What a AI Fundraising Platform actually does
Generates major-gift propensity scores and personalized stewardship thank-you copy from nonprofit donor histories.
This AI implementation combines classical ML (XGBoost trained on giving history + wealth signals) with LLM-powered narrative generation to help nonprofit consultants and fractional development directors identify high-value donors and personalize stewardship outreach. The system ingests donor transaction records (amounts, frequency, recency) and demographic signals, scores each donor's likelihood of major-gift readiness, and auto-drafts thank-you copy tailored to their giving pattern and causes supported.
The category is compelling in 2026: Bloomerang dominates the nonprofit CRM space (1.5M+ nonprofits in the US, ~$1.5B fundraising-consulting market), but none of the major SaaS (Bloomerang, DonorPerfect, Bonterra, Givebutter, Classy) expose agency-tier white-label options. Fundraising consultancies reselling a branded propensity + stewardship stack can charge $199–$499/mo per nonprofit client with near-zero COGS (text-only workload).
AI capabilities involved
Major-gift propensity scoring from giving history + demographic signals
Stewardship thank-you copy generation per donor segment
Grant-prospect identification via RAG over foundation databases
Lapsed-donor reactivation messaging
Campaign messaging personalization by donor segment
Who uses this
- Nonprofit fundraising consultants managing 8–20 small-to-mid-sized organizations
- Fractional development directors selling per-nonprofit project retainers
- Grant-writing services serving nonprofits with multiple funding streams
- Nonprofit-sector accelerators and capacity builders
SaaS alternatives on the market
Real products you can sign up for today — with current 2026 pricing, honest pros and cons.
Bloomerang
Individual nonprofits (not consultants) who want plug-and-play donor CRM without technical overhead.
14-day trial
$99/mo (Essentials)
$299+/mo (Premium)
Pros
- +Donor CRM + email bundled; simple interface for small nonprofits.
- +Mobile app for real-time donor notes.
- +No technical setup required; works out-of-the-box.
- +Integrates with Mailchimp and other email platforms.
Cons
- −No AI propensity scoring — you get donor management, not predictive modeling.
- −No agency-tier white-label — can't resell under your brand.
- −Pricing per nonprofit ($99+) eats your margin if you resell at $199/mo.
- −Changing pricing plans mid-year can lock nonprofits into annual contracts.
DonorPerfect
Long-standing nonprofits with large donor databases who already use DonorPerfect and want continuity.
$99/mo (Core)
$299+/mo (Premium)
Pros
- +Longer in market (founded 1988); many large nonprofits use it as legacy system.
- +Robust reporting and custom field support.
- +Integrates with accounting software (QuickBooks).
- +Phone support included.
Cons
- −Outdated UI compared to Bloomerang or modern alternatives.
- −No AI features; no white-label option for consultants.
- −Steep learning curve for nonprofits; requires IT support for customizations.
- −Annual contracts lock nonprofits in, making it hard to switch to your branded solution.
Givebutter
Young nonprofits doing grassroots / peer-to-peer fundraising, not major-gift consultants.
Free plan with up to 500 contacts
5% platform fee (no base monthly)
Custom pricing for $2M+ annual giving
Pros
- +No monthly fees, only per-transaction; low cost for nonprofits with small donor bases.
- +Built-in peer-to-peer fundraising tools.
- +Excellent UX for fundraisers (not tech staff).
- +Direct nonprofit pitch — 'Givebutter for good'.
Cons
- −5% take rate quickly becomes expensive at scale (100 $500 donations = $2,500/mo cost).
- −No white-label; no AI features.
- −Peer-to-peer focus means weaker traditional major-gift workflows.
- −Transaction-based pricing makes MRR unpredictable for consultants trying to resell.
Classy by GoFundMe
Nonprofits optimizing donation-page UX and peer-to-peer fundraising, not consultants selling branded tools.
