Offline-First Django CRM Development
Freelancer — Systems Architect
The Service of Applied Psychology at UNED needed a CRM system to manage patient cases and session schedules while complying with strict university regulations: no internet connection, full local data control, and access restricted to authorized administrative personnel only.
Commercial CRM solutions could not meet the university’s data sovereignty and security requirements.
The opportunity was to design and deliver a fully offline, GDPR-compliant CRM system capable of managing patient data, therapist schedules, supervisions, and administrative reporting, all from a single secured local machine.
- Designed and built an offline-capable CRM platform using Django, deployed locally on a dedicated Windows machine.
- Developed models and workflows for patient management, case tracking, session scheduling, therapist coordination, payment recording, and supervision logs.
- Implemented user authentication, access controls, and local backup procedures to secure sensitive data without cloud reliance.
- Built the system modularly to allow administrative users to operate independently with minimal technical intervention.
- Conducted full training for the administrative team on platform operation, basic maintenance, and data protection best practices.
- Documented all system procedures and provided a localized offline user manual.
- Delivered a fully functional, offline-first CRM that met all UNED’s data protection, access control, and operational requirements.
- Enabled efficient patient intake, scheduling, and case management without external software dependencies.
- Reduced administrative overhead by centralizing previously fragmented workflows into one streamlined system.
- Achieved full GDPR compliance for patient data storage and management within a university context.
Django-Based Collaborative Dissertation Platform
Freelancer — Systems Architect
Traditional academic supervision tools (Word, email, PDFs) were unstructured, hard to track, and inefficient for managing feedback on a 300+ page dissertation under constant revision.
The goal was to build a purpose-built collaboration platform for real-time document review between PhD student and advisor.
Academic advisors needed a structured way to comment on specific sections, track changes over time, and reference data tables and figures — none of which was well-supported by traditional tools.
The opportunity was to build a lightweight but powerful Django-based app that enabled inline feedback, review tracking, and custom integration of code-generated content.
- Designed a custom collaboration platform tailored to the academic supervision workflow, enabling structured feedback and version control across long-form documents.
- Built a local-first system that prioritized data privacy, modularity, and full author control over content and revisions.
- Developed flexible editing and commenting capabilities to support granular, sentence-level review and iterative improvement.
- Implemented dynamic content handling to support integration of external elements such as data tables and figures generated in Python.
- Created administrative tools to manage documents, track feedback cycles, and support academic process transparency.
- Future-proofed the architecture to accommodate citation logic, content compilation, and extended use beyond a single dissertation.
- Eliminated friction in PhD feedback loops — supervisor could leave comments per sentence, reducing back-and-forth confusion.
- Enabled centralized review across dozens of chapters, interviews, figures, and datasets.
- Significantly reduced cognitive load for managing revision cycles and integrating comments.
- Demonstrated feasibility of a structured alternative to traditional word processors for academic research.