Philanthropic Architecture

This system was developed for a private philanthropic foundation managing a wide network of people, organisations, and activities.

The client is responsible for reviewing grant applications and expressions of interest, maintaining relationships with grantees, and tracking how funding translates into measurable impact over time. This includes following ongoing projects, attending events, and keeping context on who is involved across initiatives, collaborations, and funded work.

For this foundation, decisions are not isolated. A single grant may relate to previous funding, build on earlier collaborations, or introduce new organisations into the network. Understanding these connections depends on consistently keeping track of interactions across people, projects, and initiatives, without relying on memory.

Reconstructing the history of a relationship or project often requires checking multiple sources of information and remembering subtle details. This makes it difficult for the client to manage ongoing work and hand over responsibilities as the foundation grows and more team members become involved.

The foundation’s knowledge exists across personal notes, spreadsheets, email threads, WhatsApp messages, and informal conversations, depending on the situation. This makes it difficult to review past funding decisions, understand how relationships have developed over time, or explain how specific outcomes connect back to earlier support.

The approach was to treat each type of activity the foundation manages as a separate record, rather than combining them into single notes or summaries.

People, funding decisions, projects, events, and outcomes were structured as distinct datasets so they could be linked over time. This allows a grant to connect to a project, that project to appear across events, and outcomes to be recorded later without rewriting the same information in multiple places.

The structure was designed so that past decisions remain traceable and new information can be added without losing earlier context.

Each part of the process is handled by a separate component:

The system is implemented as a Notion workspace structured around a set of connected databases forming a central relational layer. Each database represents a different type of record, with relationships allowing information to be shared across people, initiatives, projects, events, and support.

Information is added through forms, buttons, and guided interfaces rather than direct editing of the databases. This ensures consistency in how data is entered and reduces the risk of accidental changes. Notion automations are used to route entries and maintain connections between records, while Notion AI supports querying and navigating the dataset.

Access is managed through role-based dashboards, where each team member interacts only with the information relevant to their responsibilities. Sensitive data, such as funding details or internal notes, remains restricted while still allowing operational work to be distributed across the team.

The current system captures relationships and activities in a structured format that can be queried within the workspace. The next step is to extend this into a graph-based layer, where connections between people, initiatives, projects, events, and funding can be explored more directly.

This would allow the foundation to examine patterns across its network, such as repeated collaborations, funding concentration, or how different initiatives connect through shared participants.