Services: Data Capture & Automation Engine + Evidence, Insight & Reporting Engine
Services: Data Capture & Automation Engine + Evidence, Insight & Reporting Engine
Services: Data Capture & Automation Engine + Evidence, Insight & Reporting Engine
I build customised systems that capture structured inputs, run workflow automation, and turn messy qualitative or quantitative data into traceable, standards-aligned reporting outputs (with audit trail and data governance built in).
I build customised systems that capture structured inputs, run workflow automation, and turn messy qualitative or quantitative data into traceable, standards-aligned reporting outputs (with audit trail and data governance built in).
I build customised systems that capture structured inputs, run workflow automation, and turn messy qualitative or quantitative data into traceable, standards-aligned reporting outputs (with audit trail and data governance built in).
Proven on policy-scale submission synthesis and donor-aligned research reporting workflows.
Proven on policy-scale submission synthesis and donor-aligned research reporting workflows.
Proven on policy-scale submission synthesis and donor-aligned research reporting workflows.
Who I work with
Who I work with
Best fit
Best fit
Research and evaluation agencies
Policy / management consultancies
Donor-funded implementing partners and consortia
Government-adjacent units and delivery entities
Agencies needing a subcontractor for the data + reporting workstream
Research and evaluation agencies
Policy / management consultancies
Donor-funded implementing partners and consortia
Government-adjacent units and delivery entities
Agencies needing a subcontractor for the data + reporting workstream
Not a fit
Not a fit
Logo / visual identity work
Fundraising advisory as a primary need
Low-budget “misc marketing support” retainers without system/reporting scope
Logo / visual identity work
Fundraising advisory as a primary need
Low-budget “misc marketing support” retainers without system/reporting scope
Not sure if it’s a fit? Send a brief
Who I work with
Best fit
Research and evaluation agencies
Policy / management consultancies
Donor-funded implementing partners and consortia
Government-adjacent units and delivery entities
Agencies needing a subcontractor for the data + reporting workstream
Not a fit
Logo / visual identity work
Fundraising advisory as a primary need
Low-budget “misc marketing support” retainers without system/reporting scope
Not sure if it’s a fit? Send a brief
What you can expect
What you can expect
Structured data capture tools (forms / calculators as needed)
Clean, standardised databases with a documented data dictionary
AI-assisted categorisation and synthesis (with review guardrails)
Insight interface (Custom GPT) to query and reuse the evidence base
Standards-aligned reporting outputs (tables, summaries, draft sections)
Governance built-in: QA checks, versioning, source traceability
Handover pack: SOP + training for your team
Access control + confidentiality approach (work within your environment where possible)
Templates mapped to your required standard (donor / policy / internal format)
Structured data capture tools (forms / calculators as needed)
Clean, standardised databases with a documented data dictionary
AI-assisted categorisation and synthesis (with review guardrails)
Insight interface (Custom GPT) to query and reuse the evidence base
Standards-aligned reporting outputs (tables, summaries, draft sections)
Governance built-in: QA checks, versioning, source traceability
Handover pack: SOP + training for your team
Access control + confidentiality approach (work within your environment where possible)
Templates mapped to your required standard (donor / policy / internal format)
What you can expect
Structured data capture tools (forms / calculators as needed)
Clean, standardised databases with a documented data dictionary
AI-assisted categorisation and synthesis (with review guardrails)
Insight interface (Custom GPT) to query and reuse the evidence base
Standards-aligned reporting outputs (tables, summaries, draft sections)
Governance built-in: QA checks, versioning, source traceability
Handover pack: SOP + training for your team
Access control + confidentiality approach (work within your environment where possible)
Templates mapped to your required standard (donor / policy / internal format)
How it works
How it works
Scoping (objectives, standards, constraints, stakeholders)
System design (data schema, taxonomy, workflow map)
Build (capture tools, database, automations, AI workflows)
QA + traceability (checks, versioning, audit notes)
Handover (SOP + training + recommended next steps)
Scoping (objectives, standards, constraints, stakeholders)
System design (data schema, taxonomy, workflow map)
Build (capture tools, database, automations, AI workflows)
QA + traceability (checks, versioning, audit notes)
Handover (SOP + training + recommended next steps)
How it works
Scoping (objectives, standards, constraints, stakeholders)
System design (data schema, taxonomy, workflow map)
Build (capture tools, database, automations, AI workflows)
QA + traceability (checks, versioning, audit notes)
Handover (SOP + training + recommended next steps)
Relevant case studies
Relevant case studies
TheFutureMe — Lifestyle Audit calculator (capture + automation)
Interactive tool that computes outputs, triggers follow-ups, and builds a clean dataset.
