For grant-dependent nonprofits

Your data should
work for you —
not against you.

If your reports don't match, your CRM is full of duplicates, or your spreadsheets are doing backflips — grant applications get harder than they need to be. I help nonprofits get their data clean and stable before it's crunch time.

Async, email-based process. No weekly meetings required.

Sample Assessment Snapshot
Data Readiness Score
58
out of 100 — Workable, but gaps will show under deadline pressure
Top Issues Found
~340 duplicate contacts
Inflating headcount + skewing report totals
Inconsistent program tags
Same program named 3 different ways
2 broken intake automations
Silently failing — bad records entering system

Messy data doesn't just
look bad — it costs you.

Nonprofits shouldn't have to scramble before a grant deadline. But when data is inconsistent, reporting gets slow, stressful, and hard to defend. Here's what that actually looks like:

🚩 Common red flags I see
Duplicate contacts inflating your headcount and skewing report totals
Missing fields and inconsistent tags making filters unreliable
Conflicting totals across systems — and no clear source of truth
Automations that quietly break and nobody notices until it matters
✓ What you get instead
A clean, consistent dataset you can actually trust for reporting
Clear field standards your staff can follow — no more guessing
Guardrails that catch problems before they become reporting disasters
Confidence going into grant season — not last-minute scrambling

Three steps. No surprises.

The process is calm, structured, and async — meaning no weekly check-ins eating up your schedule. Here's what working together actually looks like:

01
Assess what's breaking trust in your data

I review how your data enters your systems, how it flows, and where things go sideways. You'll get a clear score and a ranked list of what to fix first.

Data Readiness Assessment
02
Stabilize the foundation

Deduplication, field standardization, cleanup rules. I work through the issues systematically and document everything so your team knows what changed and why.

Data Foundation Cleanse
03
Protect it with automation guardrails

The cleanup shouldn't have to happen twice. I install lightweight automations that catch problems before they enter your system — so the mess stays away.

Integrity Engine
See If Your Data Is Grant-Ready →

You'll get a score + fix-first plan. I'll reply with next steps within 48 hours.

How I've helped nonprofits
trust their data

Case Study 01
Registration → Clean Contacts
+ Reliable Messaging

Every time someone signed up to volunteer or participate, staff had to manually move that data into their messaging system — and hope nothing got lost, doubled, or missed. It was slow, it was fragile, and the duplicate contacts piling up meant their headcount numbers couldn't be trusted. I fixed the flow once, and built guardrails so it stays fixed.

~100 duplicates identifiedManual uploads: 2 hrs/week → near zeroAutomated status logging
View full case study
Case Study 02
Automation Continuity
During a Platform Migration

Switching platforms is supposed to make things better. But mid-migration is also when things quietly break — and in a nonprofit, a broken intake flow or a silent data mismatch can show up at the worst possible time: when you're pulling reports for a funder. I made sure that didn't happen.

Zero disruption to onboardingReal-time status visibilityCross-system consistency audits
View full case study
Case Study 03
From Founder-Dependent Onboarding
to a Single Source of Truth

If your ED or founder is the only person who knows where a volunteer stands in the onboarding process — that's a data problem, not just an operations problem. Funders want to see that your organization runs on systems, not on individuals. This nonprofit's onboarding lived entirely in emails and people's heads. I designed a way out.

Fewer manual follow-upsClearer onboarding statusRepeatable + scalable workflow
View full case study

Start where you are.

Every engagement starts with the Assessment — it's how we figure out exactly what your data needs. Most clients leave grant-ready after the Assessment + Cleanse. The Engine is an optional upgrade for orgs who want ongoing protection.

Start Here
Step 1 — Required
Data Readiness Assessment
$750–$1,250
Depends on systems + complexity
What you get
Review of key systems + data flows
Identification of duplicates, gaps, and broken workflows
Data Readiness Score (0–100)
Top issues ranked by impact
Fix-first roadmap + recommended next step
Start with the Assessment →
Optional Upgrade
Add-On
Integrity Engine
For teams who want automated guardrails that keep data clean long-term
$6,500–$10,500
Scoped from your assessment findings. Cleanse may be included if needed.
What you get
2–5 guardrail automation modules
Duplicate prevention + required-field gates
Anomaly alerts + exception queues
Full documentation + handoff guide
Async training notes for your team
Learn About the Engine →

All paths start with the Assessment — every button above takes you there.

💡
The upgrade credit: If you move forward with a Cleanse or Integrity Engine within 30 days, your assessment fee is fully credited toward the project.
What's not included: Grant writing, dashboard builds, full CRM migrations, ongoing data entry support, or 24/7 monitoring. These can be scoped separately if needed.

