Delta Analytics: Nonprofit partnerships

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Every year, Delta Analytics partners skilled data scientists, engineers and analysts with nonprofits around the world for free. We provide a wide range of data-related services catering to non-profits big and small. Very few projects are straightforward but all start off with a question. Where is my funding coming from? How did my free after-school mentoring program impact test scores? How many people have we reached in the past 6 months?

Armed with a clear question, we can decide what services best illuminate an answer. That is why we start off with an application process -- we want to work with nonprofits who have a well-defined sense of what they want to achieve. Our potential services are described in more detail below.

If you have data but are unsure what to make of it, we can help transform the data into something meaningful. We can set up data management systems that let you pull important insights from the information at your fingertips.

Delta can run statistical analysis to help assess impact on measurable variables. For instance, we can tell an environmental organization how much waste it has reduced per dollar spent.

Understanding who you work with is crucial to maximizing your influence; Delta can analyze data to help you categorize your market. For example, we can track characteristics of donors, clients, or volunteers, and provide insights on the demographics of stakeholders. 

Delta creates engaging graphs, charts, and tables to help you visualize data. These can be utilized for internal processes or to show off your organization's impact to the world.

Interested in adding AI to your organization? Delta can build LLM pipelines to enable AI workloads either customer facing, or for internal use, e.g., building a knowledge base of organizational information.

Have questions about the application process? See this guide first, and if you have questions reach out to inquries@deltanaltyics.org

Many early-stage nonprofits are eager to leverage modern data tools and artificial intelligence but lack the technical infrastructure or data strategy required for traditional data science grants. The AI Enablement Program bridges this technical gap by providing structured training, hands-on mentorship, and custom implementation support.

• Duration: 6 Months (3 months of curriculum development & NGO selection, followed by 3 months of active workshops and implementation).
• Cohort Size: 4–5 select nonprofit organizations per cohort to ensure deep, tailored support.
• Format: 5 Hands-on practical AI workshops held once or twice a month, combined with direct Delta Fellow mentorship.
• Outcome: Every participating nonprofit will build and deploy a working AI solution for a real organizational challenge by the end of the program.

• Use standard cloud tools (e.g., Google Workspace).
• Have foundational digital data (surveys, documents, spreadsheets) ready to be utilized.
• Are willing to complete baseline training on generative AI and prompt engineering prior to workshops. Absolutely no coding or technical experience is required!
• Seek practical, high-impact AI capabilities to automate processes, analyze data, or enhance decision-making.

Our curriculum emphasizes capabilities over specific tools, combining theoretical foundations with immediate hands-on practice:

1. AI for Data & Spreadsheets
   • Natural Language Processing (NLP) on survey responses and qualitative data.
   • Automated report generation and key insight extraction for impact reporting.

1. AI for Documents & Organizational Knowledge
   • Building Retrieval-Augmented Generation (RAG) chatbots over internal files and grant archives.
   • Accelerating grant research, writing, and administrative document retrieval.

1. AI Workflows & Process Automation
   • Designing automated workflows to streamline operations.
   • Application examples: volunteer matching, response categorization, and grant pipeline tracking.

1. Responsible AI, Ethics & Governance
   • Navigating bias, fairness, privacy, and data security.
   • Developing organizational AI governance and risk management frameworks.
   • Practical evaluation of AI outputs for accuracy and reliability in nonprofit settings.