Project Overview
Saiwa Inc. recently developed and delivered an AI-powered platform that helps Indigenous students in Canada quickly discover scholarships that fit their background, study plans, and location for Saige Inc. The system continuously reads publicly available scholarship listings, normalizes each record, and matches opportunities to students through a guided questionnaire and a ranking engine.
Core Capabilities
- Scholarship & Normalized Database
Automated collection from the official bursaries portal with robust parsing and schema mapping. Each record is standardized and stored with the appropriate fields for precise filtering and matching. - Guided Student Questionnaire
A friendly, step-by-step flow captures the essentials needed for accurate matching. - AI Matching & Ranking
Using the questionnaire inputs, the engine scores opportunities across identity, geography, school and program criteria, GPA and other eligibility signals. AI-Assisted Application Pre-Fill
For matched opportunities, the platform can pre-fill application forms from the scholarship texts, helping reduce errors and save time (admin can review and edit before submission).- Admin Panel
Admins can review, correct, and approve parsed fields, ensuring high data quality.
Workflow & Deliverables
- Phase 1 – Data Ingestion & Schema (March 2025)
- Phase 2 – Questionnaire & Matching (March 2025)
- Phase 3 – Application Pre-Fill, UX & Launch (April 2025)
Impact & Benefits
- Access & Equity: Makes it easier for First Nation, Inuit, and Métis students to discover funding aligned with their identity, program, and location—without sifting through hundreds of pages.
- Time Saved: Guided questions + AI matching drastically reduce search time and manual form entry.
- Quality & Freshness: Admin validation plus periodic refresh ensures accurate, up-to-date listings tied to the government source of truth.
Roles & Collaboration
- SAIGE
Project sponsor and beneficiary; defined student experiences goals and acceptance criteria. Saiwa Inc.
Led the end-to-end technical implementation: data ingestion and normalization, questionnaire design, AI matching and ranking, application pre-fill, admin tools, QA, and deployment.
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