AI copilots for Healthcare.
Production-grade copilots engineered for healthcare and life sciences.
SmartDuke builds ai copilots for healthcare and life sciences — systems that augment users inside an existing product surface with grounded, in-context intelligence. Clinician burnout is the largest unbilled cost in healthcare. AI that compresses documentation time without sacrificing audit-readiness is the obvious fix. Our approach: Latency budgets enforced from day one, retrieval tuned to in-product context, and copilot UX co-designed with your product team — not parachuted in.
The problems
we keep solving.
Clinician burnout is the largest unbilled cost in healthcare. AI that compresses documentation time without sacrificing audit-readiness is the obvious fix.
Documentation burden eats clinical time
Clinicians spend up to two hours on documentation for every hour with patients — directly contributing to burnout.
Patient triage queues grow faster than staffing
Front-line teams are overwhelmed; severity routing is inconsistent; high-acuity patients sometimes wait too long.
Medical literature volume is unmanageable
Keeping current with relevant research is structurally impossible for any individual clinician at scale.
Three things we'd build
first.
Concrete starting points for ai copilots in healthcare and life sciences. We pick the one with the highest leverage and the cleanest measurement story.
- Idea 01
Clinical-note copilot that drafts encounter notes from voice or structured input, with audit-ready citations
- Idea 02
Triage agent that scores incoming requests and routes by acuity with explainable reasoning
- Idea 03
Medical-literature RAG with source-priority ranking on peer-reviewed and guideline content
Production-grade,
from day one.
Tool-calling against the product API, RAG against in-product context, and structured outputs that the UI can render natively rather than as walls of text.
Evals before launch.
Every loop, tool call, and structured output is graded with a frozen test set and an explicit rubric. Failed evals block the deploy.
Telemetry from day one.
Traces, latency budgets, token costs, and error rates wired up before the first user touches the system.
Guardrails as architecture.
Input validation, output verification, escape hatches, and human handoff paths designed in — not bolted on after incidents.
Boring stack on the edges.
Cutting-edge model in the middle. Reliable infrastructure around it. Stability where it earns its place.
- ×Slow latency that breaks the typing flow
- ×Generic responses that don't use product context
- ×No grounding, leading to user trust collapse
- ×Poor UX integration that feels bolted on
Common questions.
01How long does it take to build ai copilots for Healthcare?
How long does it take to build ai copilots for Healthcare?
Discovery is one week. A working prototype (Spark) is 2–3 weeks. Full production Build for healthcare and life sciences typically runs 8–12 weeks depending on data complexity, integrations, and compliance scope. We commit to a precise timeline at quote stage.
02What does pricing for ai copilots typically look like?
What does pricing for ai copilots typically look like?
Every engagement is scoped to outcomes, not hours. Discovery starts in the low four figures. Spark and Build are priced per project. Embed retainers are monthly. We return a quote within 24 hours of inquiry.
03Can you take over an existing copilots project that's stalled?
Can you take over an existing copilots project that's stalled?
Yes — it's a common engagement. We review what's there, tell you honestly what stays and what we'd rebuild, then ship it to production. Healthcare engagements often start this way.
04What's different about your approach to ai copilots?
What's different about your approach to ai copilots?
Latency budgets enforced from day one, retrieval tuned to in-product context, and copilot UX co-designed with your product team — not parachuted in. We hold the same engineering bar across every engagement, regardless of industry — but the specifics for healthcare and life sciences are tuned to your trends and pain points.
Same capability, different industry.
Same industry, different capability.
Have an AI product
that needs to ship?
Tell us where you are — early concept, broken prototype, or scaling something that already works. We'll come back within 24 hours with a take and a quote.