GradGap: Automated Prerequisite & Credit Mapping for Career Switchers

Pain Point

Career switchers face a 'black box' when applying to specialized graduate programs. A student with an English degree wanting to enter a Master of Accountancy (MAcc) or a Master's in Nursing often has 50-70% of the required general credits but lacks 4-6 specific prerequisites. Identifying exactly which undergraduate courses (e.g., 'Intro to Logic') satisfy which graduate requirements (e.g., 'Quantitative Reasoning') is a manual, error-prone process that involves scouring disparate PDF catalogs.

Target Users

• Non-traditional applicants: Liberal arts or humanities majors moving into STEM or professional fields.
• International students: Mapping foreign degree credits to US-specific prerequisites.
• Admissions consultants: Who can use the tool to speed up their service delivery.

Evidence

Multiple Reddit threads in /r/Accounting show users asking variants of: "Is it worth trying to pursue a master's with an English degree?" and "What prerequisites will I actually need?" The community response is consistently a mix of anecdotal advice and manual steps (contacting schools individually), indicating a lack of a central, automated source of truth.

MVP Idea

A 'Transcript-to-Degree' mapper.

1. Input: User uploads a PDF transcript.
2. Processing: LLM extracts course names, credits, and grades.
3. Matching: The software matches these against the published prerequisite lists of the top 20 programs in a specific field (starting with Accounting).
4. Output: A dashboard showing 'Matched,' 'In-Progress,' and 'Missing' credits, with links to accredited online courses (e.g., Coursera, StraighterLine) to fill the gaps.

Why Users Pay

This is a 'high-stakes' purchase. A user is preparing to spend $20,000-$50,000 on tuition and potentially $1,000+ on application fees. Paying $30-$50 to ensure they are actually eligible and to map out their next 6 months of prerequisite study is a low-friction decision.

Implementation Difficulty

• Data Acquisition (Moderate): Requires scraping/collecting prerequisite data from major universities. This data is public but scattered.
• Parsing (Low-Moderate): Modern LLMs (GPT-4) are excellent at transcript parsing with high accuracy.
• Matching Logic (Low): Simple logic comparing course codes and keywords.

Competitors and Alternatives

• Manual Workaround: Spreadsheets and manual emails to admissions (slow and stressful).
• Transferology: High-quality data but primarily aimed at undergrad-to-undergrad transfer, not the 'bridge' requirements for career-switching graduate degrees.
• Consultants: Charge $500-$2,000 for 'Admissions Packages' which include this mapping.

Go To Market

Target high-intent search terms like "MAcc prerequisites non-accounting major." Engage in subreddits like /r/Accounting and /r/PreNursing where this question is asked weekly. Offer a free 'Check 1 School' tier to capture leads, then upsell the 'Full Gap Analysis' for all target schools.

Revenue Potential

There are roughly 500,000 graduate school applicants in the US annually. If only 5% are career switchers (25,000) and 10% of those find the tool via search/social (2,500), at a $40 price point, this represents a $100k/year niche project for a solo developer. Expansion into Nursing, Law (JD-MBA), and CS bridge programs increases this significantly.