Diabetes projects range from focused mobile MVPs to enterprise-grade platforms that serve health systems and payer organizations. Chudovo scopes each project against the client’s stage and market.
| MVP | Enterprise Platform |
| Glucose tracking (manual + one CGM) | Multi-CGM and multi-pump support |
| Medication reminders | EHR integrations (Epic, Cerner, athenahealth) |
| Basic patient reports | Advanced analytics dashboards |
| Single patient profile | Multi-clinic and care team management |
| Notifications | AI-powered predictions and clinical decision support |
| Cloud backend | Enterprise-scale infrastructure with high availability |
| Web + mobile (patient-facing) | Patient, clinician, caregiver, and admin portals |
| Basic HIPAA compliance | Full compliance program (HIPAA, FDA, MDR, IEC 62304) |
Timelines depend on scope, integrations, and the compliance program the product must meet. The ranges below reflect typical diabetes projects Chudovo delivers.
| Phase | Timeline | What It Covers |
| Discovery | 2–4 weeks | Scoping, architecture, compliance planning |
| MVP | 3–5 months | First functional version for market validation |
| Enterprise Platform | 6–12 months | Production-ready platform with device integrations, EHR connectivity, and full compliance program |
Final timelines are set during discovery based on the specifics of each project.
Off-the-shelf diabetes platforms work for some organizations, but many clients reach a point where the platform’s constraints limit their business. The comparison below shows what changes when a client moves from off-the-shelf to custom.
| Off-the-Shelf | Custom Software |
| Limited customization to the vendor’s roadmap | Tailored to the client’s workflows and roadmap |
| Fixed set of devices and EHR integrations | Any device and any integration the client needs |
| Vendor lock-in and roadmap dependency | Full ownership of code and roadmap |
| Ongoing subscription fees | One-time investment with long-term ROI |
| Generic user experience | Brand-aligned UX for patients and clinicians |
| Limited access to underlying data | Full access to data for analytics and AI |