Evidence foundations
Bringing fragmented data and documents together into reliable, well-documented evidence that your organisation can continue to use.
Data science for charities and civil society
Better decisions
when the evidence
is messy.
Orelian builds the evidence, analytical methods and decision tools that help charities, funders and public bodies understand what is changing and decide what to do next.
Who we help
Better evidence for organisations working for public good.
Charities and civil society organisations make difficult choices with limited time, imperfect information and real consequences. Orelian helps them find insight in complex evidence and build practical tools for decisions that matter.
Also working withFundersResearchersPublic bodies
Analysis for important decisions
Answering focused questions about need, reach, outcomes, resources and risk, with assumptions and uncertainty made clear.
Decision tools
Turning evidence and analysis into useful workflows, monitoring systems and responsible AI tools that work in practice.
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Understanding fragmented evidence
Connecting information spread across internal systems, accounts, registers, grants, reports and other sources that were never designed to work together.
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Finding insight in complex documents
Turning reports, notes, submissions, free text and images into structured evidence while keeping findings traceable to their source.
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Seeing change earlier
Building timely indicators when conventional reporting is incomplete, spread across systems or arrives too late to guide action.
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Making resource decisions more defensible
Understanding need, reach, gaps, trade-offs and risk so that limited time and money can be directed where they can do most good.
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Learning what works
Combining evaluation, causal analysis and operational evidence to understand whether an intervention changed what it was meant to change.
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Building responsible data and AI tools
Creating maintainable tools with visible uncertainty, proportionate human review and clear provenance for use in day-to-day decisions.
02 Selected work
Work that survives contact with reality.
Charity sector evidence
Improving UK-CAT accuracy with machine learning
Improving the accuracy of UK-CAT – a national charity classification system – by training multi-label ML models that tripled classification accuracy over the keyword-matching baseline.
Read the case study Complex document analysisLearning from coroners' reports at scale
Extracting structured insight from thousands of unstructured coroners' reports to accelerate public health learning and surface preventable patterns of death.
Read the case study Clinical Decision SupportSmarter SSRI prescription management
An interactive tool that maps how different antidepressants bind to neuroreceptors, helping clinicians make evidence-informed switching decisions rather than cycling through drugs by trial and error.
Read the case study03 What to expect
Four steps. No black boxes.
Scope
Understand the decision, the constraints and what good looks like before writing a line of code.
Build
Develop the right-sized solution: models, tools, or frameworks shaped to your data and operating reality.
Validate
Test against real conditions, stress assumptions, and confirm it works for the people who'll use it.
Transfer
Hand over clean documentation, trained teams, and systems your organisation can run without us.
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Fit the context
We design around your team, workflows, and incentives. Solutions are shaped to work in practice from day one.
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Right-sized solutions
The best approach is the one that actually gets used. We don't pick the most advanced option for the sake of it.
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Uncertainty is a feature
We make uncertainty visible. Honest ranges and clear assumptions lead to better decisions than false precision.
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Built to operate, not to demo
Everything we deliver is designed for the people who'll run it on Monday morning, not just the stakeholders who see it on Friday.
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Make us unnecessary
If you need us forever, we've done something wrong. We focus on transfer, documentation, and simplicity so your team can own the work.
05 Founder-led by design
“The best analytical work does more than produce an answer. It helps people see a decision differently.”
Sam founded Orelian to bring together two ways of seeing. His background in social science and doctoral research in data science mean he can go deep into technically demanding work without losing sight of the systems, people and consequences behind it.
Orelian grew from a belief that civil society should have more room for ambition, even when difficult operating conditions keep pulling leaders towards survival. Sam helps organisations make hopeful, demanding ideas tangible and build them to work in the real world.
Orelian is founder-led. Sam remains involved from framing the question through to delivery, keeping responsibility for the thinking and the outcome in the same hands.
LiverpoolWorking across the UKRemote and on site
06 Start with the decision
Have an important question that your existing evidence cannot answer?
Tell us about the decision, the evidence available and where the uncertainty lies. We can help work out the right next step.