Data Analysis & Reporting

🤖 Fabi.ai for Nonprofits

Drowning in donor data but can't find insights without a data analyst? Fabi.ai transforms plain English questions into instant analysis—ask "Which donors lapsed last quarter?" and get answers with charts in 30 seconds. No SQL, no pivot tables, no waiting. Your 2-person team can now explore program impact, donor trends, and fundraising performance like you have a dedicated analytics department.

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What It Does

Your board asks for donor retention numbers. Your funder wants program outcome data broken down by demographics. Your development director needs to identify major gift prospects. Each question requires hours of spreadsheet wrangling—time your team doesn't have.

Fabi.ai is an AI-native business intelligence platform built specifically for teams without data analysts. Instead of building complex dashboards or writing SQL queries, you simply ask questions in plain English: "Show me donation trends for the last 12 months" or "Which programs have the highest retention rates?" The AI Analyst Agent instantly generates the analysis, creates visualizations, and explains the findings—complete with the SQL and Python code behind each answer (which you can view, edit, or learn from).

Beyond answering one-off questions, Fabi.ai automates insights delivery through Workflows—scheduled reports sent to Slack, email, or Google Sheets. It's the difference between spending 10 hours monthly on board reports and having them generated automatically every month with the latest data.

Best For

Organization Size

Small to mid-sized nonprofits (5-100 staff) with moderate data analysis needs but no dedicated data analyst. Particularly valuable for growing organizations transitioning from basic spreadsheets to more sophisticated analysis.

Best Use Cases

Analyzing donor behavior and identifying retention patterns across CRM data
Creating automated monthly reports for board meetings and funder updates
Measuring program impact across multiple data sources (surveys, service records, outcomes)
Exploring campaign performance and fundraising trends without building complex dashboards
Combining data from Google Sheets, databases, and SaaS applications for unified analysis

Ideal For

Executive Directors needing quick insights for strategic decisions, Development Directors analyzing donor data, Program Managers tracking outcomes, and anyone who needs data analysis but lacks coding skills or time for complex BI tools.

Key Features for Nonprofits

AI Analyst Agent

Ask questions in plain English and get instant answers with visualizations

Type "Show donors who gave more than $500 in 2025 but haven't given yet in 2026" and receive a complete analysis with charts, tables, and actionable insights—no SQL required. The AI generates all code automatically.

Smartbooks

AI-native collaborative notebooks for exploratory analysis

Combine Python code, SQL queries, AI-generated analysis, and narrative text in reactive notebooks. Share findings with your team, iterate on analysis, and maintain a living record of insights with version control via GitHub integration.

Automated Dashboards

Generate interactive dashboards from natural language prompts

Say "Create a dashboard showing monthly donation trends by campaign and donor type" and Fabi.ai builds it automatically. Customize layouts, add filters, and share with up to 50 viewers (Team plan) without manual chart configuration.

Workflows & Automation

Schedule insights delivery to Slack, email, or spreadsheets

Automate your monthly board report: every 1st of the month, Fabi.ai runs updated analysis and sends results to your team's Slack channel or Google Sheet. Set it once, never manually update reports again.

25+ Data Integrations

Connect warehouses, spreadsheets, CRMs, and applications

Unify data from Google Sheets, Salesforce, HubSpot, PostgreSQL, BigQuery, Snowflake, and more. Analyze across sources without manual exports or data consolidation. Free plan includes file uploads and Google Sheets connector.

Code Transparency & Learning

View, edit, and learn from all AI-generated SQL and Python code

Every AI response shows the exact code used. Non-technical users can trust results; technical users can refine queries. It's a learning tool—see how AI translates your questions into code and build SQL fluency over time.

