AI-powered decision support for complex care

From standard-of-care to parallel-of-care.

ParallelCare helps patients, families, and clinicians evaluate multiple evidence-backed treatment strategies in parallel — so critical decisions are made with more context, more speed, and more clarity.

Built for complex disease journeys Structured patient state + evidence graph Decision support, not direct medical advice
Case workspace
Stage-specific profile built from reports, pathology, imaging, and history
Structured timeline Evidence-linked Trial-aware
3
parallel strategies evaluated
Path A

Standard intensification

Guideline-consistent next step with timing, sequencing, and monitoring checkpoints clearly mapped.

Evidence strength High
Path B

Trial / biomarker route

Targeted trial discovery and match logic based on patient state, prior exposure, and molecular context.

Fit score 0.82
Path C

Bridging strategy

Interim option designed to preserve time, maintain control, and keep future options open.

Risk profile Balanced

Complex diseases do not move in a straight line. Care planning should not either.

In high-stakes situations, one-path-at-a-time decision making can be too slow and too opaque. ParallelCare is built for moments when patients and clinicians need to compare multiple viable strategies, understand the tradeoffs, and adapt as new evidence arrives.

01

Linear workflows break down

Real patient journeys involve changing disease state, incomplete information, treatment history, timing pressure, and uncertainty around what to do next.

02

Evidence is fragmented

Guidelines, papers, trials, reports, and patient records rarely sit in one coherent decision space. The burden falls on humans to connect them under stress.

03

Decisions need structure

What matters is not just retrieval. It is building a usable patient state, surfacing competing options, and making reasoning transparent enough to trust.

An evidence-driven workflow for evaluating multiple paths in parallel.

ParallelCare turns messy records into structured context, links that context to evidence, and generates a ranked set of strategy options with explicit reasoning.

Patient state builder

Ingest pathology, imaging reports, timelines, medication history, biomarkers, staging, and prior interventions into a structured case profile.

Evidence graph

Map guidelines, studies, trial criteria, and clinical logic to the specific state of the patient rather than generic disease labels alone.

Parallel strategy engine

Generate standard, trial-based, bridging, and fallback options side by side with assumptions, dependencies, and likely next actions.

Transparent output

Show why an option appears, what evidence supports it, what risks it carries, and which patient factors would change the ranking.

A new decision layer for medicine.

ParallelCare is built around a simple idea: the hardest cases deserve more than a single threaded answer. The future of complex care will combine structured patient state, evidence-aware reasoning, and adaptive comparison across multiple paths — always with clinicians and patients in the loop.

For patients & families

Understand what the viable paths are, what the major tradeoffs look like, and what questions to bring into the next clinical conversation.

For clinicians

Compress the time needed to synthesize records, compare options, and identify when a case may benefit from broader multidisciplinary review.

For health systems

Create a reusable decision-support infrastructure that can scale across complex disease programs while preserving traceability and human oversight.

Interested in early access?

Join the early access program to explore how ParallelCare can support complex decision-making in real-world cases. We are onboarding a limited number of clinicians, researchers, and patients for the first release.

hello@parallelcare.ai