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CASE #H1B-2847H-1B
PROCESSING
AGENT PIPELINE
DOC_INTAKE

passport · I-129 · DS-160

RAG_QUERY

policy KB + 12,400 cases

AGENT_EVAL

cross-checking eligibility

DECISION

pending

RAG SOURCES
POLICY8 CFR §214.2(h)sim:0.94
CASE#23,104 · approvedsim:0.91
POLICYUSCIS PM-602-0111.1sim:0.87

Background

Canadian visitor visas look simple on the surface but mix case-specific documents, history, and risk in ways that burn consultant hours—while the underlying rules stay structured enough to automate.

easyvisas.ai wanted an AI platform to collect documents, understand context, fill IRCC-aligned forms, and explain next steps in plain language. We shipped it end to end: multi-agent LLMs, document parsing, and form automation.

The Challenges

  • Consultants spent hours on intake and form work that didn’t need senior judgment
  • Applicants bounced between steps, unclear requirements, and slow updates
  • Rejections from errors and missing docs eroded trust and drove rework
  • IRCC changes were tracked manually—no automated way to keep workflows current
  • Growth meant hiring, not better product—no leverage in the stack

Our Approach

We designed one continuous pipeline: conversational agents own intake and follow-ups, a document layer turns uploads into structured fields, and a rules-heavy validation stage aligns that data with Canadian immigration requirements before anything is assembled for submission. Applicant messaging and status read from the same core records so the experience stays consistent end to end.

Where requirements are fixed, logic stays explicit and testable; where language and judgment matter, models sit behind structured outputs and guardrails so automation downstream stays predictable.

Challenges

Immigration software fails quietly—small errors read as rejection or lost trust. IRCC rules and forms change, so validation is never a one-time integration. Applicants need a calm, guided flow while operators still need auditability and confidence that nothing half-complete ships. The hardest work was balancing flexible conversation with first-submission accuracy, and carrying sensitive identity data safely through every step.

The Results

01

~80% less time per application vs. manual consultant workflows

02

95%+ first-submission accuracy—fewer rejections and rework

03

Same team capacity stretched across more cases

04

Clearer, faster applicant experience

05

Scale tied to the product, not only headcount

Final Takeaway

Most of the work is structured enough for software if intake, reasoning, and form generation are built deliberately. easyvisas.ai trades consultant-hour throughput for a platform that scales accuracy and cost per case.

Technologies We Use

Modern, proven technologies to build robust applications

React

React

Next.js

Next.js

Node.js

Node.js

Python

Python

G

GPT-4

L

LangChain

O

OCR Pipeline

TypeScript

TypeScript

A

AWS

P

PostgreSQL

Find your best next step

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