Ruma CareWinter 2026Active☆Watch⊞Compare

Ruma Care is one of 2138 Healthtech companies tracked from San Francisco, CA, USA, on record since 2026. By capital raised it ranks in the long tail (ahead of 8% of sector peers), and in the long tail by modeled valuation est..

Ranking is computed against this company's own sector cohort — reported capital is fact; valuation tiers are modeled.

AI analyst read est. — model-extracted from this company's public description, not a verified fact. 30%

operates a technology-led product inferred from public copy

Grounded in: “You are a venture analyst”

The operations stack for biologic infusion clinics

Ruma Care automates all admin work for infusion clinics - starting with prior authorizations & copay assistance enrollment. Biologics are expensive medications that cost $80-$150K+ per year per patient, and often need to be administered in specific settings called infusion clinics. Medical providers buy these drugs up front to secure pricing deals and safer inventory - they are reimbursed for the cost of the medications through the patients’ insurance. Current medical workflows aren't built for infusion clinics. Inventory, storage, transport, and billing is still managed through paper and excel spreadsheets. And because they’re so expensive, these specialty medications are denied by insurers at a rate of 37% each year. When they are denied, when workflows fail, or patients are infused before paperwork is cleared, providers don’t get reimbursed for the medication and are left covering the costs. Ruma Care solves this so clinics get paid, patients get treated faster, and care teams spend less time fighting forms. We do this in three ways: 1. For each medication, diagnosis, and insurance combination, Ruma extracts the submission criteria required to get the drug approved by insurers. 2. We pull out the correct forms, then automate the form-filling for prior authorizations. 3. Lastly, we enroll patients in copay assistance programs, all in one workflow and platform. We turn a process that traditionally spans 70+ online portals, disparate paper forms, and manual phone calling into a single, streamlined platform. As we process prior authorizations, our models learn from denial patterns to understand exactly what insurers need to see to get a prior authorization approved.

As reported in public records reported — not modeled.

Solid bars are reported offering amounts reported; hatched bars are the modeled post-money valuation est. — both on one shared scale so you can read raise-vs-worth at each round directly. Use the toggles to overlay data labels and the niche-peer / market average value lines.

No round amounts on record to chart.

No staged rounds to sequence.

Round size and date are reported; the stage label is inferred from round size. Valuation is modeled from stage benchmarks. Directional, not a quoted figure.

Not enough modeled valuation points to chart a trajectory.

Benchmarked against 2138 companies in Healthtech. Each bar is a median (the middle company, not an average — outliers don't skew it). Two yardsticks: real money raised (reported on Form D) and modeled value (our estimate est.). These are whole-sector medians across all stages, except the per-stage row.

Raised more than 8% of sector peers (real $). Modeled value above 8% of peers (estimate).

Stage is inferred from round size est., not reported on the filing — a round's dollar size maps to a bucket: Pre-Seed <$1.0M · Seed $1.0M–$4.0M · Series A $4.0M–$15M · Series B $15M–$40M · Series C $40M–$100M · Series D+ $100M–$400M · Growth/Late >$400M.

Predictive signals are modeled est. from this company's own cadence and step-up, plus sector benchmarks — directional, not advice. Peer set and a CSV export live in your analyst workspace.

Ruma Care is an official record sourced from the U.S. Securities and Exchange Commission (SEC). U.S. data is aggregated from SEC Form D filings.

Nearest neighbours across the whole database — matched on sector, stage and capital scale, and on shared operators (officers or directors named at both companies in public filings). A discovery shortlist, not a valuation cohort — verify before acting, the same way modeled figures are directional.

Matched by meaning, not labels — a local language model reads each company's name, sector and description and ranks the closest in that learned space. This catches look-alikes that cross sector boundaries; the structured list above explains its matches, this one trusts the text. Directional, like every modeled signal here.

See where Ruma Care sits in the wider market — its sector, location and stage cohorts, each with their own leaderboards and capital-flow timelines.

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