What CI DOES — And Doesn't (Yet)
We are a lab. We are always learning and evolving decision tools and services from rich work in practices areas. We work with partner to solve challenges in their communities. The more we learn on each engagement the more sharper our tools and services become.
This piece outlines where we are heading.
What Community Intelligence Actually Does — And Doesn't Yet
Every funder placing dollars in a community is making a bet about whether that community will actually use what gets built. Almost none of that bet is informed by data — because the data that would inform it doesn't exist in the standard toolkit.
Demographic data tells you who lives somewhere. Polling tells you what people say they'll do. Neither tells you how trust actually moves through a place — who a community listens to, which institutions it has already written off, and where the social fabric is strong enough to carry a program past its launch. Community Intelligence (CI) was built to close that specific, narrow gap: not to replace program judgment, but to give it a ground-truth layer it currently lacks.
Census-Tract Precision, Not a Survey
CI reads structural trust patterns at census-tract resolution — roughly 4,000 people per tract — using behavioral indicators drawn from public and administrative records, not surveys and not individual profiling. It collects zero personally identifiable information at any stage. It cannot name, identify, or count specific people. What it produces is a structural read of a place; identifying the actual people who carry trust in that place is human fieldwork the read informs, not something the instrument does itself.
The current architecture tracks roughly 350 indicators, of which 140–145 are typically populated for a given census tract, across seven civic domains carrying tract-level signal (two of nine originally scoped domains — Governance and Safety — are anchored to city-level values only and do not yet have tract resolution; we say so rather than blur the two). Inputs refresh on an annual cycle to five-year rolling averages — this is not a live sensor network, and we don't describe it as one.
Tested & In Active Use — vs. — In the Lab
Every instrument we name carries a stated test status. Where nothing has been tested, we say "tested against: none" rather than imply otherwise. That standard governs everything below.
Tested & In Active Use
- Floor Identification — reliably finds the most institutionally disconnected places in a district. Validated against real turnout outcomes (see Proof, below).
- Trust Flow mapping & Dark Spots — structural reachability variance within a single geography, independent of poverty.
- Institutional-gap divergence — comparing what institutions market against what neighborhoods actually measure.
In the Lab
- Gradient ranking — ordering places by degree of connection, not just floor vs. not-floor. Tested and did not hold; not offered as a capability.
- Trust Elasticity / Trust Resilience — tested at essentially no measured relationship to behavior; not claimed as predictive.
- Sustainability / stewardship prediction — CI can find which channel is likely to carry a program; whether it sustains is a tracking question during the engagement, not a pre-spend prediction.
A null or failed test is information we report, not a result we bury. That is a deliberate methodology stance, not a gap we're hoping you won't ask about.
Two Anchors, With Real Numbers
Three Uses, Not One Product
| Use | What It Adds |
|---|---|
| Pre-grant due diligence | A structural read of whether a proposed geography has the trust infrastructure to carry a place-based grant — before commitment, not after. |
| Cohort / portfolio selection | Comparing candidate communities on reachability and institutional-gap variance, with a stated coverage rule for which geographies are actually classified. |
| Community-first digital & civic tech evaluation | Reading whether a proposed digital tool is being built from an existing trust network in a place, or imposed on one — directly relevant to funders wary of novelty-first tech bets. |
The Honest Boundary
CI will not tell you whether a specific program will succeed — it tells you about the trust terrain the program will land on. It will not name or count individuals. It will not rank places by degree of connection with confidence we don't have. It will not produce a "89% accurate" headline number — no such study exists, and we won't manufacture one to make a pitch land. Where a geography isn't yet classified, we say so plainly rather than imply national coverage that doesn't exist yet.
This is not a deficit framing. It's the same discipline we'd want from any instrument asking a funder to change how it places capital.
RFUTR Inc. is the 501(c)(3) that carries this work into civic and place-based practice — non-electoral, structurally separate from our commercial licensing partners. We'd rather show you where the instrument is strong, where it's still R&D, and let that honesty be the pitch.