Swif.aiSummer 2020Active☆Watch⊞Compare

Swif.ai is one of 270 Cybersecurity companies tracked from Sunnyvale, CA, USA, on record since 2020. By capital raised it ranks in the long tail (ahead of 19% 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”

The guardrail for AI on every device

Swif.ai is a real-time device compliance and security platform that keeps every Mac, Windows, and Linux endpoint secure and audit-ready. Our lightweight agent enforces policies (encryption, patching, app controls) as people work, auto-remediates drift, and streams audit evidence to tools like Vanta and Drata. Unlike legacy MDM or “after-the-fact” compliance software, Swif.ai delivers enforcement—not just reports—plus device-level Shadow IT/AI governance to detect and block risky or unauthorized SaaS and LLM tools. Enterprises choose Swif.ai for true multi-OS coverage in a single pane of glass, one-click remediation, and fast time-to-value via silent installers and native integrations with Okta, Microsoft Entra ID, and Google Workspace (conditional access by device posture). The result is fewer tools to manage, shorter audits, and stronger security with lower operational burden. Swif.ai is SOC 2 Type II. Our near-term roadmap adds Safe-AI controls for regulated industries, AI-agent monitoring, and integrated vulnerability detection with one-click fixes—expanding our lead as the enforcement layer for endpoint compliance and AI security.

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 270 companies in Cybersecurity. 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 19% of sector peers (real $). Modeled value above 19% 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.

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

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