The Model
Cire crafts bespoke engineering solutions for research organisations with different needs
We work with academic groups and research funding bodies at the same time, and start with the principal investigator from the proposal phase. A research engineer is then embedded in the group as a Discovery Pair, so the engineering capacity is planned into the project rather than improvised later.
Why not the support frameworks already in place?
IT support answers to multiple research groups, so there is no good way to prioritise tasks. Frequent context switching brings efficiency down.
Staff scientists cost the team constantly, have their own projects to run, and many end up taking on admin work instead.
Data scientists focus on data analysis, which is exactly what scientists want to do themselves. There is little complementary synergy.
We advocate for a vertical structure of engineering support, because it allows a deeper and more dedicated level of collaboration. A research engineer joins the group for 6 to 12 months, and the contract can be paused while the project waits for data.
For startups and focused research organisations, we work with the funders behind them, including venture capital, philanthropic foundations and government programmes. Cire is the equivalent of a fund, but it invests research engineers rather than capital.
A research engineer arrives on a fixed contract as a “CTO in a box” and transfers the engineering knowledge the organisation needs to keep.
We also reach clients through solution providers expanding into scientific research, including AI model providers and cloud computing platforms. Domain knowledge is the strength: research engineers fill the gap between the people who build the tool and the scientists who need to use it.
We do not lack new tools. We lack specialised engineers and the human power to operate them.
The first three paths are how Cire finds its clients. What we keep from that work is the asset that can scale.
Through collaborative working with research scientists and research groups, Cire accumulates hands-on experience of operating complex scientific analysis workflows. We distill these know-hows into an AI agent wrapper for each tool.
These wrappers are valuable to researchers in academia and industry alike. A group can operate, extend and customise a scientific analysis tool using encoded know-how, rather than depending on a specialist being present.