- Too many interviews, case studies, notes, or submissions to review manually.
- Evidence is spread across PDFs, spreadsheets, folders, transcripts, emails, and draft documents.
- Quotes are useful but hard to trace back to the source.
- Findings are not clearly linked to supporting evidence.
- Recommendations are written before the evidence base is organised.
- Public submissions or open-text survey responses need coding, grouping, and review.
- Report writers cannot find evidence quickly, and reviewers ask where a claim came from.
- AI outputs are hard to trust because the source structure is weak.
- Senior consultants spend too much time searching, checking, copying, pasting, and rebuilding tables.
Traceable Evidence Workflow Support
Turn messy source material into structured, report-ready evidence. I help research, evaluation, policy, public-sector, and donor-funded teams turn interviews, submissions, survey comments, workshop notes, case studies, fieldwork material, documents, and reports into traceable evidence systems.
The problem
The problem this solves
Evidence-heavy projects often slow down in the middle. The team may have strong interviews, useful submissions, detailed case studies, workshop notes, policy material, survey responses, reports, and fieldwork records, but the process becomes heavy when it is time to analyse, synthesise, write, and review.
Who this is for
Who this is for
This service is built for teams that already have useful information but need a better way to structure, analyse, review, and use it.
Research teams, evaluation firms, public policy consultants, public-sector project teams, and government departments.
Donor-funded contractors, UNICEF, UN, and development-sector consultants, programme teams, monitoring and evaluation teams, NGOs, and NPOs.
Report writers, social research teams, public consultation teams, and teams handling interviews, survey comments, field notes, case studies, or submissions.
Related services
Where this connects
This is the main evidence workflow service. It often sits between better intake and stronger data-use outputs.
Data Collection & Intake Systems
Use this before the evidence workflow when the source material is still being collected and the intake process needs forms, source IDs, upload rules, and a cleaner landing place.
View Data Collection & Intake SystemsData Use, Reporting & Communication Systems
Use this after the evidence workflow when the structured material needs to become reports, dashboards, apps, public pages, decks, or decision-support tools.
View Data Use, Reporting & Communication SystemsSource material
Source material this can support
The workflow is useful when source material needs to become coded evidence, synthesis, findings, recommendations, and report-ready outputs.
interviews
focus group notes
case studies
public submissions
stakeholder comments
open-text survey responses
fieldwork notes
workshop outputs
policy documents
programme reports
monitoring data
donor reporting material
research documents
review comments
mixed qualitative and quantitative evidence
What this is not
The service keeps expert judgement visible
My role is to make the information easier to capture, organise, analyse, review, and report from.
I do not sell generic AI tools.
I do not replace researchers, evaluators, policy specialists, report writers, or project teams.
I do not make final decisions for clients.
I do not provide formal legal, financial, medical, or policy advice.
I do not use AI to invent answers or hide weak evidence.
I do not produce unchecked outputs that cannot be traced back to source material.
I do not build overcomplicated software where a practical spreadsheet, database, form, automation, or AI-supported workflow will solve the actual problem.
What I build
What I build
I build the working evidence layer between raw source material and final outputs. The exact system depends on the source material, tools, team, deadline, confidentiality rules, and output needed.
Depending on the project, this can include source registers, respondent trackers, file and folder structures, source IDs, document IDs, interview IDs, participant IDs, submission IDs, coding frameworks, extraction templates, evidence databases, quote banks, claim trackers, issue matrices, synthesis tables, findings matrices, recommendation support tables, AI prompt libraries, custom GPTs or AI assistants, QA checklists, review trackers, report section notes, handover notes, and SOPs.
The goal is not to build structure for its own sake. The goal is to give the team material they can actually use.
Workflow snapshot
Turn messy source material into report-ready evidence.
Best when interviews, submissions, documents, notes, case studies, or comments need source IDs, coding, quote banks, synthesis, and review.
How the work moves
How I work
The work starts by understanding the source material and output, then building the evidence structure that lets the team analyse, write, review, and hand over the work.
Understand the source material and output
I start by understanding what the team has and what the material needs to become, including source types, volume, formats, tools, deadlines, report requirements, review needs, sensitivity, team workflow, and required outputs.
Design the evidence structure
I design the structure that will hold the evidence: fields, IDs, categories, statuses, review notes, quote fields, source links, and output tabs.
Build the working database
I build the spreadsheet, database, tracker, or source system that the team will use as the working layer between source material and output.
Add AI support where useful
If AI will help, I add it carefully through extraction prompts, summary prompts, classification prompts, quote pulling, comparison prompts, or a custom GPT.
Process and structure the material
I help move the source material into the evidence system through coding, extraction, quote tracking, theme tagging, summary fields, and review flags.
Prepare synthesis and report-ready outputs
Once the material is structured, I help create synthesis tables, findings notes, quote banks, recommendation tables, review packs, and report section support.
Support review and handover
I help make sure the system is understandable, usable, and ready for handover through QA checks, SOPs, training notes, handover notes, and final review fields.
Deliverables
Typical deliverables
The exact deliverables depend on the project.
