The brief
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.
- Project
- easyvisas
- Year
- 2026
- Type
- AI Immigration Platform
- Stack
- Frontend, Backend, AI/ML, Document Processing, Language, Cloud, Database
- Services used
Challenge
What was in the way
- 01
Senior time lost to intake and forms
- 02
Unclear steps and slow updates
- 03
Errors and missing documents caused rejections
- 04
IRCC changes tracked by hand
- 05
Growth depended on hiring
Approach
How we built it
- 01
Conversational intake
- Adaptive question flow
- OCR + LLM extraction
- Structured outputs for forms
- 02
Form generation
- IMM 1295 population
- Completeness checks
- PDF package assembly
- 03
Status & comms
- Status tracking
- Plain-language messaging
- Deadline reminders
Results
What changed
~80% less time per application vs. manual consultant workflows
95%+ first-submission accuracy—fewer rejections and rework
Same team capacity stretched across more cases
Clearer, faster applicant experience
Scale driven by the product
Case studies
All case studies