Ambient.aiWinter 2017Active☆Watch⊞Compare

Ambient.ai is one of 30 Public Safety & Security companies tracked from San Francisco, CA, USA; San Jose, CA, USA, on record since 2016. 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”

AI company transforming enterprise physical security to prevent…

Ambient.ai is a computer vision intelligence company transforming enterprise security operations to prevent security incidents before they happen. The Ambient.ai platform applies AI and computer vision intelligence to existing sensor and camera infrastructure to deliver continuous physical security monitoring and automate the immediate dispatch of human resources. Ambient.ai is the first platform that goes beyond basic motion detection and image recognition to achieve near-human perception with automated situational context. With physical security incidents on the rise and physical security organizations left under-resourced, Ambient.ai’s computer intelligence platform comes at a time of critical need, which is why the company has raised over $50 million from venture capital investors led by a16z. Today, large enterprises, schools and organizations – including many of the largest US tech companies and other Fortune 500 companies – use Ambient.ai to secure property, people, and assets from the most harrowing physical security threats. The company was founded in 2017 by experts in artificial intelligence from Stanford who previously built iconic products at Apple, Google, Microsoft and Dropbox. We are backed by Andreessen Horowitz (a16z), SV Angel, Y Combinator, and visionary angels like Jyoti Bansal, Mark Leslie and Elad Gil.

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 30 companies in Public Safety & Security. 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.

Ambient.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 Ambient.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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