ChasiWinter 2026Active☆Watch⊞Compare

Chasi 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 Revenue Engine for the Equipment Industry

Chasi deploys AI agents that help equipment dealers sell more, respond faster, and maximize fleet utilization - 24/7. One-third of the cost to build and maintain the physical world goes to equipment, yet fleet utilization across the industry often sits below 60%. Billions in assets sit idle while dealers drown in phone calls, emails, and manual data entry. Missed quotes, slow follow-ups, and disconnected systems mean lost revenue every day. Chasi plugs into a dealer's existing stack to deploy AI agents that handle sales, rentals, and service requests around the clock. The result: faster response times, higher utilization, and stronger margins, without adding headcount. We automate the busywork so teams can focus on what actually grows the business: customer relationships. Akash Pavan and Sarman Aulakh have built tractors, race cars, and robots, and previously led AI deployments at Tesla, Boeing, and Cummins, where they saw firsthand how much operational value gets left on the table in equipment-heavy industries. Chasi is live across equipment businesses in the US and Europe.

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.

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.

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

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