Care gap outreach that closes gaps without more staff hours.
Prioritize open care gaps, personalize compliant outreach, book eligible services, and route clinical barriers to care teams.
Nothing is finalized until a human approves it.
Where the time and money actually go.
Static call lists create low contact rates, generic messages, duplicate outreach, and weak visibility into why patients do not complete preventive or chronic-care actions.
Care coordinators, outreach teams, primary-care practices, members/patients
Trigger to act: Quality targets are off track, outreach capacity is constrained, or an ACO/payer needs a repeatable campaign engine with evidence and consent controls.
The result you can model before you sign.
Illustrative only: 5,000 eligible patients × 2 percentage-point incremental closure × $120 internal value per completed action = $12,000 program value. The buyer must define the defensible value per closure.
The outcome, plainly: Prioritize open care gaps, personalize compliant outreach, book eligible services, and route clinical barriers to care teams.
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.
- Attributed population
- open gap
- eligibility and exclusion rules
- contact preference
- language
- appointment supply
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 advice, ambiguous exclusions, vulnerable-patient situations, and repeated nonresponse follow client-approved escalation and human review protocols.
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 Population health platform 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 advice, ambiguous exclusions, vulnerable-patient situations, and repeated nonresponse follow client-approved escalation and human review protocols. The system drafts and recommends; a human approves every consequential action. Explicitly excluded: No coercive outreach; no clinical recommendation beyond approved content; no contacting patients without consent/legal basis; no guarantee of quality bonus attainment..
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 $400–3,100/month (10,000–35,000 workflow runs/month with modest document and model usage), plus a $2,600/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 Innovaccer?
Tools like Innovaccer, Arcadia, Health Catalyst 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 validate next. We baseline “Gap closure rate” 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