UNICEF — FHH Zambia child poverty study analysis workflow
Standardised coding + audit trail that reduced rework and improved consistency.
SA Government — Local Government White Paper evidence synthesis
High-volume public inputs → structured database → quantified synthesis → drafting-ready outputs.
Relevant case studies
TheFutureMe — Lifestyle Audit calculator (capture + automation)
Interactive tool that computes outputs, triggers follow-ups, and builds a clean dataset.
UNICEF — FHH Zambia child poverty study analysis workflow
Standardised coding + audit trail that reduced rework and improved consistency.
SA Government — Local Government White Paper evidence synthesis
High-volume public inputs → structured database → quantified synthesis → drafting-ready outputs.
Service options
Service options
Capture & Automation Engine
Capture & Automation Engine
Capture → compute → route (automated)
Capture → compute → route (automated)
Who it’s for: Teams who need structured intake and automated follow-up.
Who it’s for: Teams who need structured intake and automated follow-up.
Outcomes
Outcomes
Clean, standardised inputs from day one
Instant scoring / categorisation outputs
Automated routing into your tools and comms
Clean, standardised inputs from day one
Instant scoring / categorisation outputs
Automated routing into your tools and comms
Deliverables
Deliverables
Framer custom form / calculator component (validation + clear UX)
Sheets calculation engine (rules, scoring, flags, outputs)
Zapier automations (Sheets, Brevo, CRM, other apps)
Admin view + QA checks + handover notes
Framer custom form / calculator component (validation + clear UX)
Sheets calculation engine (rules, scoring, flags, outputs)
Zapier automations (Sheets, Brevo, CRM, other apps)
Admin view + QA checks + handover notes
Typical timeline: 2–4 weeks (depending on complexity)
Typical timeline: 2–4 weeks (depending on complexity)
Evidence, Insight & Reporting Engine
Evidence, Insight & Reporting Engine
Raw inputs → structured evidence → reporting-ready outputs
Raw inputs → structured evidence → reporting-ready outputs
Who it’s for: Teams drowning in documents, submissions, or messy datasets.
Who it’s for: Teams drowning in documents, submissions, or messy datasets.
Outcomes
Outcomes
Faster synthesis and fewer revisions
Consistent categorisation across themes
Traceable, defensible insights for reporting
Faster synthesis and fewer revisions
Consistent categorisation across themes
Traceable, defensible insights for reporting
Deliverables
Deliverables
Data-to-database build + data dictionary
AI-assisted extraction / coding workflow + QA checks
Insight outputs (synthesis tables, theme summaries, counts where useful)
Reporting outputs aligned to required standards / templates
Data-to-database build + data dictionary
AI-assisted extraction / coding workflow + QA checks
Insight outputs (synthesis tables, theme summaries, counts where useful)
Reporting outputs aligned to required standards / templates
Typical timeline: 3–8 weeks (based on volume and deliverables)
Typical timeline: 3–8 weeks (based on volume and deliverables)
Insight Copilot (Custom GPT over your evidence base)
Insight Copilot (Custom GPT over your evidence base)
Self-serve insights for your team
Self-serve insights for your team
Who it’s for: Teams that need rapid answers without re-reading everything.
Who it’s for: Teams that need rapid answers without re-reading everything.
Outcomes
Outcomes
Faster internal insight generation
Better reuse of evidence across workstreams
Less dependence on a single analyst
Faster internal insight generation
Better reuse of evidence across workstreams
Less dependence on a single analyst
Deliverables
Deliverables
Custom GPT configured around your database + taxonomy
Guardrails + “insight recipes” (repeatable queries your team can trust)
Light team onboarding
Custom GPT configured around your database + taxonomy
Guardrails + “insight recipes” (repeatable queries your team can trust)
Light team onboarding
Typical timeline: 1–3 weeks
Typical timeline: 1–3 weeks
Report Writer System (Standards-aligned drafting workflow)
Report Writer System (Standards-aligned drafting workflow)
Drafting workflows that match project standards
Drafting workflows that match project standards
Who it’s for: Research / policy teams with tight reporting cycles and heavy review pressure.
