Our World in DataWinter 2019Active☆Watch⊞Compare

Our World in Data is one of 207 Climate / Cleantech companies tracked from Oxford, England, United Kingdom; Remote, on record since 2018. By capital raised it ranks mid-pack (ahead of 41% 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”

Research and data to make progress against the world’s largest…

Poverty, disease, hunger, climate change, war, existential risks, and inequality: The world faces many great and terrifying problems. It is these large problems that our work at Our World in Data focuses on. Our World in Data publishes an open-access publication where users can understand the state of the world today, where we are making progress and where we are falling behind. Through interactive data visualizations we can see how the world has changed; by summarizing the scientific literature we can understand why. We cover everything from global poverty to natural disasters, education and health; we have 3405 charts across 297 topics. Our World in Data is free, open-source and provided as a public good. It has millions of users every month, and is cited in research and media across the world every day. This allows millions of people to understand the large problems the world is facing, and how we can solve them.

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 207 companies in Climate / Cleantech. 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 41% of sector peers (real $). Modeled value above 41% 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.

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

If you work at Our World in Data, claim this profile or suggest a correction. We aggregate from public filings, so help us keep your description, website and links accurate.