How This Tool Uses AI

What's Actually AI-Powered

🤖 Natural Language to SQL/Python Translation

Type of AI:

Large language models (LLMs) trained on billions of SQL queries and data analysis patterns

What it does:

Translates conversational questions like "Which donors gave in December but not in January?" into executable SQL queries and Python data transformations

How it learns:

Pre-trained on massive datasets of database queries; improves with your feedback when you edit or approve generated code

Practical impact:

Instead of spending hours writing complex JOIN statements or pivot tables, you ask questions and get instant analysis—reducing data analysis time from hours to seconds

🤖 Automated Insight Generation

Type of AI:

Pattern recognition algorithms that detect trends, anomalies, and significant changes in your data

What it does:

Automatically surfaces insights like "Donor retention dropped 15% in Q4" or "Youth program participants increased 23% year-over-year" without you asking specific questions

How it learns:

Analyzes historical patterns in your data to understand what's "normal" vs. "noteworthy"

Practical impact:

Discover important trends you might miss manually reviewing data—like a digital analyst watching your metrics 24/7

🤖 Smart Visualization Selection

Type of AI:

Recommendation system that chooses appropriate chart types based on data structure and question intent

What it does:

Automatically selects bar charts for comparisons, line charts for trends, scatter plots for correlations—whatever best answers your question

Practical impact:

Skip the guesswork of choosing chart types; AI picks the most effective visualization for communicating insights to your board or funders

What's NOT AI (But Still Useful)

•Data Integrations: Connecting to databases and spreadsheets uses standard API connections, not AI
•Dashboard Hosting: Sharing dashboards with viewers is standard web technology
•Scheduled Workflows: Automation is rule-based (run every Monday at 9am), not AI-driven
•Version Control: GitHub integration for tracking changes is standard development practice

AI Transparency & Limitations

Data Requirements

• AI analysis works immediately but improves with data volume—at least 500 records recommended for meaningful insights

• Automated insight detection works best with 6+ months of historical data to establish patterns

• Code generation requires clear, well-structured data (clean column names, consistent formatting)

Human Oversight Still Required

• AI-generated queries should be spot-checked for accuracy, especially with complex questions

• Automated insights highlight correlations, not causation—you still need domain expertise to interpret findings

• AI can't understand organizational context, unique definitions, or nuances of your programs

Known Limitations

• Complex multi-step analyses may require breaking questions into smaller parts

• AI struggles with ambiguous questions—specificity improves results ("donors who gave in 2025" vs. "recent donors")

• Generated code occasionally needs manual refinement for edge cases or unusual data structures

• Visual customization may be limited compared to manual dashboard builders like Tableau

Data Privacy

• Your organizational data is NOT used to train AI models for other organizations

• All AI processing happens on SOC2 Type 2 certified servers; data encrypted in transit and at rest

• Full data portability—export all data and analyses at any time

• GDPR and CCPA compliant with data processing agreements available

When AI Adds Real Value vs. When It's Just Marketing

Genuinely useful AI:

• Translating questions like "show revenue by program" into complex SQL JOINs (saves hours of coding)
• Automatically detecting unusual patterns ("donor retention is 20% below average this quarter")
• Generating Python data transformations for merging multiple data sources

AI that's nice but not essential:

• Smart chart selection (you could pick charts yourself, but AI saves time)
• AI-suggested next questions based on current analysis

AI you don't need:

• If you only have basic reporting needs (monthly donation totals), Google Sheets or Looker Studio (free) are sufficient
• If you have clean data in a single spreadsheet, you don't need AI—pivot tables work fine

Bottom Line: Fabi.ai uses AI where it genuinely eliminates technical barriers—making data analysis accessible to non-technical teams who would otherwise need to hire a data analyst or spend weeks learning SQL. The AI is the core product, not a marketing add-on.

Real-World Nonprofit Use Case

A regional youth development nonprofit with 35 staff members was spending 8 hours every month manually compiling board reports from three separate systems: Google Sheets for program data, Salesforce for donor records, and SurveyMonkey for participant outcomes. Their development director would export CSVs, use VLOOKUP formulas to combine data, create charts in Excel, and paste everything into PowerPoint.

