Companies · Insurance
San Francisco · CA, USA · Insurance · founded 2025 · https://ressl.ai
Diligence memoA one-page analyst read on Ressl AI — recommendation, valuation, rhythm, risks.→Ressl AI: limited disclosed financing to assess.
Synthesized from the figures below est. — every claim rests on a number shown on this page.
Ressl 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”
AI Workers for Field Services
We automate the back office so field crews can focus on the actual work. Trades businesses (HVAC, plumbing, electrical, collision repair, roofing) run on legacy software and "glue" employees: people whose entire job is clicking through systems, copy-pasting between tools, and managing inbound volume across channels. A collision shop has one person generating estimates in CCCOne, another chasing parts vendors, another answering calls and Yelp messages, another doing invoices in QuickBooks. None of that requires a human. We build proactive background agents that run these operations autonomously -- quoting, estimating, procurement, insurance coordination, scheduling, follow-ups -- on top of the software these businesses already own. We started as an AI consulting firm talking to businesses across every industry. After a month, the pattern was obvious - trades and field services had the most "glue work" and the least tech sophistication to solve it themselves. Every shop we walked into had 2–4 people doing work that software should be delivering as an outcome, not just enabling. Our GTM is direct to operators and through PE-backed roll-ups, who are actively looking for margin improvements across their portfolio companies. If this is of interest, please reach out arushi@ressl.ai
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.
Ressl 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 |
|---|---|---|---|---|
| SpadeWorks AI agents that turn every call into revenue for trade businesses | AI / ML | — | — | 79% |
| Juro System Inc Intelligent contracting is here. Juro empowers your team to agree and manage contracts end-to-end with flexible AI automation that lives where you live. | Business Services | Growth/Late | $574.3M | 79% |
| NOSO LABS Build AI agents for field technicians to diagnose and sell 10x better | AI / ML | — | — | 79% |
| Seals AI AI Employees for Wholesalers & Distributors | Fintech | — | — | 79% |
| throxy Vertical AI agents that run the sales funnel on autopilot | Fintech | — | — | 78% |
| Strada AI agents that run insurance operations | Insurance | — | — | 78% |
| Tradespark AI Inc. | AI / ML | Pre-Seed | $397K | 78% |
| FleetWorks AI enabled marketplace matching trucks with jobs | AI / ML | — | — | 78% |
See where Ressl 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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