Demo / trial available
1.5% + $0.95 per transaction (no base monthly)
Custom pricing for enterprises
Pros
- +Excellent fundraising-page builders and peer-to-peer tools.
- +Integrated donor CRM + giving page.
- +Strong mobile experience.
- +Scaled to handle large nonprofits (Red Cross, March of Dimes).
Cons
- −Per-transaction fee (1.5% + $0.95) compounds fast; at 100 $500 donations/mo, you pay ~$900/mo in fees.
- −No white-label option for consultants.
- −No built-in AI; heavy on fundraising-tech (pages + campaigns) vs. donor intelligence.
- −Limited customization without developer work.
The AI stack
The core production pipeline runs propensity scoring (classical ML, runs once per week) and proposes draft stewardship copy (LLM on-demand). The architecture trades off token cost (cheaper models for bulk text generation) vs. output quality (Sonnet for high-stakes thank-yous to major donors).
Foundation model (thank-you copy generation)
Generates personalized stewardship thank-you messages, lapsed-donor reactivation copy, and campaign-messaging variants.
Claude Sonnet 4.6
$3 / $15 per M tokens (input / output)Thank-yous to top-tier donors (top 5% by giving), campaign-messaging for board communications.
DeepSeek V4 Flash
$0.14 / $0.28 per M tokens (input / output)High-volume bulk thank-yous, lapsed-donor reactivation copy, segment-level messaging.
Claude Haiku 4.5
$1 / $5 per M tokensMixed workload (both high-volume and mid-tier donors); default fallback.
Our pick: Use Claude Sonnet 4.6 for top-5%-by-lifetime-value donors' thank-yous; DeepSeek V4 Flash for the remaining 95%. For lapsed-donor reactivation campaigns (a common annual push), use DeepSeek in bulk and spot-check Sonnet drafts for quality before sending.
Propensity modeling (classical ML)
Scores each donor's likelihood of major-gift readiness (e.g., 0–100 likelihood to give $10K+ within 12 months).
XGBoost (self-hosted on Fly.io worker)
~$25/mo (Fly.io 1 shared-cpu machine) + free XGBoost libraryProduction scoring at scale; nonprofits with 500+ donor records with clean transaction history.
scikit-learn + Logistic Regression / Random Forest
Free (OSS library)MVP prototyping; nonprofits with <1000 donor records.
Google Vertex AI / Amazon SageMaker AutoML
$5–50/mo depending on inference frequencyEnterprise-scale deployments (rare for nonprofit consultancy MVP).
Our pick: For MVP: train a scikit-learn Logistic Regression on 12 months of transaction data (amount, frequency, recency, tenure). For production: graduate to XGBoost on Fly.io worker, run weekly retraining on new donor transactions. Features: total donated, donation count, days since last donation, average gift size, gift-recency decay, wealth-signal proxy (zip code median income if available).
Embeddings + RAG (grant prospect identification)
Embeds nonprofit's mission statement + donor giving history, retrieves matching grants from Candid / Foundation Directory database.
text-embedding-3-small
$0.02 per 1M tokensBulk embedding of 1000+ grants per nonprofit; monthly vector update.
Voyage voyage-3-large
$0.18 per 1M tokensSmall, high-accuracy grant databases (<500 grants per nonprofit); mission-critical grant matching.
Our pick: Use text-embedding-3-small to embed Candid Foundation Directory snapshot (~150K foundations) once per month. For each nonprofit, embed their mission + donor history, then retrieve top-20 matching foundations via cosine similarity. Pair with Sonnet 4.6 for final 'Why foundation X is a fit' narrative.
Storage + Vector DB (Supabase + pgvector)
Store donor records, transactions, and grant embeddings; support similarity search on grant prospects.
Supabase Pro ($25/mo)
$25 + $10 pgvector computeMVP; 10–20 nonprofit clients with <5K donors each.
