Companies · Insurance
San Francisco · CA, USA · Insurance · founded 2025 · https://imagineai.me
Diligence memoA one-page analyst read on Imagine AI — recommendation, valuation, rhythm, risks.→Imagine AI: limited disclosed financing to assess.
Synthesized from the figures below est. — every claim rests on a number shown on this page.
Imagine AI is one of 146 Insurance companies tracked from San Francisco, CA, USA, on record since 2025. By capital raised it ranks mid-pack (ahead of 68% 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”
We reverse engineer B2B growth, starting with LinkedIn.
Imagine AI is a research and software company reverse engineering modern B2B growth, starting with LinkedIn. We build coordinated content systems for executive teams, where the CEO, VP of Sales, and Head of Marketing post aligned narratives from a single calendar, producing compounding reach that single-founder posting cannot reach. 50+ B2B companies are now using Imagine AI, including MongoDB, Rippling, Slash, and Corgi Insurance. Customers have generated $31M in attributed revenue, 12M impressions, and 1,400 hours of executive time saved.
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 146 companies in Insurance. 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 68% of sector peers (real $). Modeled value above 68% 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.
Imagine 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.
| Company | Sector | Stage | Raised · real | Value · est | Why similar |
|---|---|---|---|---|---|
| Acadia Fire Insurance Company | Insurance | — | — | — | same sector |
| Acolite | Insurance | — | — | — | same sector |
| Adaptional | Insurance | — | — | — | same sector |
| Aegis | Insurance | — | — | — | same sector |
| AI Insurance | Insurance | — | — | — | same sector |
| Air Centurion Insurance Services, Inc. | Insurance | Pre-Seed | $600K | $13.9M | same sector |
| Albiware Inc. | Insurance | — | — | — | same sector |
| Altrina | Insurance | — | — | — | 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 |
|---|---|---|---|---|
| Letter AI Empowering B2B sellers with AI-powered training, coaching, and content | AI / ML | — | — | 80% |
| Sprites The AI performance marketing agent for entrepreneurs and growth teams | AI / ML | — | — | 78% |
| Penguin AI AI Sales Rep for Website Intent Signals | AI / ML | — | — | 78% |
| Namecard.ai AI-powered business matchmaking | AI / ML | — | — | 77% |
| Foaster The AI-native McKinsey | AI / ML | — | — | 77% |
| Redapto Enterprise AI Transformation Platform | AI / ML | — | — | 77% |
| Mindbase Build AI influencers that autonomously create content, engage fans… | Gaming | — | — | 77% |
| Kestral We automate your entire product development lifecycle. | AI / ML | — | — | 77% |
See where Imagine 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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