AI-native fundraising

An AI partner that already knows your donors.

EvolveFundraising brings AI into the records and routines your development team works with every day. It prepares the context, the lists and the first drafts. Your people keep the relationships, the judgement and the final word.

Bolted on

A general chat window

Can draft a generic appeal. Knows nothing about who gave last spring, who stopped opening email or who sits on your board. Tempts staff to paste donor records into consumer tools.

AI-native

AI inside your fundraising work

Works from gifts, pledges, engagement and relationships already on one record. Helps answer the questions that matter: which donors to call this week, and why.

Capabilities and benefits

Six ways AI lightens the everyday load.

Each capability is grounded in your own donor data and designed to hand a person something useful to review, not to act on its own. Quoted prompts and reasons below are examples only.

01

Predictive donor prioritization

Rank supporters by likelihood to give, upgrade or lapse using giving history, engagement and relationships on one record.

Your benefit: Each score comes with a plain-language reason, so your team knows who to call this week and why.

Example: attended the conference three years running, gave twice last year, recently opened every email.

02

Natural-language segmentation

Ask for a list the way you would ask a colleague, instead of stacking five filters in a query builder.

Your benefit: Small teams without a data analyst can build focused lists in plain English.

Example: “Lapsed donors who attended an event this year.”

03

Contextual appeal and thank-you drafts

Draft appeals for each segment and thank-you notes that reference a donor's last gift and the program it funded.

Your benefit: A first draft grounded in real history, in your voice, ready for a person to edit and approve.

Example: a variation of the master appeal for monthly donors.

04

Donor meeting briefs

Summarize a donor's giving, pledges, engagement and relationships before a call or visit.

Your benefit: Walk into every conversation with context instead of ten minutes of clicking through records.

Example: a one-page brief before a mid-level donor check-in.

05

Data-quality assistance

Flag likely duplicates, suggest merges and help map columns in import files to your fields.

Your benefit: Cleaner records make every score and segment stronger. AI amplifies bad data as quickly as good data.

Example: “Bob Smith, 12 Oak St” and “Robert Smith, 12 Oak Street” flagged as one person.

06

Reporting questions

Ask questions about campaigns, gifts and pledges and get an answer drawn from your fundraising data.

Your benefit: Spend less time assembling reports and more time acting on what they show.

Example: “How is the spring appeal doing compared with last year?”

Human review, always

AI drafts. People decide.

Donor trust is the whole job. Nothing goes to a supporter, and no decision is made about a relationship, without someone on your team reviewing it first.

  1. 01

    AI prepares

    Scores, lists, briefs and drafts are assembled from the donor context already in your records.

  2. 02

    A person reviews

    Staff check facts, edit tone and decide what is right for each relationship. Review every draft before sharing it with a donor.

  3. 03

    A person decides and sends

    Outreach, merges and record changes happen only when someone on your team approves them. AI does not send on its own.

Illustrative example · not real data
Meeting briefSample donor

Before you call.

Giving
Gifts summarized from the donor record
Engagement
Events, volunteering and email activity
Why now
Plain-language reason behind the priority
Status
Awaiting staff review
Questions

What teams ask about AI.

What does AI-native fundraising mean?

AI works inside your fundraising records and everyday workflows, rather than in a separate chat window. The most valuable uses, like knowing which donors to call this week, depend on donor context that a general chatbot does not have.

Does the AI send appeals or thank-you notes automatically?

No. AI drafts and suggests. People on your team review, edit and approve anything a donor sees, and make the decisions about outreach and changes to records.

Will AI replace our fundraisers?

No. AI helps with drafting, data and prioritization so fundraisers can spend more time on relationships, which is where gifts come from.

What is a good first AI use case for a small team?

Plain-English segmentation and thank-you drafting are practical starting points. Both save time on everyday work and keep a person in control of the result.

Do we need a data scientist for donor scoring?

No. Useful scoring needs clean, deduplicated records, a meaningful amount of gift history and scores that explain their reasoning so staff trust and use them.

How should we use AI responsibly with donor data?

Write a short AI policy, avoid pasting donor records into consumer chat tools, fact-check every number, never invent impact stories or quotes, and check that scoring does not systematically overlook groups of donors. Ask us about how data is handled when you request information.

Put donor context to work.

Tell us about your team and your fundraising goals. We will walk you through how AI fits your everyday work, and how your people stay in control.

Request information