A healthy nonprofit needs both a CRM and an intelligence layer. DonorSearch is a great CRM. Gratefully is the AI-native intelligence layer that sits on top of it - preserving the relationship context your CRM was never built to hold.
In one sentence: DonorSearch is a wealth screening and prospect research tool. Gratefully is the intelligence layer that sits on top - they're designed to work together, not in place of each other.
CRMs and intelligence layers are different categories of software. This table maps which capabilities live where.
| Capability | DonorSearch | Gratefully |
|---|---|---|
| Wealth and capacity screening (external data) | ||
| Philanthropic giving history (third-party sources) | ||
| Asset, real estate, and SEC filings lookup | ||
| Internal knowledge graph (notes, emails, documents) | ||
| Natural language query across all donor context | ||
| Answers cited to the actual source record | links to source DB | |
| Relationship history preserved through staff turnover | ||
| PII redaction and audit trail on AI interactions | ||
| Sits on top of existing CRM (no migration) | appends to CRM records | |
| Donor data trains shared AI models | N/A | Never |
| Proactive churn risk scoring on your portfolio | Action Center | |
| Autonomous signals from emails, notes, news | external news only | |
| Hidden revenue discovery from your existing data | ||
| Setup time | Days to weeks | Under 60 minutes |
DonorSearch is one of the most established wealth screening tools in the sector, and it does its job well: it tells you, with high confidence, who in your database has the financial capacity to give at a major level. That's a real and necessary input for any serious major gifts program.
But capacity is only half of the picture. The other half - the half that actually moves a cultivation forward - is everything your organization already knows about the relationship. The conversation from last year's site visit. The email where a donor mentioned their late father. The note your former development director left about a board member's planned gift conversation. None of that lives in a wealth screening report, and most of it isn't structured enough to live in a CRM field either.
Gratefully is the AI-native intelligence layer for that internal knowledge. You keep DonorSearch as your external intelligence source. You add Gratefully as your internal one - so that when a gift officer asks 'what do we know about this donor and what should I do next?', they get an answer grounded in both capacity data and the relationship history your team has already built.
CRMs hold your structured records. Gratefully holds the relationship context that lives between the rows.
Your gift records, contact history, and engagement data are well-organized. But the relationship context - the conversation from the gala, the note about a donor's late father, the planned gift conversation that was six months in - lives in emails, notes, and the heads of the people who logged them.
Your major gifts officer runs a DonorSearch report on a prospect and sees a $250K capacity rating. Then she asks Gratefully: 'What do we already know about her?' - and gets a cited summary of the three meetings she's had with staff, the cause areas she's mentioned caring about, the names of her children that came up in a thank-you call, and the planned gift conversation that was opened (and never followed up on) eighteen months ago. She walks into the cultivation meeting with both capacity and context.
Gratefully is built to sit on top of your existing tools - no migration, no rip-and-replace. Most organizations are set up in under 60 minutes.
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