Grant eligibility
Every application read against the rule it rests on, before it is submitted.
The situation
A funding programme where eligibility depends on rules spread across long, inconsistent documents that change over time, and where evaluators spent about a week per application finding the issue that would reject it.
How it works
Ingest
a parser and indexing layer digest regulatory documents and applications in every format they arrive in (structured and unstructured PDFs, DOC files, awkward encodings, split sections) into a corpus the model can query.
Evaluate in stages
strategic fit first, so a clear mismatch is rejected early; then the detailed programme criteria, each checked against the indexed rule, not the model's general knowledge.
Learn from decisions
past approvals and rejections are the training and evaluation set. Rejections are the most valuable part: they reveal the exact criteria that get a file thrown out, so the model flags those before submission. Rules are ingested per jurisdiction, never assumed global.
Outcome
issue found in 80% of candidates · about a week of evaluator time per file, now minutes · every decision cites its rule.
Hardest part
The rules are not in one place and they are not clean. Eligibility depends on programme criteria, the legislation above them and each jurisdiction's own layer, spread across long documents in inconsistent formats that change over time. The hard part was ingestion robust enough that an amended or reformatted document does not silently break the parser, and grounding tight enough that every decision points to the specific rule behind it. "Probably eligible" is worthless here. Someone has to be able to defend the answer.
See how this maps to your business.
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