Who it’s for: Research / policy teams with tight reporting cycles and heavy review pressure.
Outcomes
Outcomes
Faster draft production
Consistent structure and synthesis across sections
Clear evidence-to-claim linkage
Faster draft production
Consistent structure and synthesis across sections
Clear evidence-to-claim linkage
Deliverables
Deliverables
Report structure aligned to the required template / standard
Drafting workflow producing: key findings, synthesis tables, narrative sections
Review loop system (human-in-the-loop revision process)
Report structure aligned to the required template / standard
Drafting workflow producing: key findings, synthesis tables, narrative sections
Review loop system (human-in-the-loop revision process)
Typical timeline: 2–6 weeks
Typical timeline: 2–6 weeks
Service options
Capture & Automation Engine
Capture → compute → route (automated)
Who it’s for: Teams who need structured intake and automated follow-up.
Outcomes
Clean, standardised inputs from day one
Instant scoring / categorisation outputs
Automated routing into your tools and comms
Deliverables
Framer custom form / calculator component (validation + clear UX)
Sheets calculation engine (rules, scoring, flags, outputs)
Zapier automations (Sheets, Brevo, CRM, other apps)
Admin view + QA checks + handover notes
Typical timeline: 2–4 weeks (depending on complexity)
Evidence, Insight & Reporting Engine
Raw inputs → structured evidence → reporting-ready outputs
Who it’s for: Teams drowning in documents, submissions, or messy datasets.
Outcomes
Faster synthesis and fewer revisions
Consistent categorisation across themes
Traceable, defensible insights for reporting
Deliverables
Data-to-database build + data dictionary
AI-assisted extraction / coding workflow + QA checks
Insight outputs (synthesis tables, theme summaries, counts where useful)
Reporting outputs aligned to required standards / templates
Typical timeline: 3–8 weeks (based on volume and deliverables)
Insight Copilot (Custom GPT over your evidence base)
Self-serve insights for your team
Who it’s for: Teams that need rapid answers without re-reading everything.
Outcomes
Faster internal insight generation
Better reuse of evidence across workstreams
Less dependence on a single analyst
Deliverables
Custom GPT configured around your database + taxonomy
Guardrails + “insight recipes” (repeatable queries your team can trust)
Light team onboarding
Typical timeline: 1–3 weeks
Report Writer System (Standards-aligned drafting workflow)
Drafting workflows that match project standards
Who it’s for: Research / policy teams with tight reporting cycles and heavy review pressure.
Outcomes
Faster draft production
Consistent structure and synthesis across sections
Clear evidence-to-claim linkage
Deliverables
Report structure aligned to the required template / standard
Drafting workflow producing: key findings, synthesis tables, narrative sections
Review loop system (human-in-the-loop revision process)
Typical timeline: 2–6 weeks
Best for larger projects: Full Evidence & Reporting System
Best for larger projects: Full Evidence & Reporting System
Best for larger projects: Full Evidence & Reporting System
A complete workflow that runs Capture → Compute → Analyse → Report, designed for traceability, audit trail, and handover-ready documentation.
A complete workflow that runs Capture → Compute → Analyse → Report, designed for traceability, audit trail, and handover-ready documentation.
A complete workflow that runs Capture → Compute → Analyse → Report, designed for traceability, audit trail, and handover-ready documentation.
Deliverables
Deliverables
Deliverables
Capture & Automation Engine + Evidence, Insight & Reporting Engine
Optional Insight Copilot + Report Writer layer depending on scope
Capture & Automation Engine + Evidence, Insight & Reporting Engine
Optional Insight Copilot + Report Writer layer depending on scope
Capture & Automation Engine + Evidence, Insight & Reporting Engine
Optional Insight Copilot + Report Writer layer depending on scope
Frequently Asked Questions
1) Can you build an ETL pipeline to turn messy inputs into an analysis-ready database?
Yes. I design lightweight ETL pipelines (extract, transform, load) that convert PDFs, forms, spreadsheets, and documents into a clean, structured database. This includes a clear schema, validation rules, and a data dictionary so the evidence base stays consistent over time.
2) Do you do intelligent document processing (IDP) or PDF data extraction for research and policy work?
Yes. When inputs arrive as documents (PDFs, Word files, submissions), I build an intelligent document processing workflow to extract key fields, classify content, and organise it into a searchable evidence base. The goal is faster synthesis without losing traceability back to the original source.
