Case Studies: Evidence and Reporting Systems for Large-Scale Projects
Case Studies: Evidence and Reporting Systems for Large-Scale Projects
Case Studies: Evidence and Reporting Systems for Large-Scale Projects
A curated library of real projects where I built customised data capture, automation, evidence synthesis, and reporting workflows for policy, research, and programme delivery teams.
A curated library of real projects where I built customised data capture, automation, evidence synthesis, and reporting workflows for policy, research, and programme delivery teams.
A curated library of real projects where I built customised data capture, automation, evidence synthesis, and reporting workflows for policy, research, and programme delivery teams.
In high-stakes environments, the bottleneck is rarely “more data”. It is turning messy inputs into structured evidence, defensible insights, and standards-aligned outputs with audit trail and traceability.
In high-stakes environments, the bottleneck is rarely “more data”. It is turning messy inputs into structured evidence, defensible insights, and standards-aligned outputs with audit trail and traceability.
In high-stakes environments, the bottleneck is rarely “more data”. It is turning messy inputs into structured evidence, defensible insights, and standards-aligned outputs with audit trail and traceability.
Featured & Latest Case Studies
Start here: the most relevant proof for agencies and delivery teams.
These projects show the same pattern: capture → structure → analyse → report → reuse. Explore examples including policy-scale submissions analysis, audit-ready qualitative evidence systems, and automated intake tools that compute insights and trigger workflows.
TheFutureMe (TFM), a systems-first wellness score for real life
LGWP26 Case Study: Turning 270 Submissions into a Traceable Evidence Base
08 Sept 2025
UNICEF AI Case Study: Child Poverty Study (Zambia)
08 Sept 2025
Newsletter: Evidence systems and reporting workflows
You’ll get: workflow patterns, templates, QA checklists, and examples from real projects (without the noise).
Short, practical notes on building data capture pipelines, audit-ready evidence bases, AI-assisted synthesis guardrails, and standards-aligned reporting outputs for policy, research, and programme delivery teams.
Best for agencies, consultancies, implementing partners, and government-adjacent delivery teams.
Explore All Case Studies
Browse projects by service line, data type, and reporting output. Each case study focuses on the system built, governance approach, and deliverables produced.
Case Study: TheFutureMe Wellness Score & Systems-First Habits
Digital Brand Building Case Study: Creating Craft Cask
20 Jun 2025
LGWP26 Case Study: AI-Assisted Evidence Synthesis (SA)
08 Sept 2025
UNICEF AI Case Study: Child Poverty Study Evidence Workflow
08 Sept 2025
FAQs: Case Studies and Delivery Systems
Quick answers for teams evaluating a customised capture and reporting workflow.
Plain‑English guidance on which guides to read first, where to find free tools, and how these resources support funding and strategy. Deep‑link into the hubs below for more detail.
What types of projects do these case studies represent?
They cover policy, research, and programme delivery work where teams face high-volume inputs and tight reporting cycles. Typical examples include consultation submissions, qualitative case studies, interviews, and operational datasets that must be turned into defensible outputs.
What is an “audit-ready evidence base”?
An audit-ready evidence base is a structured database where outputs can be traced back to the source. In practice, this means clear record IDs, a data dictionary, QA checks, and source traceability (e.g., quote references or document links) so findings are defensible during review.
Do you build the full system or only parts of it?
Both. Some teams only need the Data Capture & Automation Engine (intake, forms, pipelines, routing). Others need the Evidence, Insight & Reporting Engine (coding, synthesis, reporting outputs). For larger projects, I combine both into a full Capture → Analyse → Report system.
How do you use AI without risking unreliable outputs?
AI is used with guardrails and human review. Workflows typically require supporting evidence (quotes/fields), flag ambiguity, enforce schemas, and include QA checks. The goal is speed and consistency without sacrificing traceability.
Can you work as a subcontractor to an agency or consultancy?
Yes. Subcontracting is a strong fit. I can own the evidence workflow workstream, align to your reporting standard, and deliver handover-ready outputs (SOPs, templates, and training) so your team can run the system.
Featured & Latest Case Studies
Start here: the most relevant proof for agencies and delivery teams.
These projects show the same pattern: capture → structure → analyse → report → reuse. Explore examples including policy-scale submissions analysis, audit-ready qualitative evidence systems, and automated intake tools that compute insights and trigger workflows.
TheFutureMe (TFM), a systems-first wellness score for real life
LGWP26 Case Study: Turning 270 Submissions into a Traceable Evidence Base
08 Sept 2025
UNICEF AI Case Study: Child Poverty Study (Zambia)
08 Sept 2025
Newsletter: Evidence systems and reporting workflows
You’ll get: workflow patterns, templates, QA checklists, and examples from real projects (without the noise).
Short, practical notes on building data capture pipelines, audit-ready evidence bases, AI-assisted synthesis guardrails, and standards-aligned reporting outputs for policy, research, and programme delivery teams.
Best for agencies, consultancies, implementing partners, and government-adjacent delivery teams.
Explore All Case Studies
Browse projects by service line, data type, and reporting output. Each case study focuses on the system built, governance approach, and deliverables produced.
Case Study: TheFutureMe Wellness Score & Systems-First Habits
LGWP26 Case Study: AI-Assisted Evidence Synthesis (SA)
08 Sept 2025
UNICEF AI Case Study: Child Poverty Study Evidence Workflow
08 Sept 2025
Digital Brand Building Case Study: Creating Craft Cask
20 Jun 2025
Frequently Asked Questions (FAQs) About Civil Society Organisations
Quick answers for teams evaluating a customised capture and reporting workflow.
