Imagine an EMR that thinks alongside the neurosurgeon.
Elkra is a white-label neurology practice management SaaS, clinics onboard via custom URL, brand it, and run it inside their own walls. The MVP worked. The UX hadn’t kept up. The founder, Dr. Ramy, brought us in to revamp every flow and bake AI into the platform as connective tissue, not a chat-bubble bolted on, but a Copilot trained on the clinic’s own protocols and a Scribe that recommends tests from a recording.
Denovers walked in with my cluttered MVP and walked out 90 days later with an AI-native neurology platform our clinicians actually want to use. They embedded with our team, shipped with us daily, and treated AI as a layer instead of a screen, exactly how we needed it built.
Elkra is the operational spine of a neurology clinic, patients, workflows, protocols, reports, scribe. The MVP worked. The UX hadn’t kept up. Dr. Ramy and the team brought us in to revamp every flow and bake AI into the platform, not a chat-bubble bolt-on, but a Copilot trained on the clinic’s own protocols and a Scribe that thinks like a clinician. The audit named four heaviest costs (cluttered nav, scattered patient info, untracked workflow status, AI as an island), and those four problems became the four chapters of the redesign.
One dedicated product designer embedded with Dr. Ramy and the dev team, daily syncs, no async hand-offs. Each surface was designed, reviewed, and built in the same week, with AI integrations scoped alongside the visual redesign so the Copilot and Scribe shipped as part of the platform, not on top of it. White-label support went in as the foundation: custom URL, branded UI, clinic-built forms, multi-license billing. Live inside the fundraising window.
Audit-led: catalogued where clinicians lost time, then redesigned the four problem surfaces in parallel with implementation. Every flow shipped reviewed and built in the same week.
The Copilot trained on the clinic’s own protocols + the ambient AI Scribe with test recommendations were designed into the platform, not bolted on, so AI became the navigation and documentation layer.
A working MVP can hide a lot. The screens loaded, the data persisted, the basic flows completed, but the cost of using the product piled up everywhere a clinician’s attention should have been. The audit named four heaviest costs: cluttered navigation, scattered patient info, untracked workflow status, AI as an island. Each one paired below with the real before-shot from the MVP.
Discovery was the MVP’s biggest UX failure, clinicians knew Elkra had powerful features but couldn’t remember where they lived. Instead of redesigning a deeper menu tree, we made AI the navigation layer. The Copilot is trained on the clinic’s own protocols, reports, and patient data, so “which patients need an MRI in two days?” filters the list in one go, and dropping in a referral letter returns next-step recommendations. The chat surface replaces the menu tree.
In the MVP, a patient lived in five places at once. Scribe, workflows, protocols, reports, each on its own screen. We rebuilt around one principle: the patient is the unit, not the feature. Every flow that touches a patient now lives inside that patient’s card, sections collapse inline, the Scribe records right there, the timeline stretches across the bottom, protocols and reports surface as tabs. The clinician opens one surface and gets the whole patient.
Healthcare workflows are state machines pretending to be checklists: ordered → authorized → called → scheduled → billed. The MVP inferred status from scattered fields. We rebuilt the workflow as an explicit timeline with each stage tracked, dated, and attributed; above it sits a Kanban management view that operates across every patient at once, so the coordinator sees every workflow and report that needs attention without clicking into each patient individually.
We collapsed several disconnected dashboards into a single aligned operating view. KPIs, weekly/monthly/yearly graphs, an insurance-provider breakdown that matters in the US clinical context, and recents across patients, workflows, reports, and AI Scribes. Then we shipped a drag-and-drop form builder, primitive blocks the clinic admin assembles into intake, follow-up, or post-op forms that feed downstream into reports and the timeline. The same engine powers the white-label rollout: custom URL, branded UI, clinic-built protocols.
Roughly 90 days from audit to live: trained Copilot, ambient AI Scribe, unified patient surface, timeline-aware workflows, Kanban management view, custom form builder, multi-license billing. In clinics today, ready for the white-label rollout to additional neurosurgery practices.