Self-hosted PostgreSQL + pgvector (Render.com / Railway)
$12–50/mo depending on storageDIY builders or larger agencies managing multiple dedicated instances.
Our pick: Start with Supabase Pro ($25/mo). By client #15, you'll need to either upgrade to Team or shard nonprofits across multiple Supabase projects.
Reference architecture
The system ingests donor transaction CSV files (or API syncs from Bloomerang / DonorPerfect), trains an XGBoost propensity model weekly, embeds grant opportunities monthly, and serves on-demand thank-you-copy generation via LLM edge functions. The main engineering challenge is multitenancy: each nonprofit's donor data must be strictly isolated in RLS-controlled Supabase tables, and propensity scores must be nonprofit-specific (donor pool varies wildly by org size / sector).
Nonprofit uploads donor CSV or connects OAuth to Bloomerang/DonorPerfect
Lovable frontend + Supabase RLSUser authenticates as nonprofit admin. Lovable component (React form) accepts CSV upload or OAuth sync. CSV is parsed and validated (amount, date, donor_id, name). All data written to Supabase `donors` table with nonprofit_id and row-level-security policies ensuring nonprofit sees only their own data.
Weekly: Compute propensity scores for all donors
Scheduled Fly.io Python worker running XGBoostCron job triggers every Sunday at 2am UTC. Worker queries Supabase for all (nonprofit_id, donor) records, computes RFM + wealth signals, runs XGBoost inference, writes propensity scores back to `donor_propensity` table (nonprofit_id, donor_id, score, percentile, risk_segment).
On-demand: Generate thank-you copy for selected donors
Lovable UI (React) → Supabase Edge Function → DeepSeek / SonnetFundraiser selects 1–100 donors in the Lovable UI, clicks 'Generate thank-yous'. Edge Function fetches donor records (amounts, dates, causes supported), batches them, calls DeepSeek V4 Flash (or Sonnet for top-tier), returns 50–200 token drafts per donor. Results are displayed in-UI for copy-paste or scheduled email send.
Monthly: Embed Candid Foundation Directory; retrieve matching grants
Fly.io worker (Voyage embeddings) + Supabase pgvectorWorker fetches latest Candid snapshot (~150K foundations), embeds with Voyage text-embedding-3-small, upserts into `foundations` pgvector table. On demand, nonprofits' mission statements are embedded, cosine-similarity search retrieves top-20 matching foundations. Sonnet 4.6 drafts 'Why foundation X is a fit' for each match.
Dashboard: Donor propensity heatmap + segment breakdown
Lovable UI + rechartsNonprofit sees bar chart of donor count by propensity decile (0–10, 10–20, …, 90–100). Clicking a segment filters to donors in that propensity range. Users can bulk-action: 'Send thank-you to top 10%', 'Email lapsed donors', etc.
Estimated cost per request
~$0.0008 per donor thank-you draft (DeepSeek V4 Flash: ~100 input tokens from donor record + ~150 output tokens for draft = 250 tokens at $0.28/M output = $0.00007); ~$0.005 per propensity score batch (100 donors × XGBoost inference at ~$0.00005/donor = $0.005); ~$0.02 per grant-prospect batch (embedding + retrieval of 20 foundations at text-embedding-3-small rate).
Cost calculator
Drag the sliders to model your actual usage. The numbers update in real time so you can stress-test economics before writing a single line of code.
This calculator models monthly COGS for a consultant running a white-label fundraising platform serving multiple nonprofit clients. Assumptions: each nonprofit uploads 1K–5K donor records; the consultant batches thank-you generation once per month (average 500 donors/nonprofit). Fixed costs cover Supabase, Voyage embeddings license, and Fly.io workers; per-unit costs cover LLM tokens (DeepSeek default, Sonnet for high-tier donors).
Estimated monthly cost
$50.00
≈ $600 per year
Calculator notes
- This model assumes batch generation (once-per-month bulk drafting) rather than on-demand streaming, which reduces per-token costs by ~40% due to lower concurrency.
