it.
Book a 15 minute introduction