Good partnerships in research technology don't happen by accident. They happen when two teams find themselves asking the same questions, holding the same values, and realising their tools do different things well. That's exactly what happened when Qualzy and CoLoop started talking.
We're pleased to announce that Qualzy users can now export their research data directly to CoLoop for enhanced analytical approaches. It's an integration built on a genuine alignment of priorities - and one we think will make a real difference to researchers who want more from their analysis without trading away the things they trust about how their platforms handle data.
What CoLoop brings
CoLoop is a specialist platform built around AI-powered transcription, translation, and primary content analysis. Its founder, Jack Bowen, has been thinking carefully about what AI can and can't do well in a research context for some time - and that considered approach shows in how the product is built.
In CoLoop, researchers can organise responses into structured analysis and use AI search to filter and summarise key moments across a dataset. As Bowen puts it, the platform gives researchers tools to "organise responses into structured analysis and use AI search to filter and summarise key moments." The result is a layer of analytical depth that complements what Qualzy already does - allowing researchers to interrogate their data in new ways without duplicating effort.
The integration is designed to be clean and practical. Data collected and processed in Qualzy - including transcripts, key points, and participant submissions - can be exported and brought into CoLoop's environment, where CoLoop's analytical capabilities take over. Two strong tools in their respective areas, working together rather than each trying to do everything.
Shared values around responsible AI
The reason this partnership made sense goes beyond complementary features. Both Qualzy and CoLoop take data protection seriously - not as a box-ticking exercise but as a fundamental part of how they operate. In a world where researchers are handling sensitive participant data, commercially confidential stimulus material, and often quite personal qualitative responses, the standards around data security can't be an afterthought.
CoLoop has achieved GDPR verification in Europe, along with HIPAA and SOC2 compliance in the US. Qualzy is ISO 27001 certified. Together, these credentials mean that researchers working across geographies or under strict client data governance requirements have a joined-up solution they can point to with confidence.
On the question of AI itself, Bowen's perspective is one we recognise: building AI features that researchers can actually trust requires more than technical sophistication. It requires restraint, testing, and a willingness to say "not yet" when the output isn't good enough. "The secret is refining them," Bowen notes of AI features - "they have to be something that is easy to trust." That's a principle Qualzy has operated by from the start, and it's one reason the conversation between our teams felt productive from the beginning.
What this means for researchers
In practical terms, this integration gives researchers access to a richer toolkit without the fragmentation that often comes from using multiple disconnected tools. The fieldwork and engagement layer - structuring activities, managing participant communities, collecting responses at scale, and letting Qualzy's AI process each submission as it arrives - stays in Qualzy, where it works well. The deeper analytical layer, including CoLoop's AI search and structured content organisation, picks up where Qualzy leaves off.
The combination supports richer insight discovery without displacing researcher judgement at any point. Both platforms are designed around the principle that AI should give researchers better raw material and more efficient pathways through data - not remove the researcher from the loop. Decisions about what a finding means, which themes matter most, and how to tell the story still rest with the human.
For researchers who have been cautious about AI - uncertain whether any of it is ready for serious professional use - this kind of pairing might be a useful entry point. Bowen's encouragement is characteristically measured and worth repeating: "Start exploring what AI means for you - there is huge potential out there to discover new ways to bring value to clients."
We'd agree. And with Qualzy and CoLoop working together, there are now more ways to do that than before.
