MediConsult — Engineering Case Study

MediConsult is an employer product in the healthcare domain. It is an AI-powered Electronic Medical Record for doctors and nurses on Android phones and tablets, currently in internal pilot. Herry contributed as a Full Stack Engineer with a focus on applied AI and full-stack integration. Source code and internal implementation details remain private.

Project context

MediConsult is an employer product where the name may be used publicly and technical discussion is allowed while source code remains private. The product is in internal pilot, available as a pilot build for Android rather than a public store release.

Platforms include Android, web, backend and AI backend. Capabilities include Applied AI, Backend Engineering, Mobile Engineering and Web Engineering. Technologies include Ollama and responsibilities have included AI integration, backend development and frontend development.

Healthcare workflow context

The product supports clinical workflows for doctors and nurses including patient worklists with Waiting, Active and Done states, structured SOAP consultation notes, allergy information, ICD-10 support, AI suggestions, voice dictation, medication orders, laboratory orders, radiology orders, urgent flags and stock-aware medication information with review and acceptance of AI recommendations on Android phone and tablet.

AI suggestions are presented as review-oriented assistance where clinicians review and decide, rather than autonomous decisions. Consultation and order screens keep allergy and admission context visible to support safe review.

Role and contribution boundary

Herry’s role is Full Stack Engineer from 2026 to present, within the broader Alocare employment that also covers MediConsult. His responsibilities have included AI integration alongside backend and frontend development.

Herry contributed across backend, mobile and web surfaces, with work that covered applied AI and integration. Source code and internal implementation details remain private, and this narrative does not claim ownership of every product feature.

Applied AI engineering

The work is applied-AI engineering focused on evaluating and integrating AI capabilities into product workflows rather than foundational-model research.

Herry contributed to applied-AI engineering and integrating AI capability into application and backend surfaces and into frontend and mobile surfaces where required.

Locally deployed AI and Ollama

Locally deployed AI is part of the product’s engineering themes, with Ollama as the established technology for local model deployment. Herry worked with locally deployed AI and with Ollama as part of that context.

Model evaluation and prompt engineering

Model selection and evaluation and prompt engineering were part of the engineering work, focused on assessing and integrating models for product use.

OCR and medical-information processing context

OCR is part of the established applied-AI experience. Its relationship to structured clinical documentation and AI-assisted suggestions is described only at the capability level, without attributing a specific pipeline to the product.

Backend and API integration

MediConsult’s product workflow includes worklist management and order handling.

Herry’s established responsibilities include backend development and API integration.

Mobile and web AI integration

MediConsult is designed for Android phones and tablets for clinical use, with SOAP documentation and order management accessible on those devices and AI suggestions presented for clinician review and acceptance.

Herry’s established work includes frontend and mobile integration.

Human review around AI-assisted workflows

AI suggestions are used in a human-in-the-loop pattern. The case study presents them as review-oriented assistance where healthcare users review and act, not as autonomous medical authority or certified clinical decision support.

Private-source and confidentiality boundary

MediConsult is a private-source product. No patient names, medical record numbers, credentials, demo patient data or proprietary internal details are disclosed. No screenshots, sample data or internal instructions are reproduced.

Engineering takeaways

Working with locally deployed AI, model evaluation, prompt engineering and OCR as applied-AI engineering — integrating capabilities into backend, API and mobile surfaces — reinforced the importance of connecting product understanding and engineering contribution across multiple surfaces.

This case study complements the Product Overview, which describes what the product is, while this narrative describes the engineering contribution around it.