After implementing Fabi.ai, they connected all three data sources in 45 minutes. They created a Smartbook with natural language queries like "Show participant retention by program for the last 12 months" and "Compare donor acquisition costs across campaigns." The AI generated all analyses automatically with interactive visualizations.

Using Workflows, they scheduled automated monthly updates—every 1st of the month, Fabi.ai runs fresh analysis and sends updated dashboards to the board's Slack channel. The development director now spends 30 minutes reviewing AI-generated insights instead of 8 hours building reports manually.

Result: 90% reduction in reporting time (from 8 hours to 30 minutes monthly), faster identification of at-risk participants through automated pattern detection, and board members receiving real-time insights instead of month-old data. The organization redirected those 7.5 hours per month toward donor cultivation and program development.

Pricing

Starter (Free Forever)

Perfect for small nonprofits testing the platform

$0/month

25 AI requests per month
5 Smartbooks
10 dashboard viewers
All basic connectors (Google Sheets, file uploads)
No credit card required

Builder

For small teams getting started with AI analysis

$39/month per seat

Up to 3 builders

300 AI requests per month
10 Smartbooks
25 dashboard viewers
Scheduled dashboards & workflows
Application connectors access (Salesforce, HubSpot, etc.)
AI Analyst Agent configuration
14-day free trial

Team

Enterprise

For large nonprofits with advanced needs

Custom Pricing

Unlimited builders
All data connectors
Custom security review
Quarterly roadmap reviews
"Fractional data science team" support

Note: Pricing information is subject to change. Please verify current pricing directly with the vendor.

Nonprofit Discount & Special Offers

Student Discount

Students receive a 50% discount on the Builder plan, reducing the cost from $39/month to approximately $19.50/month per seat.

Nonprofit & Education Organizations

Organizations with 501(c) tax-exempt status or educational focus can contact Fabi.ai directly for potential nonprofit discounts and assistance. While specific percentage discounts aren't publicly listed, the company indicates they work with nonprofits.

How to inquire: Email [email protected] with your 501(c) determination letter or educational institution verification.

Free Tier for Testing

The Starter plan is free forever with 25 AI requests per month, 5 Smartbooks, and basic connectors. This allows small nonprofits to test the platform at no cost before committing to paid plans.

Note: Contact Fabi.ai directly for the most current nonprofit pricing options and to discuss discounts based on your organization's size and needs.

Learning Curve

Intermediate

Beginner-friendly for basic questions; intermediate for advanced analysis and workflows

Time to First Value

Initial setup: 30 minutes to 1 hour (connecting data sources, importing data)
First question & answer: Immediate (type question, get instant results)
Basic proficiency: 2-4 hours (learning question phrasing, dashboard creation)
Advanced features: 1-2 weeks (Smartbooks, automated workflows, code editing)

Technical Requirements

Comfort with spreadsheets (Excel/Google Sheets) helpful but not required
No SQL or Python knowledge required (AI generates all code)
Basic understanding of your data structure (what fields mean, where data lives)
For integrations: Admin access to connected platforms (Salesforce, HubSpot, etc.)

Support Available

Interactive product tutorials and documentation
Example queries and Smartbook templates
Email support (Builder tier and above)
Quarterly roadmap reviews and fractional data science team (Enterprise)

Pro Tip

Start with simple questions you already know the answers to (e.g., "How many total donations in 2025?"). This helps you understand how the AI interprets questions and builds confidence. Once comfortable, progress to exploratory questions where you don't know the answer upfront.