Plain‑English guidance on which guides to read first, where to find free tools, and how these resources support funding and strategy. Deep‑link into the hubs below for more detail.
What types of projects do these case studies represent?
They cover policy, research, and programme delivery work where teams face high-volume inputs and tight reporting cycles. Typical examples include consultation submissions, qualitative case studies, interviews, and operational datasets that must be turned into defensible outputs.
What is an “audit-ready evidence base”?
An audit-ready evidence base is a structured database where outputs can be traced back to the source. In practice, this means clear record IDs, a data dictionary, QA checks, and source traceability (e.g., quote references or document links) so findings are defensible during review.
Do you build the full system or only parts of it?
Both. Some teams only need the Data Capture & Automation Engine (intake, forms, pipelines, routing). Others need the Evidence, Insight & Reporting Engine (coding, synthesis, reporting outputs). For larger projects, I combine both into a full Capture → Analyse → Report system.
How do you use AI without risking unreliable outputs?
AI is used with guardrails and human review. Workflows typically require supporting evidence (quotes/fields), flag ambiguity, enforce schemas, and include QA checks. The goal is speed and consistency without sacrificing traceability.
Can you work as a subcontractor to an agency or consultancy?
Yes. Subcontracting is a strong fit. I can own the evidence workflow workstream, align to your reporting standard, and deliver handover-ready outputs (SOPs, templates, and training) so your team can run the system.
Featured & Latest Case Studies
Start here: the most relevant proof for agencies and delivery teams.
These projects show the same pattern: capture → structure → analyse → report → reuse. Explore examples including policy-scale submissions analysis, audit-ready qualitative evidence systems, and automated intake tools that compute insights and trigger workflows.
TheFutureMe (TFM), a systems-first wellness score for real life
LGWP26 Case Study: Turning 270 Submissions into a Traceable Evidence Base
08 Sept 2025
UNICEF AI Case Study: Child Poverty Study (Zambia)
08 Sept 2025
Newsletter: Evidence systems and reporting workflows
You’ll get: workflow patterns, templates, QA checklists, and examples from real projects (without the noise).
Short, practical notes on building data capture pipelines, audit-ready evidence bases, AI-assisted synthesis guardrails, and standards-aligned reporting outputs for policy, research, and programme delivery teams.
Best for agencies, consultancies, implementing partners, and government-adjacent delivery teams.
Explore All Case Studies
Browse projects by service line, data type, and reporting output. Each case study focuses on the system built, governance approach, and deliverables produced.
Case Study: TheFutureMe Wellness Score & Systems-First Habits
LGWP26 Case Study: AI-Assisted Evidence Synthesis (SA)
08 Sept 2025
UNICEF AI Case Study: Child Poverty Study Evidence Workflow
08 Sept 2025
Digital Brand Building Case Study: Creating Craft Cask
20 Jun 2025
Frequently Asked Questions (FAQs) About Civil Society Organisations
Quick answers for teams evaluating a customised capture and reporting workflow.
Plain‑English guidance on which guides to read first, where to find free tools, and how these resources support funding and strategy. Deep‑link into the hubs below for more detail.
What types of projects do these case studies represent?
They cover policy, research, and programme delivery work where teams face high-volume inputs and tight reporting cycles. Typical examples include consultation submissions, qualitative case studies, interviews, and operational datasets that must be turned into defensible outputs.
What is an “audit-ready evidence base”?
An audit-ready evidence base is a structured database where outputs can be traced back to the source. In practice, this means clear record IDs, a data dictionary, QA checks, and source traceability (e.g., quote references or document links) so findings are defensible during review.
Do you build the full system or only parts of it?
Both. Some teams only need the Data Capture & Automation Engine (intake, forms, pipelines, routing). Others need the Evidence, Insight & Reporting Engine (coding, synthesis, reporting outputs). For larger projects, I combine both into a full Capture → Analyse → Report system.
How do you use AI without risking unreliable outputs?
AI is used with guardrails and human review. Workflows typically require supporting evidence (quotes/fields), flag ambiguity, enforce schemas, and include QA checks. The goal is speed and consistency without sacrificing traceability.
Can you work as a subcontractor to an agency or consultancy?
Yes. Subcontracting is a strong fit. I can own the evidence workflow workstream, align to your reporting standard, and deliver handover-ready outputs (SOPs, templates, and training) so your team can run the system.
Book a 20-minute scoping call with Romanos
Book a 20-minute scoping call to map your reporting requirements, data reality, and delivery risks. You’ll leave with a recommended scope (Capture Engine, Evidence & Reporting Engine, or full system) and next steps.
Helping agencies, consultancies, and delivery teams turn raw inputs into structured evidence and reporting-ready outputs.
Book a 20-minute scoping call with Romanos
Book a 20-minute scoping call to map your reporting requirements, data reality, and delivery risks. You’ll leave with a recommended scope (Capture Engine, Evidence & Reporting Engine, or full system) and next steps.
Helping agencies, consultancies, and delivery teams turn raw inputs into structured evidence and reporting-ready outputs.
Book a 20-minute scoping call with Romanos
Book a 20-minute scoping call to map your reporting requirements, data reality, and delivery risks. You’ll leave with a recommended scope (Capture Engine, Evidence & Reporting Engine, or full system) and next steps.
Helping agencies, consultancies, and delivery teams turn raw inputs into structured evidence and reporting-ready outputs.
Kickstart a project today!
Kickstart a project today!