- Supabase Pro tier supports ~10–15 nonprofits before hitting compute / query limits. At 20+ nonprofits, graduate to Supabase Team ($599/mo) or shard across multiple projects.
- XGBoost retraining is included in Fly.io $15/mo; no separate ML platform costs.
- Grant-matching (Candid embedding + retrieval) scales with nonprofit size but is O(150K) one-time cost per month, amortized across all clients.
- This excludes customer support, email-send infrastructure (Resend / Mailgun), and Stripe payment processing (if billing per-nonprofit).
Build it yourself with vibe-coding tools
In 1 weekend with Lovable Pro, you'll have a working MVP that uploads donor CSVs, scores propensity with a pre-trained XGBoost model, and generates thank-you drafts. By Sunday night, you'll have a demo-ready prototype showing a nonprofit consultant how to onboard their first client.
Time to MVP
12–16 hours (1 weekend)
Total cost to MVP
$25 Lovable Pro + $50 API credits (DeepSeek + Voyage embeddings)
You'll need
Starter prompt
Build a white-label nonprofit fundraising tool with these features: 1. Authentication: Supabase Auth (email/password signup). Each org is a separate tenant. 2. Donor CSV upload: Form that accepts CSV with columns (donor_name, email, donation_amount, donation_date). Parse and insert into Supabase `donors` table (with nonprofit_id RLS). 3. Propensity scoring: After CSV upload, show a modal that calls an edge function to compute RFM (recency, frequency, monetary) scores. Store in Supabase `donor_propensity` table. 4. Thank-you generation: Form with a multi-select of donors. On submit, call Supabase edge function that batches donors (max 100 per batch) and streams DeepSeek V4 Flash thank-you drafts. Show results in a table with copy-to-clipboard buttons. 5. Dashboard: Show total donors, avg propensity score (pie chart), recent uploads (list). 6. Styling: Tailwind + shadcn/ui buttons and tables; clean, professional nonprofit-appropriate colors (blues, greens). Use React + TypeScript. Do NOT build XGBoost; just compute RFM manually in JavaScript (sum of donations / count / days since last donation). Database schema: - nonprofits (id, org_name, created_at) - donors (id, nonprofit_id, donor_name, email, amount, donation_date) - donor_propensity (id, nonprofit_id, donor_id, recency_score, frequency_score, monetary_score, combined_score, created_at) Edge Functions: - POST /edge-function/propensity-score-batch: takes nonprofit_id, returns propensity scores - POST /edge-function/generate-thankyous: takes nonprofit_id + donor_ids[], calls DeepSeek V4 Flash, returns drafted copy
Paste this into Lovable
Follow-up prompts (run in order)
- 1
Add a 'Donor segments' page that filters the table by propensity decile (0–10, 10–20, etc). Add buttons like 'Email top 10%' that pre-fill thank-you copy for bulk select.
- 2
Integrate with Resend.com to send drafted thank-yous as actual emails (for now, just a preview; don't require SMTP setup). Add a checkbox to each draft: 'Ready to send' and a 'Send all marked' button.
- 3
Add a 'Grants' section that lets nonprofits paste their mission statement, then calls a Voyage embeddings API to embed it and retrieve top-10 matching foundations from a mock Candid database (you can mock this with a JSON file of 50 example foundations). For each match, call Sonnet 4.6 to draft 'Why this foundation is a fit.'
- 4
Upgrade the propensity scoring from RFM to a pre-trained XGBoost model. Export your mock training data as a PMML or pickle file, load it in the edge function, and score against it. (You'll find pre-trained models online or train one yourself on synthetic data.)
- 5
Add multitenancy: support 5 separate nonprofits logging in with different domains (e.g., org1.yourdomain.com, org2.yourdomain.com). Each org should see only their own donors and propensity scores (RLS should enforce this).
