Redouble AISummer 2024Active☆Watch⊞Compare

Redouble AI is one of 310 Pharma companies tracked from New York, NY, USA; Remote, on record since 2024. By capital raised it ranks in the long tail (ahead of 16% 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”

Java-native multi-agentic AI operating system for enterprise

At Redouble AI we have developed Silverlake, a Java-native agentic AI operating system for enterprise. While other AI solutions force enterprise stakeholders to embrace unfamiliar concepts in an unfamiliar language, we do the opposite: we slot agentic AI right into the enterprise comfort zone - by mapping all agentic concepts onto established enterprise primitives in their own language, their own security model, their own infrastructure. It’s like moving from Bitcoin to Stablecoin, just for agentic AI. When we did YC we realized there was no framework or platform that gave us as enterprise and workflow automation veterans what we needed to build truly secure, reliable, and scalable agentic solutions for mission-critical workflows. That’s why we spent the past 18 months building Silverlake from the ground up. We empower the 12 million Java engineers worldwide to write and deploy their own AI, securely, at scale. They define an agent in a few lines of code, and our platform does everything else, from orchestration to permission control, from auditability to rate limiting, from long-running agents to autonomous coordinated networks that perform the work of entire departments. Silverlake has been developed with design partners across biopharma, insurance and financial services. For example, our agentic workflows write submission-ready Clinical Study Reports that are hundreds of pages long, analyze entire datarooms full of financial and operational data for private equity investors, and automate claims processing for a large insurance player. We are backed by Y Combinator, Exponential, Transpose Platform, Tiny VC, and the Oxford Seed Fund and advised by Java inventor James Gosling and automation guru Professor Christian Terwiesch.

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 310 companies in Pharma. 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 16% of sector peers (real $). Modeled value above 16% 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.

Redouble AI 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 Redouble AI sits in the wider market — its sector, location and stage cohorts, each with their own leaderboards and capital-flow timelines.

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