3) Can you create a codebook / coding framework for qualitative analysis so multiple analysts code consistently?
Yes. For qualitative projects, I can design a codebook (coding framework) that defines themes, inclusion/exclusion rules, and examples. This improves inter-coder consistency, makes synthesis easier, and helps teams defend findings in reviews.
4) Do you build RAG / knowledge base chatbots so teams can query internal evidence and documents?
Yes. If you want your team to query an internal evidence base in plain English, I can build a knowledge base chatbot using RAG (retrieval-augmented generation) principles. This helps teams reuse evidence across drafting, reporting, and stakeholder questions without repeatedly searching folders.
5) Can your system produce reporting packs for donor reporting and MEL / M&E reporting cycles?
Yes. I build reporting workflows that generate a reusable reporting pack, including tables, synthesis summaries, and draft-ready sections mapped to your required standard. This is especially useful for donor reporting, MEL systems, and recurring M&E reporting cycles where consistency and auditability matter.
Frequently Asked Questions
1) Can you build an ETL pipeline to turn messy inputs into an analysis-ready database?
Yes. I design lightweight ETL pipelines (extract, transform, load) that convert PDFs, forms, spreadsheets, and documents into a clean, structured database. This includes a clear schema, validation rules, and a data dictionary so the evidence base stays consistent over time.
2) Do you do intelligent document processing (IDP) or PDF data extraction for research and policy work?
Yes. When inputs arrive as documents (PDFs, Word files, submissions), I build an intelligent document processing workflow to extract key fields, classify content, and organise it into a searchable evidence base. The goal is faster synthesis without losing traceability back to the original source.
3) Can you create a codebook / coding framework for qualitative analysis so multiple analysts code consistently?
Yes. For qualitative projects, I can design a codebook (coding framework) that defines themes, inclusion/exclusion rules, and examples. This improves inter-coder consistency, makes synthesis easier, and helps teams defend findings in reviews.
4) Do you build RAG / knowledge base chatbots so teams can query internal evidence and documents?
Yes. If you want your team to query an internal evidence base in plain English, I can build a knowledge base chatbot using RAG (retrieval-augmented generation) principles. This helps teams reuse evidence across drafting, reporting, and stakeholder questions without repeatedly searching folders.
5) Can your system produce reporting packs for donor reporting and MEL / M&E reporting cycles?
Yes. I build reporting workflows that generate a reusable reporting pack, including tables, synthesis summaries, and draft-ready sections mapped to your required standard. This is especially useful for donor reporting, MEL systems, and recurring M&E reporting cycles where consistency and auditability matter.
Frequently Asked Questions
1) Can you build an ETL pipeline to turn messy inputs into an analysis-ready database?
Yes. I design lightweight ETL pipelines (extract, transform, load) that convert PDFs, forms, spreadsheets, and documents into a clean, structured database. This includes a clear schema, validation rules, and a data dictionary so the evidence base stays consistent over time.
2) Do you do intelligent document processing (IDP) or PDF data extraction for research and policy work?
Yes. When inputs arrive as documents (PDFs, Word files, submissions), I build an intelligent document processing workflow to extract key fields, classify content, and organise it into a searchable evidence base. The goal is faster synthesis without losing traceability back to the original source.
3) Can you create a codebook / coding framework for qualitative analysis so multiple analysts code consistently?
Yes. For qualitative projects, I can design a codebook (coding framework) that defines themes, inclusion/exclusion rules, and examples. This improves inter-coder consistency, makes synthesis easier, and helps teams defend findings in reviews.
4) Do you build RAG / knowledge base chatbots so teams can query internal evidence and documents?
Yes. If you want your team to query an internal evidence base in plain English, I can build a knowledge base chatbot using RAG (retrieval-augmented generation) principles. This helps teams reuse evidence across drafting, reporting, and stakeholder questions without repeatedly searching folders.
5) Can your system produce reporting packs for donor reporting and MEL / M&E reporting cycles?
Yes. I build reporting workflows that generate a reusable reporting pack, including tables, synthesis summaries, and draft-ready sections mapped to your required standard. This is especially useful for donor reporting, MEL systems, and recurring M&E reporting cycles where consistency and auditability matter.
Book a Free Discovery Call
Book a Free Discovery Call
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.