Precision
Of the things flagged, how many were correct.
IntelCit turns a street image, video, or location into a reviewable observation and a practical next step. A person always reviews the output and chooses what to do.
Open any service for its inputs, outputs, evidence, and known boundaries.
Every service reports observations with confidence where supported — not verdicts.
See the full evidence methodA short checklist your team can use on any result.
The short version. The full plain-language glossary lives on Science & Evidence.
Of the things flagged, how many were correct.
Of the things really there, how many were found.
A confidence score is the model's estimate for one output, not validated accuracy.
A generated example, using neutral IDs and sample data.
A reviewer opens Example segment EX-014, sees a litter count with an attention level, confirms it is accurate, and records a cleanup action.
Illustrative operating scenario, not a customer case study.
No. Every output is prepared for human review; a person makes the decision.
No. Interface previews use generated sample data, clearly labeled.
IntelCit's internal cleanliness scale from 1 (nearly clean) to 4 (very dirty).
Request a demo. The form opens your email app with a pre-filled message to info@intelcit.com.
Safe product concepts, a getting-started overview, a registry-derived service reference, and evidence concepts.
Open the docsA guided demo can walk through a service, its evidence, and the review workflow with your team.