Expected output
A working Lovable app where a nonprofit consultant can: (1) sign up, (2) upload a donor CSV, (3) see propensity scores auto-calculated, (4) generate thank-you drafts for selected donors (showing DeepSeek output in a table), (5) copy drafts to clipboard or preview a multi-donor email batch. No production-ready compliance or security audit needed — this is a proof-of-concept.
Known gotchas
- !Lovable's default Supabase instance is shared; RLS policies must be explicitly set per table. Test multitenancy (two orgs) early, or you'll accidentally let org A see org B's donors.
- !DeepSeek V4 Flash sometimes repeats thankyou templates if you batch >50 donors at once. Add a 'de-duplicate' step post-generation or manually review long batches.
- !CSV file encoding matters: nonprofits often export from Excel as Windows-1252 (ISO-8859-1). Lovable's built-in CSV parser defaults to UTF-8, so add a 'file encoding' dropdown or use a library like `papaparse` to auto-detect.
- !Propensity scoring on RFM alone is simplistic. If a nonprofit has very few donors (<100), RFM will show all donors with nearly identical scores. Consider adding a 'wealth proxy' (e.g., zip code median income from a free API like census.gov) to improve signal.
- !If you use Sonnet 4.6 for high-tier donors, token costs balloon if you're not careful. Add a price cap: 'Sonnet only for top 5% of donors, DeepSeek for the rest'.
- !Grant-matching (Voyage embeddings) requires external data (Candid / Foundation Directory). For MVP, use a mock JSON file of 50 example foundations to avoid setup overhead.
Compliance & risk reality check
Fundraising platforms touch sensitive nonprofit operations: donor confidentiality (IRS Schedule B), personal wealth signals, and GDPR/CCPA compliance for international nonprofits. This implementation must respect donor privacy and charitable-solicitation laws in 40+ US states. Below are the key compliance gates and mitigation strategies.
IRS donor-confidentiality (Schedule B privacy)
In the US, nonprofits must file IRS Form 990-N (e-file) or 990 (paper) annually. Schedule B lists donors who gave $5,000+, but it is NOT public. Federal law (26 USC § 6104) restricts access to Schedule B — typically only IRS, state AG, and authorized nonprofit staff see it. Storing donor names + amounts in a database (your platform) requires access controls that respect this confidentiality ceiling.
Mitigation: Implement role-based access control: only nonprofit development directors and the executive director should see donor names + amounts. Lovable can enforce this via Supabase RLS policies per nonprofit_role (e.g., 'development' vs. 'finance'). Add an audit log (immutable Supabase table) of who accessed what data and when. Include a data-retention policy: after 7 years, archive or delete inactive donor records unless required by nonprofit's retained-records policy.
GDPR / CCPA for donor PII (especially international nonprofits)
If a nonprofit serves international beneficiaries or has donors in the EU, donor names + emails + giving history constitute personal data under GDPR (Art. 4(1)). CCPA applies if nonprofit has donors in California. Both regulations require explicit consent, data minimization, and the right to erasure ('right to be forgotten').
Mitigation: Add a consent field in the `donors` table: (consent_given: boolean, consent_date: timestamp, consent_source: 'signup_form' | 'email_opt_in' | 'phone_call'). Lovable UI includes a checkbox: 'I consent to this nonprofit using my giving history for stewardship outreach.' For nonprofits in GDPR scope, implement a 'Request deletion' button that lets donors request erasure of their record; log the request to an audit table and comply within 30 days. For CCPA, add a 'Do Not Sell My Data' link per CCPA § 1798.100. Set data retention: auto-delete donor records 5+ years after last gift unless nonprofit's policies require retention.
State charitable-solicitation registration & donor-list transparency
40+ US states require nonprofits soliciting donations to register with the state Attorney General. Some states (e.g., New York, Florida) require nonprofits to file annual charitable-solicitation reports that list major donors. Your platform must not auto-publish donor lists without explicit consent.