This is a good fit if you're
tired of not trusting
your own numbers.

You don't need to have everything figured out. You just need to know something's off — and want a clear path to fixing it before your next grant deadline.

See If Your Data Is Grant-Ready →

Async, email-based. No weekly meetings. Reply within 48 hours.

Your nonprofit relies on data for credibility and reporting
Reporting is slow, stressful, or takes way longer than it should
Duplicates, missing fields, or inconsistent categories keep showing up
You want clarity without hiring full-time ops or data staff
You have a grant deadline in the next 30–90 days
Free Resource

Get clarity on your data
Score it in minutes

Before the Assessment, see exactly where your data stands. The Grant-Ready Data Checklist walks you through 24 yes/no checks across 7 key areas — source of truth, reporting readiness, automations, and more. Simple, fast, actionable.

24 checks across 7 areas of data readiness
Score yourself 0–24 and see where you land
Quick, clear, actionable
Yes, I Want Clarity→Takes less than 2 minutes to score
Preview
Grant-Ready Data
Checklist
🗂 Source of Truth
We know the "source of truth" for each data type
Each system has a clear owner
📊 Reporting Readiness
Every metric maps to a specific field
We can run the same report twice consistently
🎯 Grant-Specific Readiness
Grant requirements mapped to specific data
Core reports pull quickly — no manual cleanup
___ / 24 Your score
0–6 Fragile19–24 Strong

Questions you might be wondering

How does the Data Readiness Assessment work?
+
After you apply, I’ll confirm fit and send a simple request for access (or exports) from your systems.

I then review your data flow end-to-end — where data enters, how it changes, and where reporting pulls from.

You’ll receive a clear summary by email, including:

- A Data Readiness Score (0–100)

- A ranked list of top risks

- A fix-first roadmap

If you decide to move forward, I’ll include exact pricing for the next step.
Do you need access to our systems?
+
Usually, yes — I request read-only access first to keep everything safe. If that’s not possible, we can work from secure exports (CSV reports or screenshots). Nothing is ever changed without your sign-off.
What does the async process look like day-to-day?
+
There are no recurring meetings. Everything happens over email, with regular written updates as work progresses.

You’ll always know what I’m working on, what I’ve found, and what’s next — without anything taking over your calendar.

I work at a calm, structured pace, and you can reach out with questions anytime.
What kind of organizations do you typically work with?
+
I work with nonprofits managing multiple programs, systems, or reporting requirements — especially those preparing for grants or struggling to trust their data.

If your data feels scattered, inconsistent, or hard to report on, this is likely a good fit.
Do you do grant writing?
+
No — DreamFlow focuses entirely on data readiness and system stability.

I make sure your data is clean, structured, and reliable so grant writing becomes faster and easier for whoever handles it.
What if I've already paid for the Assessment and want to move forward?
+
If you move forward with the Cleanse or Integrity Engine within 30 days, 100% of your Assessment fee is credited toward the next service — so you’re not paying for it twice.
How long does each service take?
+
The Assessment typically takes 5–10 business days, depending on the number of systems and data complexity.

Timelines for the Cleanse and Integrity Engine are scoped during the Assessment, so you’ll know exactly what to expect before committing.

Still have questions?

I'm happy to help. Reach out directly, or start with the Assessment when you're ready.

Grant-ready data for nonprofits.
© 2026 Hello, DataFlow. All rights reserved.
Case Study 01 • Intake + Messaging Automation

Registration → Clean Contacts
+ Reliable Messaging

Every time someone signed up to volunteer or participate, staff had to manually move that data into their messaging system — and hope nothing got lost, doubled, or missed. It was slow, it was fragile, and the duplicate contacts piling up meant their headcount numbers couldn't be trusted. I fixed the flow once, and built guardrails so it stays fixed.

~100 duplicates identifiedManual uploads: 2 hrs/week → near zeroAutomated status logging

Note: This project predates Hello, DataFlow's formalized offers and has been mapped to the closest aligned services.

Stop the data from getting messy at the door
So reporting numbers are accurate before grant season even starts
Google Forms + Sheets
Automation platform + SMS tool
Data Foundation Cleanse + Integrity Engine
Deduplication + guardrails + logging

What wasn't working

  • Every new registration required staff to manually move data into the messaging system — eating 2+ hours a week.
  • The same person could sign up twice and create two separate records, inflating participant counts.
  • When something broke, nobody knew until it was already a problem.

What changed

  • New registrations flow directly into the system automatically — no manual uploads, no missed records.
  • Duplicates get flagged and held for review instead of entering the system and corrupting the data.
  • Staff can see exactly what the system did and catch errors before they touch a report.

