MisprintWinter 2025Active☆Watch⊞Compare

Misprint is one of 2067 AI / ML companies tracked from New York, NY, 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”

Misprint is building Robinhood for Pokemon cards

Misprint is an all-in-one marketplace that solves the biggest pain point in the collectibles world: opaque pricing. Collectors, investors, and hobbyists currently rely on scattered data from auction houses, online forums, and reseller platforms, making it difficult to know the true value of their items. Misprint streamlines the process by combining accurate pricing analytics with a seamless buy/sell marketplace, making it easier than ever to understand and monetize collectible assets. Existing marketplaces lack robust, real-time analytics because accurate valuations require deep expertise in both the collectibles domain and advanced pricing algorithms. Misprint’s unique blend of insider trading card knowledge and machine learning allows us to fill this gap. Building these pricing models requires extensive data infrastructure, deep domain expertise, and cutting-edge ML. Recent surges in the trading card market show that collectors crave transparent valuations. The global collectibles market is worth tens of billions of dollars. Eva has experienced the scale of this industry firsthand, generating $500k ARR within three months of taking her Pokemon card-selling side hustle full-time. With additional segments like sports cards, comics, and emerging collectible categories, the growth runway is immense. Co-founders Eva and Jon have been best friends since Exeter, combining finance expertise, a passion for collectibles, and mathematical rigor. By merging Goldman Sachs-level financial analytics with top-tier mathematical talent, Misprint is uniquely positioned to become the go-to platform for fair, transparent pricing in the collectibles space.

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.

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

If you work at Misprint, claim this profile or suggest a correction. We aggregate from public filings, so help us keep your description, website and links accurate.