The Theory of Change Builder takes a project's core design and constructs the structured causal logic connecting it — making every link from activities to impact explicit, traceable, and evidenced rather than asserted.
Turns a task that typically requires deep familiarity with a Donor's evaluation standards into a guided, structured process.
The design intent is that the output drops directly into a concept note or funding proposal — not a planning artifact that then has to be translated separately.
Combined with the Climate Rationale Builder and Concept Note Evaluator, the Theory of Change Builder completes a pipeline that takes a project from initial concept through to a fully evidenced, logically coherent, submission-ready package.
It takes a project's core design — the problem it addresses, the activities planned, and the intended beneficiaries — and constructs the structured causal logic connecting them. The tool makes explicit the chain from activities to outputs, outputs to outcomes, and outcomes to long-term impact, surfacing the assumptions underlying each step so they can be reviewed and, where appropriate, supported with evidence. The goal is to address one of the most common reviewer critiques of climate finance submissions: a theory of change where the connection between what a project does and the impact it claims is asserted rather than demonstrated.
Project developers and the advisory teams supporting them — particularly those who are expert in the technical substance of a project but less familiar with the specific causal logic structure that Donor reviewers expect. It's also valuable for experienced practitioners who want a faster, more systematic first draft of a theory of change rather than building it from scratch, especially when managing multiple projects simultaneously.
At minimum, a description of the core project design: the problem being addressed, the planned activities, and the target beneficiaries or systems. The richer the input, the more precise the output — but the tool is designed to work with the kind of information a project developer typically has at the concept note stage, not to require a fully developed proposal before it can function.
The intended output combines two elements: a visual pathway mapping activities through to impact, and a narrative write-up structured to the format Donor reviewers expect. The design intent is that the output can be dropped directly into a concept note or funding proposal with minimal reformatting, rather than serving as a planning artifact that then has to be translated into a submission document separately.
Yes — that's a core design intent. Because the tool draws on the same evidence-grounded knowledge base as the rest of the platform, assumptions about climate risk, adaptive capacity, or sector-specific barriers can be checked against real climate science and national policy documentation. The goal is to flag where a causal assumption is unsupported before a Donor reviewer does.
A template or checklist gives you a structure to fill in — it doesn't help you identify whether the logic within that structure holds. The Theory of Change Builder actively reasons about whether the causal connections you're asserting are coherent and evidenced, not just whether you've filled in each box. The distinction matters because Donor reviewers assess the quality of the logic, not just its presence.
It sits between the Knowledge Vault (which provides the evidence base) and the Concept Note Evaluator (which reviews the full draft). Together, they form a pipeline: the Knowledge Vault supports evidence-grounded research, the Theory of Change Builder turns that evidence into structured causal logic, and the Concept Note Evaluator checks that the assembled document holds up to scrutiny before it reaches a Donor. Each tool reinforces the others.
The design intent is to handle the range of project types common in climate finance portfolios, including interventions that span multiple sectors or beneficiary groups. The level of granularity and precision achievable will depend on how clearly the project design inputs are specified. For very complex multi-component programs, the tool is likely to be most effective when scoped to a single component or sub-project at a time.
Like all AI-assisted drafting tools, the quality of output scales with the quality of input — vague or incomplete project descriptions will yield less precise theories of change. Additionally, the tool produces a structured draft and evidence check, not a finished document; expert review of the output before submission remains important.
Structured causal logic, evidence-checked assumptions, submission-ready output.