Companies · AI / ML
San Francisco · CA, USA · AI / ML · founded 2025 · https://autosana.ai
Diligence memoA one-page analyst read on Autosana — recommendation, valuation, rhythm, risks.→Autosana: limited disclosed financing to assess.
Synthesized from the figures below est. — every claim rests on a number shown on this page.
Autosana is one of 2067 AI / ML companies tracked from San Francisco, CA, USA, on record since 2025. By capital raised it ranks mid-pack (ahead of 62% 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 agents for E2E testing across mobile & web
Autosana is the end-to-end testing layer for your coding agents, across iOS, Android, and Web apps. Step away from your laptop. Come back to full-stack features built and tested end-to-end, production ready. Autosana creates, updates, and runs tests automatically from your code diffs. Locally, it loops with your coding agent until every test passes. In PRs, it loops with cloud agents and shows video proof of your new feature or bug fix working end-to-end. No setup, no maintenance, just tests evolving with your codebase. Ship with confidence.
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 2067 companies in AI / ML. 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 62% of sector peers (real $). Modeled value above 62% 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.
| Stage | Amount · real | Announced | Post-money · est | Value · est | Conf. |
|---|---|---|---|---|---|
| No rounds recorded. | |||||
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.
Autosana 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.
| Company | Sector | Stage | Raised · real | Value · est | Why similar |
|---|---|---|---|---|---|
| a0.dev | AI / ML | — | — | — | same sector |
| Accord | AI / ML | — | — | — | same sector |
| Acely | AI / ML | — | — | — | same sector |
| Adam | AI / ML | — | — | — | same sector |
| Aedilic | AI / ML | — | — | — | same sector |
| Affogato AI | AI / ML | — | — | — | same sector |
| Aftercare | AI / ML | — | — | — | same sector |
| Afternoon.co | AI / ML | — | — | — | same sector |
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.
| Company | Sector | Stage | Value · est | Match |
|---|---|---|---|---|
| Persana AI Sales Agents with 100+ data sources to close more deals | AI / ML | — | — | 81% |
| TesterArmy Test your app with AI, catch bugs before users do | AI / ML | — | — | 77% |
| Narrative AI agents for end-to-end testing | AI / ML | — | — | 77% |
| Decipher AI QA agents that write tests 10x faster with zero maintenance | AI / ML | — | — | 76% |
| Lark The E2E testing layer for AI-driven development | AI / ML | — | — | 76% |
| Proxis The platform for enterprise AI agent automations, starting with email. | AI / ML | — | — | 76% |
| Tasklet Agents that own the work | AI / ML | — | — | 75% |
| Amika Infra to build your own software factory | AI / ML | — | — | 75% |
See where Autosana sits in the wider market — its sector, location and stage cohorts, each with their own leaderboards and capital-flow timelines.
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