Advisory · Multi-Agent PlatformLive: MVP Deployed

Advisify

How AZK.AI engineered a multi-agent policy matching platform to automate complex immigration eligibility evaluations with 100% auditable citations.

3x
Workflow Velocity
Turnaround times cut from 1–5 days to under 5 minutes
100%
Cited Guidance
Every recommendation references verified governmental policy lines
45%
Process Streamlining
Reduced human verification friction across standard files

Client Challenge

Immigration advisors and applicants manually parse tens of thousands of constantly shifting visa laws, guidelines, and policy briefs. General LLM assistants hallucinate immigration criteria, fail to capture live regulatory updates due to cut-off windows, and lack reliable data citations. This creates massive administrative waste and introduces liability risks for professional practices.

Objectives

  • Reduce prospective candidate evaluation timelines from business days to real-time.
  • Provide zero-hallucination compliance checking with exact references to governmental source materials.
  • Implement multi-model evaluation systems that guarantee output reliability across edge cases.

Solution Design

We designed an advanced multi-agent system utilizing separate roles to index, check, evaluate, and cite candidate profiles.

First, the system normalizes the candidate profile (degrees, age, financial backing). Next, it routes queries to a custom RAG indexing database of up-to-date immigration guidelines. The profile then passes through a deterministic rule filter to check baseline exclusions, followed by an evaluation agent network running GPT-4.1 and Claude Sonnet to compare matching pathways, generate recommendations, and output a structured report with cited references.

Implementation Process

01

Phase 1: Knowledge Ingestion

Mapped and indexed municipal immigration manuals and visa codes into vectorized database instances.

02

Phase 2: Agent Configuration

Configured separate reasoning roles for eligibility mapping, rule checks, consensus scoring, and formatting.

03

Phase 3: Human Gateways

Integrated human-in-the-loop validation dashboards to automatically flag low-confidence scoring files for senior reviews.

Results & Business Outcomes

< 5 Minutes Evaluation

Evaluations dropped from days of research to minutes, enabling immigration firms to scale their customer acquisition loops.

Zero Liability Risk

By providing complete compliance citations, senior advisors check output logic and verify accuracy in real time.

Technology Stack

Next.jsPython FastAPIGPT-4.1Claude SonnetMongoDBPinecone Vector SearchAWS VPC

System Architecture Flow

01
User Profile Ingestion

Collects nationality, degrees, finance, and career details.

02
RAG Retrieval

Semantic search checks active, dynamic visa law database files.

03
Rule Filter

Deterministic checks to eliminate clearly invalid paths first.

04
Agent Consensus

GPT-4.1 and Claude cross-weigh eligibility profiles.

05
Cited Audit Trail

Generates report with exact links to governmental codes.

Advisify Advisor Dashboard Mockup

Simulated user interface showing dynamic RAG retrieval, profile parameters, confidence scores, and citation links.

advisify.ai/dashboard/advisory-run-094
98.4% Confidence
1. PROFILE SPECIFICS
Nationality: Australia
Education: MSc Software Eng
Experience: 5 Years
Finances: Approved
• RECOMMENDATION & CITATION FEED

Based on rules mapped from Immigration Code Section 18.2, candidate qualifies for the Skilled Work Stream (Class 189).

Reference: VISA-S189-APolicy Manual: Page 144
Report Status: Ready for verification
ARCHITECTURE FIRST

Need an AI Strategy Before You Build?

Book a complimentary AI Architecture Review. We'll assess your use case, identify opportunities, evaluate technical feasibility, and provide clear implementation recommendations.