Data Druid is a decision intelligence company. We connect the data your organisation already holds, model the decisions that matter most, and put the evidence in front of the people who make them. Every recommendation is governed and every choice is on the record. In production across agriculture, government and education.
Government
Development
Agriculture
Geospatial technology
Events & hospitality
Education
Health and wellness
Education
Government
Development
Agriculture
Geospatial technology
Events & hospitality
Education
Health and wellness
Education
Each capability we ship feeds the same loop, from the data a decision stands on to the record of what was decided. AI recommends inside that loop. People decide.
The governed data model every decision stands on: one source of truth, an identity layer and an audit spine. Secured by default and yours to run.
The data every decision stands on, reconciled in one place.
Evidence delivered inside the workflow, where the decision happens.
The evidence a decision needs, from the data and from the map.
Systems secure enough that the decisions made on them hold up.
Models that recommend. People who decide.
The infrastructure that keeps the evidence there when it's needed.
A technology direction you can commit to, and the people to carry it.
Every engagement runs the same way, in the open. The steps below are the ones we hold ourselves to, and the ones you can hold us to.
We start with how your organisation actually works — operations, data, constraints, and the decision the system has to support. We name the threat surface in the same breath. You leave with a written scope, a delivery plan, and a fixed view of what done looks like.
We engineer the system around your processes, not a template — data systems, software, analytics or GIS, delivered on AWS, Azure or Google Cloud. APIs and middleware keep it interoperable with what you already run.
Security by design, not a closing checkbox: least-privilege access, encryption where it matters, audit logging, and penetration testing before launch. We instrument the system so you can see it running and measure it.
We hand over to people who can run the system without us — documentation, training and capacity-building — then keep it healthy under clear SLAs. We reply within one business day.
Every write goes through four checkpoints before it lands. Nothing moves in the dark; every decision is reversible, attributable, and timestamped to the second.
Governance and security are built in from the start, so every recommendation traces back to its data and every decision to the person who made it. Auditable by default, secure by design, and yours to run.
# the AI proposes, a human approves, then it runs def run(query, actor): plan = ai.propose(query) # never writes directly audit.log(actor, plan, level="proposed") if not approvals.granted(plan): return Pending(plan) # held for review result = db.execute(plan, scope=actor.rbac) return Signed(result) # traceable, reversible
Safe, auditable AI on the databases institutions already run on.
Live operational intelligence for agribusiness at scale.
Turning national registries into instant, privacy-safe intelligence.
Reaching the records the registry never could — even fully offline.
Marketplaces and commerce platforms, built with partners.
Learning platforms engineered to run on minimal hardware.
Cooperative, accounting and financial systems.
Clinical and facility data systems built for low-connectivity settings.
Productised systems we build once and give out.
End-to-end training delivery and accountable participant payments.
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Read post →Tell us the decision your team finds hardest to make well. We'll map what it needs and reply within one business day.
I'm Elenchus. I ask a few questions so the team understands your situation before we talk. I won't try to solve it here.
Question 1
