Building NCEATutor NZ: A Full-Stack Ed-Tech Platform

When we set out to build NCEATutor NZ, we knew we were tackling more than just another marketplace. We needed to create a platform that could match students with tutors based on complex NCEA level requirements, handle secure payments, and maintain sub-200ms query times.

Our initial implementation fetched all tutors from the database and sorted them in memory. This worked fine with 50 tutors, but we knew it would collapse under real-world load. We moved all logic into MongoDB aggregation pipelines.

pipeline = [
    {"$match": filters},
    {"$addFields": {
        "subjects_count": {"$size": "$subjects"}
    }},
    {"$sort": {"subjects_count": -1, "rating": -1}},
    {"$skip": skip},
    {"$limit": limit}
]
tutors = await db.tutors.aggregate(pipeline).to_list(None)