Companies · AI / ML
San Francisco · CA, USA · AI / ML · founded 2025 · https://outship.ai
Diligence memoA one-page analyst read on Outship — recommendation, valuation, rhythm, risks.→Outship: limited disclosed financing to assess.
Synthesized from the figures below est. — every claim rests on a number shown on this page.
Outship 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”
Hire amazing engineers by seeing how they use AI
Software engineering is being rewritten in real time, and hiring is getting pulled along for the ride. With tools like Claude Code and Cursor, being able to ship is the new baseline. The signal for finding extraordinary engineers is the process: how candidates break down work, steer the agent, make tradeoffs, and recover when things break. Outship is a recruiting tool that allows you to capture and analyze that process alongside the final code so you can hire with confidence. Candidates work in a cloud workspace that's ready to code. We handle the environment setup and secret management to give you a level testing ground.
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.
Outship 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 |
|---|---|---|---|---|---|
| Accord | AI / ML | — | — | — | same sector |
| Acely | AI / ML | — | — | — | same sector |
| Aemon | AI / ML | — | — | — | same sector |
| Affogato AI | AI / ML | — | — | — | same sector |
| Agentic Labs | AI / ML | — | — | — | same sector |
| Ai Aiba | AI / ML | — | — | — | same sector |
| Ai-Ais Hot Springs | AI / ML | — | — | — | same sector |
| AIOS | 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 |
|---|---|---|---|---|
| Standout Agentic hiring marketplace | AI / ML | — | — | 78% |
| Outrove Ultra-realistic AI Recruiter | AI / ML | — | — | 78% |
| Topo AI Agents for outbound working by your side | AI / ML | — | — | 77% |
| Hirebolt AI engineering capacity. Made simple. ⚡️ | AI / ML | — | — | 77% |
| Canary The first AI QA engineer that understands your code | AI / ML | — | — | 76% |
| Arcimus A stream of engineering candidates who ship. | — | — | — | 76% |
| OutRival, Inc. Outbound AI Agents for Education, Insurance, and Travel | Insurance | — | — | 76% |
| Weekday AI recruiter that runs outbound sourcing campaigns to find top talent | AI / ML | — | — | 76% |
See where Outship sits in the wider market — its sector, location and stage cohorts, each with their own leaderboards and capital-flow timelines.
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