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Application Review

A rule plus LLM hybrid that validates each submission against a long requirement guideline set and surfaces exactly which requirements pass, fail, or need a human look.

LLMRule engineDocument parsingValidation
Pass/failMarked per requirement
Flagged onlyRouted to people
At scaleFrom a team bottleneck
The problem

Each submission had to be checked against a long set of requirement guidelines for compliance and completeness, one document at a time.

Done by hand the review was slow, inconsistent between reviewers, and a bottleneck for the whole team.


How it works

Extract, verify, then route the unsure to a human.

route_to_human.pipeline Confident · auto Unsure · to a human
Incomingcases · docs
Modelconfidence
Human review
Flagged cases
Auto-resolved
Confident, cited
01

Check every requirement

Each submission is checked against every requirement in the guideline set, not a sampled subset. Deterministic rules catch the cases rules do well.

02

Apply judgment

The LLM handles the requirements that need reading and judgment, the ones a rule cannot express cleanly.

03

Route the unsure

Each requirement is marked pass, fail, or needs-a-human. Reviewers spend their time only on fails and uncertain cases.


What shipped

Compliance and completeness checks that used to bottleneck a team now run at scale, applied the same way every time.

Humans review only the flagged cases instead of reading every submission end to end.

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