- workflow map
- source register
- folder structure
- file naming rules
- data dictionary
- coding framework
- evidence database
- quote bank
- AI prompt library
- custom GPT or AI assistant
- extraction templates
- synthesis tables
- findings matrix
- recommendations support table
- public submission matrix
- open-text response analysis table
- report section notes
- QA checklist
- review tracker
- SOP
- handover notes
- training call
Before and after
How the workflow helps
A report can be delayed not because the team cannot write, but because the evidence is not ready to write from. That is the core problem this service solves.
Before
The team searches manually for quotes, claims, issues, and findings.
After
Source IDs, respondent fields, file links, quote IDs, and review notes make the source trail visible.
Before
Writers work from folders full of raw material.
After
Writers get structured evidence, quote options, theme summaries, findings notes, recommendation support tables, and review flags.
Before
AI outputs are hard to check because the source structure is weak.
After
AI works inside approved sources, defined fields, prompt rules, output formats, and human review points.
Where this fits
Common use cases
The strongest fit is usually a team dealing with too much qualitative material, weak source traceability, review pressure, report writers who cannot find evidence quickly, AI interest without enough structure, or a deadline that is getting closer.
Research and evaluation projects
Structure interviews, focus group notes, survey comments, case studies, and documents so the team can code material, extract quotes, compare themes, and prepare report-ready outputs.
Public consultation and policy work
Turn submissions, stakeholder comments, review notes, and consultation material into a coded evidence base with themes, issue matrices, source links, response notes, and drafting support.
Donor-funded reporting
Structure fieldwork material, programme updates, case studies, partner reports, and reporting evidence so donor reports are easier to prepare, check, and support.
Situation analysis support
Build the evidence layer for source retrieval, recommendations, coded entries, quote tracking, and drafting when analysis, recommendations, and report writing need to move in parallel.
Open-text survey analysis
Classify responses, extract themes, flag useful quotes, compare by respondent group, and prepare synthesis outputs.
Internal knowledge and document retrieval
Prepare reports, strategy documents, meeting notes, internal guidance, and project material for structured retrieval and controlled AI knowledge-base use where useful.
Careful AI use
AI-assisted extraction and review
I use AI where it helps, but I do not treat AI as the final authority.
Where AI can help
AI can support first-pass extraction, suggested codes, theme identification, open-text summaries, candidate quotes, comparison across groups, draft synthesis notes, gap flags, first-pass tables, and structured evidence queries.
What AI needs around it
AI outputs need approved source material, clear prompts, defined fields, source IDs, quote requirements, review flags, human checks, output templates, and limitations notes.
Why the structure matters
The point is not to say AI has analysed the project. The point is to reduce repetitive extraction and sorting while keeping human judgement, source checking, and review visible.
Client inputs
What clients need to provide
If these are not ready, part of the work can be to help define them.
source material
current spreadsheets or trackers
research questions or evaluation questions
report outline, where available
proposal or methodology, where available
coding framework, if already agreed
examples of desired outputs
confidentiality rules
tool access
team roles
deadlines
review requirements
donor, client, or public-sector requirements, where relevant
Proof
Related case studies
Related work shows the same core pattern: source material, coded evidence, synthesis, drafting support, and review need to stay connected.
Calculators
Use these tools if you need to diagnose the workflow first
The strongest calculator fit depends on where the pressure sits: search, capacity, traceability, reporting drag, or knowledge-base value.
Related reading
Useful guides before you scope the work
These articles explain the thinking behind the service and the adjacent workflow problems.
Frequently asked questions
Questions before you enquire
Do you replace our research or evaluation team?
No.
Your team keeps responsibility for research design, subject-matter interpretation, stakeholder judgement, evaluation conclusions, policy advice, client relationships, final recommendations, and sign-off.
I support the evidence workflow underneath that work.
Can you work behind a lead consultant or primary contractor?
Yes.
This is often the best fit. The lead consultant or contractor keeps the client relationship and subject-matter lead. I support the source structure, evidence database, coding workflow, quote tracking, AI-assisted extraction, synthesis tables, report-ready evidence, review flags, and handover documentation.
Can this work with our current tools?
Usually, yes.
The system can often be built in Google Sheets, Excel, Airtable, Google Drive, Microsoft 365, SharePoint, or another agreed environment.
The tool should fit the team, access rules, budget, and handover requirements.
Do you use AI?
Yes, where it has a clear job.
AI can help with extraction, classification, comparison, summary, quote identification, retrieval, and drafting support.
It does not replace human review.
Can you help if the report is already behind?
Yes, depending on the source material and timeline.
In a report recovery situation, I usually focus on the fastest route to a usable evidence structure, synthesis outputs, quote options, findings support, and review flags.
The aim is to make the evidence easier to use under deadline pressure.
Can you help before the project starts?
Yes.
I can help build the evidence workflow method before the material arrives, or support a proposal by strengthening the planned approach to coding, source traceability, synthesis, AI use, review, and report outputs.
Let's talk
Start with the evidence workflow
If your team has source material spread across interviews, submissions, survey comments, workshop notes, PDFs, spreadsheets, reports, case studies, fieldwork material, or draft documents, send the source types, current tools, volume, deadline, output needed, traceability needs, AI context, and review process. I will help you work out the most practical next step.