A clinical assistant for treatment planning and source review.

Start with a case question or source packet. Manoa works through the missing context, grounds each recommendation in the thread, and returns ranked treatment paths with rationale, tradeoffs, and citations clinicians can review before acting.

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Obesity + type 2 diabetes treatment options

Clinical question

Rank semaglutide versus tirzepatide for a new primary care patient with obesity and type 2 diabetes, then tell me what details would materially change the plan.

Reviewable recommendation

Coverage-first branch

Semaglutide first, tirzepatide as the access backup

This branch keeps the recommendation anchored to the cleanest likely path to action while still addressing glycemic control and obesity goals.

Fastest likely approval is the stated priority in this branch.

Coverage friction is not secondary here

The full workspace keeps the source trail and branch conditions attached to the recommendation.

Unified workspace

Ask, ground, and rank in one flow.

The assistant stays in the case: it works through missing context, keeps the source packet visible, and turns the thread into reviewable output instead of isolated chat responses.

Ask

Start from the case

Open with the treatment decision or source packet that needs pressure-testing.

Ground

Pull in the right context

Keep chart context, public evidence, and access constraints in the same working view.

Deliver

Return reviewable output

Produce ranked treatment paths with rationale, branch conditions, and citations.

Case reasoning

Navigate high-stakes treatment questions with an always-on clinical coworker.

Start with a real treatment question and keep iterating until the case is specific enough to support a recommendation. The assistant behaves more like a second reader than a generic prompt box.

Case-first chat

Start with the treatment decision, not a template. Manoa asks targeted follow-ups until the thread is specific enough to rank options.

Source-aware analysis

The assistant keeps notes, labs, payer rules, and public evidence in the same working view instead of forcing clinicians to reconstruct context from scratch.

Visible support

Every recommendation stays tied to cited support so a clinician can verify the reasoning before sharing or acting.

Live case thread

From clinical question to ranked recommendation

Treatment question

PCP note

Payer screenshot

Rank semaglutide versus tirzepatide for a new primary care patient with obesity and type 2 diabetes, then tell me what details would materially change the plan.

Missing context

Clarify prior exposure, comorbidities, and approval constraints before ranking.
Keep the working recommendation visible as new context arrives.

Working recommendation

Semaglutide first, tirzepatide as the access backup

This branch keeps the recommendation anchored to the cleanest likely path to action while still addressing glycemic control and obesity goals.

Source trail stays attached

Review-ready work product

Produce decision-ready treatment plans without switching contexts.

The thread should end in something a clinician can review and use. Manoa turns rough case exploration into structured output without losing the source trail or the conditions that shaped the ranking.

Ranked treatment paths

Return one to three reasonable paths, ordered for the current case rather than a generic protocol.

Branch conditions

Call out the contraindications, access issues, and patient goals most likely to change the ranking.

Shareable work product

Turn the thread into a structured packet a clinician can discuss, document, or hand off with the source trail intact.

Review-ready output

Treatment planning that reads like work product, not a chat log.

The answer can stay concise for a quick consult or expand into a structured packet with rationale, alternatives, and next steps.

Leading recommendation

The best-fit treatment path for the current thread.

Backup options

Alternatives if efficacy, tolerability, access, or patient goals shift.

Rationale and branch conditions

The reasoning, tradeoffs, and facts most likely to shift the ranking.

Citations and next steps

Source support, a clean source trail, and suggested follow-up actions.

Evidence in context

Surface the evidence that actually changes the recommendation.

Clinical questions rarely hinge on one source. The assistant needs to surface the small set of facts, citations, and access constraints that actually change the answer.

Decisive sources first

Pull forward the note, lab, guideline, or payer rule that actually changes the recommendation.

Side-by-side comparison

Keep conflicting signals and access constraints visible instead of flattening them into a single summary.

Stay within shown context

Reason only over the materials attached to the thread and the public references used to support the answer.

Sources in view

De-identified notes and chart summaries

Labs, imaging summaries, and medication history

Guidelines, evidence reviews, and public references

Payer policies, denial letters, and coverage rules

What changed the ranking

A recent PCP note narrowed the current risk profile.

A1c trend and medication history favored GLP-1 escalation.

Payer policy changed the first-pass ranking between options.

Guideline support stayed attached to the final recommendation.

Agentic review

Expand or narrow the search until the thread has enough evidence to support the answer.

Review tables

Compare options, caveats, and source-backed findings without leaving the workspace.

Personalization and control

Tailored carefully. Governed explicitly.

Manoa can adapt to clinician preferences and specialty context, but the control model stays visible. The point is better judgment support, not hidden autonomy.

Tailored output

Depth, framing, and language can adapt to specialty, workflow, and preferred level of detail.

Clinician control

Recommendations stay cited and reviewable so the assistant supports judgment rather than replacing it.

Grounded thread state

The current case, source packet, and reasoning history stay visible while the answer evolves.

What Manoa does

Works through case questions and asks follow-ups until the thread is clinically usable.
Grounds recommendations in uploaded context and cited public evidence.
Returns ranked treatment paths with rationale, citations, and next steps clinicians can review or share.

What Manoa does not do

Replace clinician judgment or make the final treatment decision.
Submit prior authorizations, place orders, or take action automatically.
Claim access to unseen systems or guarantee coverage, payment, or outcomes.
Promise autonomous research beyond the sources and context shown in the thread.

See the assistant in a real treatment-planning workflow.

Walk through a live thread, the follow-up questions it asks, and the ranked recommendations it returns with citations.

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