Before anything could be analysed, the documents had to be somewhere useful. We led the first phase of QIntelligence and built the infrastructure for storing, indexing and searching user documents inside Qfact's existing platform.
The infrastructure had to hold document volumes that would keep growing, and it had to slot into a microservices landscape that was already in production and could not be disturbed.
It also had to survive its own success. Whatever came next in the initiative would be built on this layer, so it needed room for requirements nobody had written down yet.
Qfact gained a document layer that scaled with its users and became the foundation for the automated content analysis that followed.
A microservices platform for complex analysis workflows, built and led from 2018 to 2024. We introduced measurable sprint velocity where there was none and removed whole classes of recurring bugs.
A system that reads user uploaded documents, extracts what matters and generates project suggestions from it, built on large language models.
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.
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