Mitigation: In your Lovable UI, add a toggle per nonprofit: 'Generate state AG report.' When enabled, filter donors to those who explicitly consented to public-report inclusion, and export a redacted CSV (nonprofit name, donor name, gift amount, gift date, but NO contact info). Warn nonprofits: 'Some states require reporting major donors in public filings — add donor consent before filing state reports.' Add a checkbox at signup: 'I consent to my name appearing in public filings' (many nonprofits use this for transparency / public recognition).
PCI DSS (payment card data) / Stripe passthrough
If your platform ever touches payment cards (credit card numbers), you enter PCI DSS scope. Your platform should NEVER store raw card data; instead, route all donations through Stripe (or Givebutter/Classy) and store only Stripe transaction IDs.
Mitigation: In your platform, donor-import CSVs should contain donation amounts + dates (from nonprofit's accounting system), NOT card numbers. When displaying donation history, show only Stripe charge IDs + amounts. If a nonprofit wants to use your platform to accept donations directly (future feature), integrate Stripe Checkout (hosted, PCI-compliant) — never build a custom payment form. Add a security note in Lovable's dashboard: 'We do NOT store credit card data. All donations are processed through Stripe.'
Wealth-screening data ethics (donor profiling)
Using donor propensity scores to predict 'high-value' donors based on zip code, giving patterns, or inferred wealth signals can create algorithmic bias or privacy concerns. Nonprofits might over-weight wealthy donors and under-serve mission to marginalized communities.
Mitigation: In your Lovable dashboard, add a transparent explanation: 'Our propensity model scores donors based on giving history (amount, frequency, recency). Zipcode data is NOT used to avoid algorithmic bias. Scores are suggestions; final stewardship decisions are staff decisions.' Include a warning if a nonprofit imports wealth-screening data (e.g., Capacity-based screening): 'Consider whether wealth signals align with your nonprofit's equity values.' Add optional fairness metrics: 'Your top 10% donors are 62% male, 78% white — does this reflect your service population?'
Build vs buy: the real math
6–9 weeks
Custom build time
$18,000–$32,000
One-time investment
8–12 months
Breakeven vs buying
A Lovable DIY build costs $25/mo + ~$30/mo COGS, allowing you to resell at $199–$249/mo per nonprofit with ~95% gross margin. At 12 nonprofit clients, that's $2,268–$2,988/mo in gross margin, or ~$27K–$36K annually. Against the $18K–$32K custom build cost, you break even at 8–12 months of client subscriptions. The buy-SaaS path (Bloomerang at $99+/mo per nonprofit) produces zero margin if you resell under your brand at $199/mo, and Bloomerang offers no white-label tier anyway — making custom build the clear winner for any consultant with 8+ clients. Even at 3–5 clients, DIY wins because the $18K–$32K custom build overhead is amortized over years of recurring revenue. The only case for buying SaaS is if you're a one-off nonprofit (not a consultant reselling); if you're building a practice, build yourself first with Lovable and graduate to custom only if you hit 25+ clients and need proprietary features (e.g., custom workflows, predictive churn models).
Skip the DIY — RapidDev builds the production version
A Lovable MVP gets you a demo. Production needs auth that doesn't leak data, AI calls that don't bankrupt you, observability when models drift, and code you can audit. That's what we ship.
Discovery call (free)
30 minWe map your exact AI Fundraising Platform use case: who uses it, target volume, AI model choice, integrations, compliance scope. You get a detailed scope document and fixed-price quote within 48 hours.
AI-accelerated build
6–9 weeksOur engineers use Claude Code, Lovable, and custom tooling to ship 3–5x faster than agencies. You see weekly progress in a staging environment — not a black box.
Launch + handoff
1 weekWe deploy to your infrastructure, transfer the GitHub repo, set up CI/CD and monitoring, and train your team. You own 100% of the source code, prompts, and model configurations.
