CampusConnect is a student community and conversion platform serving universities. The platform supports prospective and current students through recruitment, admissions, transition, and retention by enabling peer-to-peer connections, live events, automated chat groups, and engagement analytics.
The client had an operational MVP when we began our work with them. The system prevented their ability to expand operations because it had critical functional deficiencies.
The platform established student connections through manual processes, which used fundamental filtering methods. The system lacked intelligent recommendation capabilities that would display the most suitable ambassadors and content to students based on their profiles, interests, and actual activities.
University staff and student ambassadors answered repetitive questions individually across multiple chat threads. The absence of first-line support automation and knowledge retrieval tools led to increased manual work demands while the organization faced challenges in responding to inquiries during peak enrollment seasons.
The system’s original design could not handle simultaneous user access at high traffic volume. The system experienced performance issues and network problems during recruitment periods when multiple students accessed the system at once.
The platform required universities to connect their existing student information systems with CRM platforms and communication tools, but its design prevented connections to third-party systems.
Crunch-IS was engaged to:
The platform was transformed from a basic community application into a sophisticated student recruitment solution for educational technology that leverages artificial intelligence to support large-scale operations.
We constructed a structured vector database through Pinecone by bringing together all university resources, together with program information, FAQs, policies, and historical Q&A data.
The system retrieves the most relevant context from this knowledge base when students ask questions via chat or search for information, and it generates accurate, personalized responses with GPT-4o.
We created a matching algorithm that connects students based on their course enrollment, geographic location, shared interests, background demographics, and behavioral signals.
The system determines optimal peer connections based on student profiles, interaction patterns, and conversation topics. Then it shows the new students’ recommended connections, ranked by importance.
We implemented WebSocket-based real-time messaging and event streaming to support live chats, group discussions, and online events without latency.
The infrastructure handles concurrent sessions for thousands of students during peak periods, with automatic scaling based on demand. The system ensures message delivery through offline message queuing, along with automatic retry mechanisms that prevent messages from being lost in the conversation.
All live events operate without interruptions because they use video integration together with live polling and moderated chat features. University teams can host multiple simultaneous events without any performance degradation.
We introduced triggered automation for key enrollment milestones. The system initiates personalized engagement workflows when a student receives an offer, joins a group, completes their profile, or stays inactive for a specific period.
The workflows execute the following processes:
Universities can create their workflows through the admin interface without needing engineering assistance.
University teams now have access to real-time visibility into:
The predictive analytics system identifies students who will stop engaging, thus enabling universities to reach out to them before they quit enrollment.
The platform was moved to AWS via containerized microservices running on ECS. The system manages recruitment season traffic spikes through automated scaling policies that operate without human intervention.
Database sharding and read replicas distribute load efficiently, while Redis caching decreases latency for frequently accessed data. The infrastructure uses Terraform for provisioning, enabling identical deployments across development, staging, and production environments.
We developed API connectors for student information systems, CRM systems, and communication platforms used by most universities. Universities use OAuth 2.0 for authentication, while all data transmission occurs through encrypted end-to-end channels.
Student data synchronization happens automatically, keeping profiles up to date without manual CSV uploads or duplicate data entry. The system reduced onboarding time for new university partners from several weeks to just 2 days.
We rebuilt the mobile applications with React Native, ensuring a consistent experience across iOS and Android. The interface prioritizes discoverability, with contextual recommendations surfaced throughout the student journey.
The rebuilt platform provided a measurable impact across enrollment, operational efficiency, and user satisfaction.
Students who make early peer connections through the platform have a threefold increase in their enrollment and first-year academic completion rates.
RAG-based automated replies handle the majority of common inquiries so that staff members can dedicate their time to resolving complicated student issues.
The system now supports thousands of users who access the platform during peak recruitment periods without service interruptions.
User experience enhancements, together with smart recommendation systems, led to higher student participation and longer platform usage time.
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