History & Projects
Our AI work is built on 36 years of asking how data should be stored when the people who need it don’t know in advance what they’ll need.
1989: the question that started it
Azquo’s development began over 35 years ago. Bill Cawley was given the task of defining the basis of an expert system for marketing — this was the mid-1980s, when expert systems were considered the future of computing.
Two things became clear early in the research. First, marketers rarely know at the outset of a project exactly what data they will require — and that data is likely to change as the work develops. Second, the spreadsheet was already the dominant analytical tool for business users, and any solution that ignored it would be ignored in return.
Bill concluded that the prerequisite for any expert system was a database fundamentally more accessible than the relational databases of the time: one that would accept any data at any time without needing to call in IT, and that could transfer data to and from a spreadsheet seamlessly.
Now, an AI layer on the same foundation
The foundation that emerged — flexible storage, no schema migrations, provenance on every value, two-way Excel — turns out to be exactly what AI agents need. We are currently developing an AI layer that handles the two tasks that until now required Azquo-specific knowledge: mapping incoming data into the right hierarchy, and generating report templates from natural-language requests.
The goal is that Azquo’s flexible, auditable, spreadsheet-native data model becomes accessible without any learning curve. Users load their data, ask questions of it in plain language, and get live Excel reports connected to a fully provenanced database.
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The Team
Azquo remains a small, focused team: Bill Cawley and his son Edd, together with two colleagues, Ed, who liaises with customers, and Nick, who specifically understands insurance, based in Ludlow, Shropshire.
The team works directly with clients, building and adapting Azquo deployments to fit each organisation’s specific data challenges. We are actively looking for businesses that can exploit this unique database — organisations where conventional data tools are too rigid, too slow to adapt, or too dependent on IT specialists.