Discover the full insider trade history of Amesite Inc., a listed equity based in United States. Shares are quoted on US US, under the supervision of SEC (Form 4). Operating in the Technology sector, Amesite Inc. has recorded 30 insider filings. Market capitalisation: €5.3m. The latest transaction was disclosed on 28 December 2021 — Acquisition. Among the most active insiders: Tompkins Mark N.. Every trade is openly available.
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Amesite Inc. is a U.S.-listed technology company on the NASDAQ (United States) focused on AI-driven applications for education, workforce learning, and, increasingly, healthcare. The company was founded in November 2017 and is headquartered in Detroit, Michigan. Over time, Amesite has evolved from a broader cloud-based learning platform provider into a more vertically focused software company with a clear emphasis on practical AI tools for clinical and care-delivery workflows. Its U.S. headquarters and public-company disclosures indicate that the business is still primarily domestically operated, even as it begins to show a small international footprint. ([ir.amesite.com](https://ir.amesite.com/sec-filings/annual-reports)) The company’s flagship offering is NurseMagic, a mobile app and software suite designed for nurses, caregivers, and other healthcare professionals. According to Amesite, NurseMagic streamlines nursing documentation, generates notes, supports patient communication, and helps with professional guidance and workflow efficiency. The company says the app is used across more than 100 professions and positions it as a tool that can materially reduce the time required for documentation while improving care quality and operational performance. This is the core of Amesite’s current growth narrative and its main route to monetization through subscriptions and enterprise-oriented offerings. ([ir.amesite.com](https://ir.amesite.com/company-information)) From a competitive standpoint, Amesite operates in a crowded and fast-moving market that includes healthcare software vendors, clinical automation providers, and AI productivity platforms. Its competitive edge is not scale, but specialization: it is targeting a specific, repetitive, high-value task set in nursing and post-acute care. The company also appears to be pursuing a hybrid go-to-market strategy, serving both B2C users and B2B enterprise customers, which gives it flexibility but also requires disciplined execution. For investors, the key question is whether Amesite can convert product traction into durable recurring revenue. ([ir.amesite.com](https://ir.amesite.com/company-information)) Historically, Amesite built and marketed AI-enabled learning software for business, university, and K-12 customers before expanding more aggressively into healthcare. Recent company disclosures and press releases show a series of milestones: public launch of NurseMagic in 2024, rollout on major app stores, HIPAA-related positioning for enterprise use, and later language expansion and enterprise contract wins in 2025. That progression suggests a company still in commercialization mode, trying to establish product-market fit and scale its customer base. ([sec.gov](https://www.sec.gov/Archives/edgar/data/1807166/000121390024112017/ea022584201ex99-1_amesite.htm?utm_source=openai)) Geographically, Amesite remains centered in the United States, but the company has reported users across all 50 states and multiple countries, which gives it an early-stage international dimension. For francophone investors, Amesite should be viewed as a small-cap AI software story with a healthcare angle, rather than a diversified software platform. Recent SEC filings and capital-markets activity also indicate an active financing backdrop, reinforcing the view that the company is still building its operating base and funding its growth initiatives. ([globenewswire.com](https://www.globenewswire.com/news-release/2024/07/29/2920199/0/en/Amesite-Announces-Dramatic-Increase-in-NurseMagic-Users-Representing-All-50-States-and-6-Nations-Using-App-for-Wide-Variety-of-Applications.html?utm_source=openai))