Integration & Compatibility

Connects With

Data Warehouses

Snowflake, Google BigQuery, PostgreSQL, MySQL, Redshift, Databricks

Spreadsheets & Files

Google Sheets, Excel files, CSV uploads (free plan includes these)

CRM & Sales

Salesforce, HubSpot, and other application connectors (Builder tier+)

Delivery & Collaboration

Slack, Email, Google Sheets (for automated workflow delivery)

Developer Tools

GitHub (version control for Smartbooks), MCP Server integration, API access

Platform Availability

Web-based: Chrome, Firefox, Safari, Edge (no desktop app required)
Mobile: Web-responsive interface (works in mobile browsers)
Security: SOC2 Type 2, GDPR, CCPA compliant

Data Portability

Full CSV export: Download all analysis results and raw data
Code export: All AI-generated SQL and Python code is visible and exportable
GitHub integration: Version control for Smartbooks
Dashboard sharing: Share interactive dashboards via public links

Pros & Cons

Pros

True AI-native platform: AI isn't bolted on—it's the core product, genuinely eliminating the need for SQL/Python knowledge
Free forever tier: 25 AI requests/month with basic connectors makes it accessible for tiny nonprofits to test and use
Code transparency: See and edit all AI-generated code—builds trust and enables learning
Automated workflows: Schedule insights delivery to Slack/email, eliminating manual report creation
Fast time to value: Ask questions and get answers in seconds (not hours of manual analysis)
Flexible data sources: 25+ integrations including free Google Sheets and file uploads

Cons

AI request limits on lower tiers: 25/month (free) or 300/month (Builder) may feel restrictive for active users
Viewer limits: 10 viewers (free) or 25 (Builder) can be challenging if you want to share dashboards widely
Uncertain nonprofit discount: No publicly stated nonprofit percentage—must contact sales for potential discounts
Requires clean data: AI works best with well-structured data; messy spreadsheets need cleanup first
Limited track record: Relatively new platform (active 2025-2026) compared to established BI tools
May be overkill for basic needs: If you only need simple monthly totals, free tools like Google Sheets or Looker Studio suffice

Alternatives to Consider

If Fabi.ai doesn't feel like the right fit, consider these alternatives:

Google Looker Studio

100% free, dashboard-focused BI tool

More basic than Fabi.ai but completely free with unlimited creators and viewers. Best if you need simple dashboards connected to Google Sheets or BigQuery and don't need AI-powered analysis. Ideal for nonprofits with straightforward reporting needs.

Choose Looker Studio if: Budget is your primary concern and you only need basic dashboards.

Metabase

Open-source BI with AI chatbot (Metabot)

Free self-hosted option with unlimited users. More SQL-focused than Fabi.ai but includes Metabot AI for natural language queries. Best if you have technical capacity to self-host and want open-source flexibility. Visual query builder is excellent for learning SQL.

Choose Metabase if: You want open-source control, can self-host, and prefer SQL-first workflows.

Julius AI

AI data analyst for spreadsheets and databases

Similar natural language querying to Fabi.ai but simpler interface focused on spreadsheet analysis. Handles structured and unstructured data (PDFs, documents). Best for nonprofits primarily working with spreadsheets who want conversational AI without complex BI features.

Choose Julius AI if: You primarily work with spreadsheets and want simplicity over advanced BI features.

Microsoft Power BI

Enterprise BI with AI features ($4-5/month nonprofit)

More comprehensive and established than Fabi.ai with nonprofit pricing. Steeper learning curve but more robust for complex organizational needs. Best if you need enterprise-grade features, Microsoft ecosystem integration, and proven track record.

Choose Power BI if: You want enterprise features, Microsoft integration, and can invest time in training.

Why Choose Fabi.ai Instead

Fabi.ai sits in the sweet spot between free basic tools (Looker Studio) and complex enterprise platforms (Power BI). Its AI-native design makes data analysis genuinely accessible to non-technical teams without the learning curve of traditional BI tools. Choose Fabi.ai if you need powerful analysis capabilities but lack a data analyst—it's the only platform on this list built specifically for AI-driven, conversational data exploration from the ground up.

Getting Started

Your First 48 Hours with Fabi.ai

1Sign Up and Connect Data (30-60 minutes)

Start with the free Starter plan (no credit card required) at fabi.ai. Connect your first data source—Google Sheets is the easiest starting point. Upload a CSV of donor data or program metrics.

