From whiteboard to working prototype in weeks, not quarters.
Newton3 pairs Lovable's full-stack AI app platform with Anthropic's Claude for Healthcare to build, test, and validate clinician-ready AI workflows — before you commit to a multi-year build or procurement.
Prototype the workflow, not just the model.
Most healthcare AI projects stall in the gap between a model demo and a workflow clinicians will actually use. We close that gap by building working prototypes — real UI, real data flows, real eval harnesses — that a clinician can click through, react to, and reshape in days. The question stops being "is the model good?" and becomes "is this workflow worth scaling?"
The stack.
A modern, opinionated toolchain assembled for clinical speed and safety.
Lovable
Full-stack AI app generation with built-in auth, database, storage, and edge functions — production-grade scaffolding that turns a workflow sketch into a working pilot in days, not a quarter.
Anthropic Claude
Claude Sonnet and Opus bring long-context reasoning over clinical documents, tool use for chart and order systems, and Anthropic's constitutional safety posture — a strong default for high-stakes healthcare reasoning.
Claude for Healthcare
Anthropic's healthcare-aligned offering — announced alongside Claude for Life Sciences — is purpose-built for providers and payers, with integrations spanning EHRs, chart summarization, and patient record connectivity through partners like Elation Health and HealthEx.
Newton3 validation layer
Workflow mapping, clinician interviews, evaluation harnesses, bias and safety review, and HIPAA / FDA SaMD readiness — the discipline that turns a slick prototype into something a health system can actually adopt.
What we prototype.
Common starting points across providers, payers, and life sciences.
Intake & triage copilots
Symptom capture, risk stratification, and routing tools that reduce front-desk and nursing load while surfacing clinician-readable rationale.
Prior-auth & revenue cycle
Document-heavy workflows where Claude's long context shines — drafting, evidence assembly, and denial response with an auditable trail.
Clinical documentation
Ambient and post-encounter summarization, problem-list reconciliation, and structured note generation built around clinician edit patterns.
Knowledge & policy agents
Internal copilots for guidelines, formularies, and payer policy — grounded in your sources, with citations and refusal behavior tuned for clinical use.
How an engagement runs.
A typical 4–6 week sprint, structured for evidence — not theater.
Discover
One week. Workflow shadowing, risk and PHI mapping, success metrics, and a no-go list. We leave with a one-page brief any clinician can read.
Prototype
Two to three weeks. We build in Lovable, wired to Claude through the Anthropic API, with weekly clinician reviews and tight iteration loops on prompts, tools, and UI.
Validate
One to two weeks. Eval harness on representative cases, bias and safety review, and an adoption plan that hands off cleanly to internal IT, compliance, and clinical leadership.
Guardrails, by default.
Prototypes default to synthetic or de-identified data. PHI only enters the loop after a documented review with your privacy and security teams, and only inside environments your organization controls.
Every prototype ships with an evaluation harness — accuracy, refusal behavior, bias slices, and drift checks — wired into the Newton3 GRC playbook so handoff to compliance is not an afterthought.
A clinician is always in the loop. We design for assistance, not autonomy, and we document where the system should decline.
Start a conversation.
Strategy, governance, and infrastructure — built around people.