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Case study · AI/ML

AI Healthcare Assistant

Intelligent healthcare app using ML for diagnosis and treatment recommendations.

Industry
AI/ML
Engagement
Discovery → Launch
Region
Global
Status
Live

AI Healthcare Assistant · Cover image

01 · The challenge

What needed solving

HealthTech Solutions wanted a clinical decision support tool that provided accurate triage suggestions while respecting HIPAA compliance.

02 · Our approach

How we framed the work

We started with a discovery sprint to map the user journey, business goals and real constraints. From there we wrote a fixed-scope plan: clear milestones, weekly review gates on a staging URL, and a written exit criterion for every phase. The ai/ml space rewards teams that ship — not teams that plan — so we biased the engagement towards working software from week two onward.

03 · The solution

What we built

Our team trained NLP models on anonymised EHR data, implemented explainable AI modules, and built secure clinician portals with audit trails.

04 · The results

What changed for the client.

45
Clinics Onboarded
94%
Decision Accuracy
62%
Time Saved
  • Reduced patient triage time by 62%

  • Model accuracy reached 94% across 120 diagnostic categories

  • Achieved HIPAA compliance with end-to-end encryption

Tech stack

PythonTensorFlowHealthcareMLNLP

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