When a registrar uploads a transcript to VAST, a lot happens in a very short time. What used to take a trained evaluator 30-60 minutes now takes less than a minute — but the AI isn't cutting corners. It's doing more work, faster and more consistently.
Here's a step-by-step look at the pipeline.
Step 1: Document Ingestion (0-2 seconds)
VAST accepts transcripts in PDF, JPG, and PNG formats. The system first determines the document type and quality:
- Is it a digital PDF or a scanned image?
- Is it single-page or multi-page?
- What's the resolution and readability?
For scanned documents, VAST applies image enhancement — adjusting contrast, correcting skew, and sharpening text — before proceeding to extraction.
Step 2: AI-Powered Data Extraction (2-15 seconds)
This is where the magic happens. VAST's AI engine reads the entire transcript and extracts structured data:
- Student information: name, ID, dates of attendance
- Institution details: school name, accreditation, location
- Academic records: courses, grades, credit hours, term-by-term
- GPA data: cumulative, term-level, and any honors designations
The AI has been trained on thousands of transcript formats from institutions across the country. It understands the difference between quarter hours and semester hours, weighted and unweighted GPAs, and the countless ways schools format their academic records.
Think of it like an experienced evaluator who has seen every transcript format imaginable — except this one never gets tired and processes each document the same way, every time.
Step 3: GPA Recalculation (15-20 seconds)
Raw extraction isn't enough. VAST recalculates the student's GPA according to your institution's specific grading scale. This accounts for:
- Different grading systems (4.0, 5.0, percentage-based)
- Credit hour weighting differences
- Pass/fail course handling
- Repeated course policies
Step 4: Course Equivalency Matching (20-40 seconds)
VAST compares each extracted course against your institution's equivalency database. Using both exact matching and AI-powered similarity analysis, it identifies:
- Direct equivalencies from existing articulation agreements
- Probable matches based on course title, description, and credit hours
- Courses that require manual review (flagged with confidence scores)
The Confidence Score System
Every match comes with a confidence score. High-confidence matches (90%+) can be auto-approved based on your institution's policies. Lower-confidence matches are queued for human review — ensuring your team's expertise is applied exactly where it's needed.
Step 5: Evaluation Summary (40-60 seconds)
Finally, VAST generates a comprehensive evaluation summary that includes:
- Total transferable credits
- Recalculated GPA
- Course-by-course equivalency mapping
- Flagged items requiring human review
- Export-ready data for your SIS or CRM
The entire process — from upload to evaluation — completes in under 60 seconds. Your evaluators can then review the AI's work, approve or modify recommendations, and move on to the next transcript.
What This Means for Your Team
With VAST handling the heavy lifting, your evaluators become reviewers rather than processors. They're no longer spending their expertise on data entry and GPA math. Instead, they're making judgment calls on edge cases, advising students, and ensuring quality — the work that actually requires a human touch.
Want to see it in action? Book a live demo and watch VAST process one of your own transcripts in real time.