AI and software for charities and foundations
We build AI for nonprofits that have more work than staff: charities, foundations and funds that rely on donors, volunteers and grants. The focus is on removing admin from small teams, with trustees, committees and staff making the decisions about money and people.
Where the work gets stuck.
Donor data lives in too many places
Gifts come in through payment providers, fundraising platforms, events and direct debits, while the CRM holds only part of it. Teams reconcile spreadsheets before they can thank a donor or report income.
Grant applications pile up
Foundations receive applications in varying quality and formats, and each needs checking against criteria before a committee sees it. Charities face the reverse, writing reports for each funder in its own template.
Small teams without developers
Most nonprofits have no in-house developers and depend on a mix of licensed tools and volunteers. New software has to be simple to run and light to maintain.
How we improve non-profit.
Each one is scoped around your systems and rules, and each one keeps a person in charge of the decisions that matter.
Donor data integration
Gifts, mandates and campaign data from payment providers, fundraising platforms and email tools flow into one CRM record per supporter. Fundraisers work from a complete picture and finance reconciles faster.
Grant application review
Applications and attachments are checked for completeness and summarised against your funding criteria, with open questions listed. The grants officer and committee assess each project and decide on funding.
Donation administration
Periodic gift agreements, failed direct debits, address changes and tax receipts are processed from incoming requests and bank files. Staff approve exceptions and supporter-facing messages.
Staff and volunteer knowledge assistant
Staff and volunteers ask questions about procedures, programmes and past reports and get answers with sources, and can draft funder reports from programme data. A staff member checks every report before it goes out.
Volunteer and beneficiary portals
Portals where volunteers sign up for shifts and beneficiaries apply for support, connected to your CRM. Coordinators spend less time on phone calls and spreadsheets.
AI roadmap for a small organisation
We look at your processes, data and tools and recommend where AI is worth it, where a licensed tool already covers the need and what to leave alone. The board gets a short plan with effort estimates to discuss.
Built around the rules.
What we design for from the first week. Your legal and compliance people keep the final word.
GDPR and supporter data
Donor records can reveal beliefs or health conditions, depending on the cause. We set clear purposes and retention per data type, keep processing in the EU and document the lawful basis for each use.
Consent for fundraising contact
Dutch telecom rules limit fundraising by email and phone to people who gave consent or have an existing relationship. Integrations carry consent status with each record so campaigns respect it.
ANBI rules
Organisations with ANBI status have publication duties, and periodic gifts need a valid written agreement for donors to deduct them. Donation administration tools store agreements and data in a way that supports both.
CBF recognition and RJ 650 reporting
Recognised fundraising organisations report under Guideline 650 and meet CBF standards on accountability. Data pipelines keep income by source and spending by objective traceable for the annual report.
Works with what you run.
If a system has an API, a database, an export or an inbox, we can build on it. These are the ones we meet most.
- Salesforce Nonprofit Cloud
- Blackbaud Raiser's Edge NXT
- Microsoft Dynamics 365
- HubSpot
- Kentaa
- Mollie
- Stripe
- Mailchimp
- Exact Online
- Microsoft 365 and SharePoint
Where to start.
Donor data integration with one CRM
A build that brings gifts, mandates and consent from your payment and fundraising tools into a single CRM. It removes weekly reconciliation work and gives every later project clean data to build on.
Talk it throughWhat it includes
- Connectors for payment and fundraising tools
- Matching and deduplication of supporters
- Consent status carried per record
- Daily sync with error reporting
Guides.
Build vs buy software: a decision guide for operations and product teams
A practical guide to choosing between off-the-shelf and custom software, with a cost comparison, a decision matrix and a checklist for your team.
10 min read
AI readiness checklist: what to answer before your first agent goes live
The questions to answer before your first AI agent handles real work, from process and data to approvals, monitoring and ownership.
10 min read
Further reading.
Build vs buy software: when custom development pays off
A practical way to decide between off-the-shelf software and custom development, covering total cost of ownership, integrations and risk.
5 min read
Human-in-the-loop AI agents: design patterns for production
The patterns we use to run AI agents safely in production: approval checkpoints, confidence thresholds, tool permissions, audit trails and fallbacks.
4 min read
Document parsing with LLMs: extracting data from invoices and forms
How to turn invoices and forms into reliable structured data with LLMs, schemas, validation and a review queue for the cases that need a person.
4 min read
Common questions.
Sometimes. Where a licensed tool or nonprofit discount covers the need, we recommend that. Custom work makes sense for the integrations and specific processes that off-the-shelf tools miss, and we keep those builds small and easy to maintain.
Yes. Both have APIs we build against, as do Dynamics 365, HubSpot and the common Dutch payment and fundraising platforms. We work alongside your CRM partner if you have one.
Your grants officers and committee. The software checks completeness and summarises against your criteria, and people assess the project and make the funding decision.
We keep processing in the EU, limit access by role and send as little personal data to models as possible. Sensitive beneficiary data can stay entirely outside AI processing where you prefer.