CyberdeskSummer 2025Active☆Watch⊞Compare

Cyberdesk is one of 2138 Healthtech companies tracked from San Francisco, CA, USA, on record since 2025. By capital raised it ranks in the long tail (ahead of 8% of sector peers), and in the long tail 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”

Self learning computer use agent for developers

Cyberdesk is the first self learning computer use agent for developers to automate desktop workflows. For example, one of our customers is building an AI agent for hospital patient intake, and they’re using us to automate an entire team of people manually clicking and typing into a desktop app to book appointments. We launched mid July, and our agent is already operating in production environments, creating appointments in electronic health record apps and processing files in legacy ERPs. We’ve built the first computer use agent that memorizes tasks and repeats them quickly while still adapting to unexpected changes on the screen. A good analogy is to how humans use computers: once we get used to an app, we use it much faster, while still adapting to random popups and crashes. This new paradigm for computer use will be needed by every company automating human workflows on computers. Mahmoud previously built robotic process automation solutions impacting 20K+ employees at a Fortune 100 company. He also built AI & ML solutions at Baylor College of Medicine Neuroscience & Texas Children's Hospital + co-published a paper at the Rice Networks Group. Alan is ex-NASA and previously dropped out to be the first founding engineer at a PearX startup. He is a second time founder, having previously built and scaled a consumer AI app to thousands of paying users. Computer-use agents will automate the $6T dollars spent on enterprise knowledge work and Cyberdesk will be the platform to power this. We’d love to talk with you! https://cal.com/mahmoud-al-madi-klrs5s/30min

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 2138 companies in Healthtech. 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 8% of sector peers (real $). Modeled value above 8% 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.

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

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