Pro Tip:

Clean your data first—remove duplicates, ensure consistent date formats, and fill in missing column headers. The AI is only as good as the data you feed it.

2Ask Your First Questions (15-30 minutes)

Start with questions you already know the answers to: "How many total donors in 2025?" or "Show me donations by month." This helps you understand how the AI interprets questions and builds confidence in the results.

Pro Tip:

Click "View Code" on every response to see the SQL/Python the AI generated. You'll learn how to phrase questions more effectively by seeing how they translate to code.

3Create Your First Dashboard (30-45 minutes)

Use the AI to build a simple dashboard: "Create a dashboard showing monthly donation trends and top 10 donors." Let the AI auto-generate visualizations, then customize layouts and add filters as needed.

Pro Tip:

Start simple. Create a basic 2-3 chart dashboard before attempting complex multi-source analyses. You can always iterate and add complexity later.

4Set Up an Automated Workflow (Builder tier, 20-30 minutes)

If you upgrade to Builder or Team tier, schedule an automated report: every Monday morning, send updated donation metrics to your team's Slack channel or email. Set it once, never manually update again.

Pro Tip:

Test workflows manually before scheduling. Run the report once to ensure it captures the right data, then automate delivery.

Start Free Trial

Need Help with Implementation?

Setting up AI-powered data analysis can feel overwhelming, especially when you're already stretched thin managing programs and fundraising.

If you'd like expert guidance connecting your data sources, structuring effective queries, or building automated workflows with Fabi.ai, we're here to help. One Hundred Nights offers implementation support—from quick setup assistance to full-service onboarding and staff training.

We'll help you get from "drowning in spreadsheets" to "instant insights" without the trial-and-error learning curve.

Frequently Asked Questions

Is Fabi.ai free for nonprofits?

Fabi.ai offers a free Starter plan with 25 AI requests per month, 5 Smartbooks, and basic connectors—perfect for very small nonprofits testing the platform. Organizations with 501(c) status can contact [email protected] for potential nonprofit discounts on paid plans. Students receive a 50% discount on the Builder plan.

Do I need to know SQL to use Fabi.ai?

No. Fabi.ai's AI Analyst Agent lets you ask questions in plain English and automatically generates the SQL and Python code for you. You can view, edit, and learn from the code, making it valuable for both non-technical users and data teams. It's designed specifically for teams without dedicated data analysts.

What data sources does Fabi.ai connect to?

Fabi.ai connects to 25+ data sources including Google Sheets, Excel files, data warehouses (Snowflake, BigQuery, PostgreSQL, MySQL), CRMs (Salesforce, HubSpot), and application connectors. The free plan includes basic connectors and file uploads; application connectors are available on Builder tier and above.

How does Fabi.ai compare to Google Looker Studio or Metabase?

Fabi.ai is AI-native, meaning AI is built into every layer (not added as a feature). Unlike Looker Studio's dashboard-first approach or Metabase's query-focused design, Fabi.ai centers on conversational analysis with an AI agent. Choose Fabi.ai if you want natural language querying and AI-powered automation; choose Looker Studio for simple dashboards (it's free); choose Metabase for open-source flexibility and SQL-first workflows.

How long does it take to see value from Fabi.ai?

Initial setup takes 30 minutes to 1 hour (connecting data sources and importing data). You can ask your first questions and get insights immediately. AI features work best with at least 6 months of historical data and 500+ records. Full proficiency typically takes 1-2 weeks of regular use, with ongoing improvement as the AI learns from your queries.

Is my nonprofit data secure with Fabi.ai?

Yes. Fabi.ai is SOC2 Type 2 certified and GDPR/CCPA compliant. Your data is encrypted in transit and at rest. According to their privacy policy, your organizational data is not used to train AI models for other organizations. You can export all data at any time (full data portability) and maintain ownership of your information.