Data and AI for public sector and non-profit
Public sector and non-profit organisations often hold data of real social value under tight budget, privacy and transparency constraints — where the method has to be explainable to people who are not analysts.
Clients in this sector: CMHA
What usually gets in the way
- Data spread across programmes, regions and legacy systems with no common identity
- Privacy obligations for vulnerable populations that constrain analysis
- Reporting obligations to funders and the public on fixed schedules
- Limited internal analytics capacity and constrained budgets
- Findings that must be defensible in public, not merely statistically sound
What we build
- Programme and service data integration across regions and systems
- Outcome and impact reporting pipelines for funders and boards
- Demand and service-utilisation forecasting for planning
- De-identification and safe-release methods for published data
- Analytics tooling non-specialist staff can operate without us
How we handle the constraints
Findings need to withstand public scrutiny, so method transparency matters as much as accuracy. We favour approaches that can be explained plainly, and we build for handover — the goal is your team running it, not a permanent dependency.
Ways to work with us
Fixed-scope build
Defined deliverable · weeks to months
The problem is well understood and you want it solved without opening a hiring req.
Embedded senior team
Ongoing · alongside your people
You have a capable team that is short on senior capacity, not on direction.
Advisory and roadmap
Assessment · sequenced plan
There are several plausible directions and the cost of picking the wrong one is high.
Build and run
Delivery · then ongoing operation
The system matters but does not justify hiring a permanent team to maintain it.
Common questions
We have a small team and a fixed budget. Is that workable?
Yes, and it usually shapes the engagement toward a fixed scope with an explicit handover, so the thing keeps running once we step back.
How do you handle data about vulnerable populations?
Minimum necessary access, de-identification wherever the question permits it, and aggregation thresholds on anything published. These are design constraints from day one, not a review at the end.
Working on something in public sector?
Describe the problem in a couple of sentences. If we're not the right people for it, we'll tell you who is.