Ångström AISummer 2024Active☆Watch⊞Compare

Ångström AI is one of 233 Biotech companies tracked from San Francisco, CA, USA, on record since 2024. By capital raised it ranks mid-pack (ahead of 67% of sector peers), and mid-pack 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”

Gen AI molecular simulations that reproduce wetlab results

Angstrom AI builds GenAI-based molecular simulations to substitute wet lab experiments in the pre-clinical drug development pipeline. We are a team of 2 PhD's and 2 Professors from the University of Cambridge who decided to start a company together after we realised how to combine breakthoughs in our research in quantum-accurate models of physics and generative AI models. Our Biotech/Pharma clients can verify the efficacy and safety of new drug candidates using our computer simulations, which match the accuracy of wet lab experiments, but are over 100x faster. We achieve this accuracy by constraining our genAI-based simulations to obey the laws of physics, avoiding the hallucinations seen in other GenAI technologies. Since joining YC, Angstrom AI has developed the first physically accurate gen-AI based simulation of multiple molecules interacting. We have published the first molecule water solubility results with accuracy within the error range of wet lab experiments. We have also kicked-off a 150K pilot project with a pharma company to apply our tech to estimating solubility in their drug development pipeline.

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 233 companies in Biotech. 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 67% of sector peers (real $). Modeled value above 67% 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.

Ångström 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 Ångström 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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