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Case study

Advisify

AI immigration assistant with personalized pathway recommendations grounded in CV and preferences.

LLMsRAGPythonLangChainDocument AIAWS

Problem

Immigration options change by country, visa category, and timing. Generic articles do not personalize to someone's CV or goals.

Applicants need guidance aligned with what is actually available, not one-size-fits-all advice.

Solution

We built structured intake combining conversational profile data with CV understanding, then layered retrieval on current program material.

An LLM-driven experience explains pathways and trade-offs with clear boundaries around legal advice.

Outcomes

Users receive preference-aware pathways grounded in their documents and goals.

Clear narrative from profile to actionable next steps.

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