Qfact's analysis functionality was slowing down as data volumes grew, and every non standard report was a ticket for a developer. We led the redesign that fixed both problems at once.
Frequently requested use cases organisations can now serve themselves, with no developer involved
The existing analysis methods could not keep up with the volumes being pushed through them. Reports that used to return quickly were becoming slow enough to stop people using them.
The data was also spread across multiple microservices, so any report worth having had to pull from several places and stay consistent while it did.
Load performance for complex multi source reports improved measurably, and organisations gained the ability to answer 25 or more of their most frequent questions without waiting on the development team.
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.
The indexing and full text search foundation underneath QIntelligence, built on Python and Elasticsearch and designed to outlive the requirements it started with.
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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