Discharge coordination that cuts delays without the chase.
Coordinate discharge tasks, surface blocked dependencies, and keep patients and downstream providers informed through an auditable work queue.
Nothing is finalized until a human approves it.
Where the time and money actually go.
Discharge depends on many teams, orders, authorizations, transport, medication, equipment, and post-acute placement; status is fragmented and delays are discovered late.
Case managers, social workers, nurses, pharmacy and post-acute coordinators
Trigger to act: Length of stay is above target, case managers spend time chasing status, or readmission/transition failures expose coordination gaps.
The result you can model before you sign.
Illustrative only: 300 discharges/month × 20 coordination minutes removed × $42 loaded hourly cost ÷ 60 = $4,200 monthly capacity. Bed-day value must be validated separately and conservatively.
The outcome, plainly: Coordinate discharge tasks, surface blocked dependencies, and keep patients and downstream providers informed through an auditable work queue.
Inputs in. A cited, review-ready result out. Your expert decides.
A Tool-using workflow agent. Every material fact is grounded in an allowed source and returned with its identifier, no invented data.
Claude Sonnet 4.6 or GPT-5.6 Terra for complex grounded work; select by task-level evaluation; Gemini 2.5 Flash, GPT-5.4 mini or Claude Haiku 4.5 for high-volume routing and drafting. PostgreSQL + pgvector or managed vector store; Policy rules and evaluator service.
- Expected discharge date
- Task list
- Orders
- Authorization status
- Placement responses
- Medication reconciliation status
AI-Native, not autonomous. Judgment stays with your people.
The machine does the work; the human’s role narrows to the one thing that matters, judgment. That constraint is what makes it safe to deploy.
Clinical readiness, destination appropriateness, medication decisions, and discharge authorization remain with licensed staff; patient instructions require approved content.
A scorecard, not a demo. We baseline what breaks in production.
Every deployment ships with an evaluation suite. These are the numbers we baseline before launch and monitor after.
The category is crowded. Most of it isn’t built for your workflow.
Fixed-scope, tuned to your systems and rules, grounded in your data, with the human gate and audit trail built in from day one. A price you own, not a subscription you rent.
It plugs into the stack you already run.
No rip-and-replace. Access is scoped to the minimum data necessary, isolated per tenant, and fully logged.
Transparent by design. The build price buys the workflow and the proof.
A fixed implementation fee plus a monthly bill that scales with volume and governance. No hidden seats.
- ✓ One process / scope
- ✓ Live workflow on your data
- ✓ Baseline evaluation suite
- ✓ Measured vs. current process
- ✓ Full scope & integration
- ✓ Human-review UI & audit trail
- ✓ Write-back to your systems
- ✓ Production evals & monitoring
- ✓ Multi-facility rollout
- ✓ Advanced security & compliance
- ✓ Custom control & escalation
- ✓ Dedicated evaluation program
10,000–35,000 workflow runs/month with modest document and model usage.
Planning assumptions, not vendor quotations. Your EHR discharge plan and other platform licenses are separate and owned by you. Figures confirmed during scoping.
“His vast knowledge of technologies and a natural problem-solving mindset consistently lead us through complex challenges with clarity and confidence.”
Questions serious buyers ask.
Does the AI act on its own?
No. Clinical readiness, destination appropriateness, medication decisions, and discharge authorization remain with licensed staff; patient instructions require approved content. The system drafts and recommends; a human approves every consequential action. Explicitly excluded: No autonomous discharge order; no clinical readiness decision; no vendor selection outside approved network/rules; no substitution for informed patient discussion..
How do you stop it inventing facts?
Every material claim is grounded in an allowed source record and returned with its source identifier. The system separates observed facts, model inference, and missing information, and routes to a human whenever confidence is low, evidence conflicts, or an adverse outcome is possible.
What does it cost to run each month?
A usage bill of roughly $450–3,400/month (10,000–35,000 workflow runs/month with modest document and model usage), plus a $2,800/month managed retainer for evaluation, monitoring and maintenance. Your existing platform licenses are separate and already yours. Exact figures are confirmed during scoping.
Do we need a ChatGPT or Claude subscription?
No consumer ChatGPT or Claude subscription is required for the production workflow. The client needs an approved API/cloud billing account. Workspace seats are optional for internal prototyping and administrator access.
How is this different from Qventus?
Tools like Qventus, Aidin, WellSky are broad platforms you adapt to. This is a fixed-scope implementation tuned to your systems and rules, grounded in your data, with the human gate and audit trail built in, and a transparent price instead of a seat subscription.
How long until it’s live, and how do we prove it works?
This is a specialist opportunity. We baseline “Discharge-before-noon or local equivalent” first, then measure against that baseline. You see the scorecard before expanding scope, the evaluation suite ships with the system, not as an afterthought.
Bring your real numbers. Leave with a fixed-scope plan.
A 30-minute engineering-led working session, no slideware. You leave with a sized opportunity estimate, a fixed-scope pilot plan, and the integration & human-review path mapped.
VP of Growth at ViitorCloud · senior delivery owner confirmed before paid work