HypermileSummer 2020Acquired☆Watch⊞Compare

Hypermile is one of 207 Climate / Cleantech companies tracked from London, England, United Kingdom, on record since 2021. 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”

Driver co-pilot to make trucking more efficient

Hypermile is on a mission to improve trucking efficiency, sustainability and safety by developing an AI driver assistance system 🚛 🌎🌱. Today, fuel is the main cost component for logistics operators, accounting for >1/3 of all operating costs. Driving behavior is a key factor affecting overall fuel consumption and can increase fuel use by up to 35%. However, current solutions are not cost effective, so logistics operators are constantly looking for new solutions. In addition, logistics operators are under huge sustainability pressure, as Heavy Goods Vehicles (HGVs) are responsible for 16% of the UK's transport emissions but only 5% of the miles travelled. While electric vehicle sales for passenger vehicles are on the rise, the same can't be said for long-haul HGVs due to high initial cost and limited range, making it impractical for logistic purposes. With this problem in mind, we aim to leverage the latest AI techniques to improve the fuel efficiency of diesel trucks today, and increase the range of zero-emission trucks of the future. Our product Hypermile Co-Pilot is a retrofittable AI cruise control for commercial vehicles focused on controlling the speed of the truck efficiently. We have trained the AI algorithms to learn the best techniques for saving fuel: anticipating how traffic flow will change, optimising speed based on the road gradient and maximizing vehicle coasting. As a result, we can reduce diesel consumption by 11% and extend the range of battery-electric vehicles by 15%. The long term vision is to incrementally build higher levels of autonomy with the next milestone being a Level-3 autonomous trucking solution. The company was founded in May 2020 and raised a $1.5M pre-seed round in May 2021 from Y Combinator, Greg Brockman (CTO of OpenAI), Luc Vincent (former Executive VP of Autonomous Driving at Lyft Level 5) and others. We’ve received a number of R&D grants from Innovate UK, Department for Transport and Horizons 2020. We’re currently a team of 10 across Commercial, Product and Engineering (including 4. sub-teams cloud software, machine learning, automotive software and electronics).

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.

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

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