The work

  • Traced exactly where data was breaking down between the form, the spreadsheet, and the messaging platform.
  • Built automation that handles contact creation and welcome messaging without anyone touching it.
  • Added duplicate detection that flags the problem without deleting anything — so staff stay in control.
  • Set up run logs so the team has a paper trail they can actually point to.
If this project happened today: we'd start with a formal Data Readiness Assessment — so before anything got built, we'd know exactly what was broken, what it was costing, and what to fix first. Same outcome, but you'd go in with eyes open.
See If This Could Work for You →

When your contact data is clean and your intake is automated, you're not scrambling to fix numbers before a grant deadline — you're already ready.

Case Study 02 • Migration + Continuity

Automation Continuity
During a Platform Migration

Switching platforms is supposed to make things better. But mid-migration is also when things quietly break — and in a nonprofit, a broken intake flow or a silent data mismatch can show up at the worst possible time: when you're pulling reports for a funder. I made sure that didn't happen.

Zero disruption to onboardingReal-time status visibilityCross-system consistency audits

Note: This project predates Hello, DataFlow's formalized offers and has been mapped to the closest aligned services.

Keep the data clean and the workflows running during the move
So nothing breaks in a way that shows up later in a grant report
Google Sheets → Airtable
Automation + messaging platform + API scripts
Data Foundation Cleanse + Integrity Engine
Continuity + guardrails + cross-system auditing

What wasn't working

  • The migration meant rebuilding onboarding workflows from scratch — with no guarantee they'd work the same way.
  • Duplicate contacts and missed welcome messages were real risks with no safety net in place.
  • There was no way to know if the new system and the messaging platform were actually showing the same data.

What changed

  • Onboarding kept running without a single disruption during the entire migration.
  • Duplicates were caught before they entered the new system — not discovered weeks later during a report pull.
  • A continuous cross-system check flagged any drift between platforms automatically, so data stayed consistent.

The work

  • Rebuilt duplicate prevention and welcome messaging inside Airtable before the old system was turned off.
  • Connected Airtable to the messaging platform via API so contact creation happened automatically.
  • Added status logging so every record had a clear trail — what happened, when, and whether it worked.
  • Built a discrepancy checker that compared records across both systems on an ongoing basis.
🔍
If this project happened today: the guardrails would be packaged as named, documented modules — so your team knows exactly what's protecting your data and how to maintain it as you grow.
See If This Could Work for You →

A migration shouldn't put your data at risk. When it's done right, you come out the other side with cleaner data and stronger systems than you had before.

Case Study 03 • Workflow Design

From Founder-Dependent Onboarding
to a Single Source of Truth

If your ED or founder is the only person who knows where a volunteer stands in the onboarding process — that's a data problem, not just an operations problem. Funders want to see that your organization runs on systems, not on individuals. This nonprofit's onboarding lived entirely in emails and people's heads. I designed a way out.

Fewer manual follow-upsClearer onboarding statusRepeatable + scalable workflow

Note: This system was fully designed and documented. Full rollout was paused due to a leadership decision — not a technical or operational blocker. This project predates Hello, DataFlow's formalized offers.

Get onboarding out of the founder's inbox and into a system
So the organization can show funders it runs on structure — not heroics
ClickUp + Calendly
Form intake + Zapier automation layer
Data Readiness Assessment
Workflow mapping + risk identification + fix-first roadmap

What wasn't working

  • Volunteers applied in one place, scheduled interviews somewhere else, and waited with no idea what came next.
  • The founder was manually tracking every step — matching emails, assigning tasks, following up by hand.
  • There was no record of where any volunteer stood in the process — just a mental map that only one person held.

What changed

  • One intake form captured everything — application, scheduling, and role information in a single submission.
  • Every volunteer got a record in one central system with a clear status anyone on the team could check.
  • Task assignment, reminders, and follow-ups were designed to trigger automatically — no manual coordination required.

The work

  • Mapped every step of the onboarding process to find where data got lost and where the founder became the bottleneck.
  • Designed a single intake flow so volunteers only had to submit information once.
  • Built a status-driven workflow so the whole team could see where each volunteer was without asking anyone.
  • Delivered a complete system design and documentation package ready to hand off and implement.
🧠
If this project happened today: it would ship with an Integrity Engine layer — automations that keep the data clean as volunteer volume grows, so the system doesn't quietly drift back into chaos.
See If This Could Work for You →

When your onboarding runs on a system instead of a person, you can tell funders exactly how many volunteers you have, where they are in the process, and what they've completed. That's the kind of operational clarity that builds credibility.