What you get
Timeline
6–9 weeks
Investment
$18,000–$32,000
vs SaaS
ROI in 8–12 months
30-min call. Fixed-price quote within 48 hours. No commitment.
Frequently asked questions
How much does it cost to build a white-label fundraising platform?
A full custom build via RapidDev costs $18K–$32K (6–9 weeks). A DIY Lovable MVP costs $25 Lovable Pro + ~$50 API credits (1 weekend). Monthly infrastructure is $25–50 (Supabase, Voyage, Fly.io worker). If reselling at $199–$249/mo per nonprofit, your COGS is <$60/mo per client, yielding 75–95% gross margin. Breakeven on the $18K–$32K custom build happens at 8–12 months of 10+ client subscriptions.
How long does it take to ship a fundraising platform?
DIY with Lovable: 1 weekend to a working MVP (CSV upload → propensity scoring → thank-you drafts). Custom build with RapidDev: 6–9 weeks to a production system with multitenancy, compliance, audit logs, and integration with Stripe for donations. The DIY path is faster for initial validation; upgrade to custom if you validate demand from 5+ nonprofits.
Can RapidDev build this for my company?
Yes. RapidDev has shipped 600+ applications, including multi-tenant SaaS platforms. For a white-label fundraising platform, typical scope is $18K–$32K over 6–9 weeks, covering Supabase schema, Sonnet/DeepSeek integration, XGBoost propensity scoring, and production-ready compliance (IRS donor confidentiality, GDPR/CCPA). Email seopartner@rapidevelopers.com for a free 30-min consultation to discuss your nonprofit consultant's specific needs.
Should I use Sonnet or DeepSeek for thank-you generation?
Use DeepSeek V4 Flash for 95% of donors — it's 7–10× cheaper ($0.28/M output vs. $15/M for Sonnet) and sufficient quality for bulk stewardship. Reserve Claude Sonnet 4.6 for top-5%-by-lifetime-value donors; the better quality justifies the cost for your most important relationships. You can also use Haiku 4.5 as a middle ground (1.5× cheaper than Sonnet, 2× more expensive than DeepSeek).
How do I handle GDPR / CCPA compliance?
Add a consent field to your donor table and require explicit opt-in before storing contact info. Implement row-level security (RLS) in Supabase so each nonprofit sees only their own donors. Add an audit log of who accessed what donor data and when. Provide a 'Request deletion' button for donors to exercise their right to erasure (GDPR Art. 17 / CCPA § 1798.100). For nonprofits in GDPR scope, use Voyage embeddings' EU data centers and ensure Supabase is hosted in EU regions.
Can I integrate with Bloomerang or DonorPerfect?
Yes. Both have APIs that export donor records (transactions, giving history). You can build a scheduled sync (OAuth + webhook) to pull donor data weekly from Bloomerang/DonorPerfect, compute propensity scores, and write results back to a Supabase tenant database. This creates a 'intelligence layer' on top of their CRM — you don't compete with the CRM itself, just offer propensity + stewardship drafting as an add-on.
What's the difference between this and a regular CRM?
A nonprofit CRM (Bloomerang, DonorPerfect, Salesforce) manages contact info, donation history, and tasks. This platform adds two AI layers: (1) Propensity scoring (XGBoost model that predicts major-gift likelihood), and (2) Automated stewardship (LLM-drafted thank-yous). The CRM is the source of truth; this platform is the intelligence + outreach engine on top.
How many nonprofits can one Supabase instance support?
Supabase Pro tier ($25/mo) supports ~10–15 nonprofits with 1K–5K donors each before hitting query-concurrency limits. At 20+ nonprofits, upgrade to Supabase Team ($599/mo) or shard across multiple projects. For a DIY build, start with Pro; upgrade only when you have >15 paying clients.
Want the production version?
- Delivered in 6–9 weeks
- You own 100% of the code
- AI cost monitoring built in
30-min call. No commitment.