GOODGRAPH FOR SOCIAL IMPACT
Know what your AI is doing, and what your organization is learning.
For mission-driven organizations, the question is whether AI is improving program delivery, reporting, grantmaking, and operations without losing the local context and staff judgment that shape the result.
BUILT FROM THE FIELD
Nearly two years working alongside grassroots and mission-driven organizations.
GoodGraph has been shaped through discovery, pilots, and product development alongside food-security and community-based organizations.
We saw two things get lost repeatedly:
Meaning: the same measure or term could mean different things across reports and organizations.
Human judgment: staff added exceptions, interpretations, and local context but that knowledge could remain trapped in a conversation or workflow.
Preserving both means important knowledge doesn't disappear when staff leave or AI models change.
MEANING
Same words. Different meaning.
Reports often contain measures that look comparable but aren't.
ORGANIZATION A
People served
3,800
- Definition
- Unique individuals receiving assistance
- Source
- Annual program report
ORGANIZATION B
People served
5,200
- Definition
- Service visits during the reporting period
- Source
- Quarterly program report
NOT DIRECTLY COMPARABLE
3,800 unique individuals ≠ 5,200 service visits
GoodGraph preserves meaning and provenance so AI doesn't silently turn different evidence into the same thing.
PRESERVING HUMAN JUDGMENT
What happens when a human corrects the AI?
SCENARIOA staff member checks program eligibility
Example workflowSTAFF MEMBER ASKS
“Can a family outside our county receive emergency assistance?”
AI ANSWERS
“No. Services are limited to county residents.”
HUMAN CORRECTS
“Emergency assistance is an exception.”
QUESTION
What happens to that correction?
TODAY, WITHOUT GOODGRAPH
The correction may stay inside one conversation or workflow.
The next person, or AI system, may get the outdated answer again.
WITH GOODGRAPH
CONTEXT USED
Eligibility Policy v2
HUMAN CORRECTION CAPTURED
“Emergency assistance is an exception.”
CURRENT SOURCE IDENTIFIED
Emergency Assistance Policy
GOODGRAPH
Flags a potential context change
Needs review
HUMAN / PROGRAM OWNER
Reviews / approves
Not every correction becomes policy.
APPROVED ORGANIZATIONAL CONTEXT
Eligibility Policy v3: emergency exception recorded
APPROVED AI WORKFLOWS
Use the current exception
When human judgment is reviewed, approved, and retained, a correction can become organizational learning.
ONE STEP FURTHER
Permissioned Governance and Sharing.
Once an organization retains its context and learning, it can decide what is approved, who owns it, and what can be reused or shared.
Organizations keep their underlying context under their own control, while choosing what approved evidence to share with funders or partners.
hand over its context or use identical measures.
ORGANIZATION
Keeps its context and learning
APPROVED EVIDENCE
Shared selectively
FUNDER / INTERMEDIARY
Learns across a portfolio
HOW TO WORK WITH US
Start with one AI workflow.
Choose one recurring AI-supported workflow where staff still review, correct, or interpret the output.
We'll look at the context the AI depends on, where human judgment enters, and what evidence should be captured or retained to understand whether the work is improving.