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Unlimited Free HIPAA-Compliant E-Signing

Hacker News

Unlimited Free HIPAA-Compliant E-Signing

Hi HN, I’m Stanley, founder of RabbitSign, an unlimited free e-signing service. (Not just a free trial or a free tier—completely free.) Created in response to the surging demand for e-signing during COVID, it puts social good ahead of profits. Since its initial launch in 2021, purely through word of mouth, RabbitSign has attracted * small business and nonprofits * unicorn startups * Fortune 500 companies * federal government agencies RabbitSign is now proud to offer HIPAA-compliant e-signing for free. HIPAA is a US federal law that created standards for safeguarding patients' protected health information (PHI). Healthcare providers and anyone handling PHI must use HIPAA-compliant e-signing, which normally costs thousands of dollars a year. By offering it for free, RabbitSign aims to help lower American healthcare costs. This mission caught the attention of Viewpoint with Dennis Quaid, a documentary series on innovations whose past guests include President George H.W. Bush, Secretary Colin Powell, and Fortune 500 CEOs. They will feature RabbitSign in Summer 2023 on public television, CNN, CNBC, and Bloomberg. On the technical/business side, RabbitSign is sustainable as a free service because it leverages AWS Serverless technology. It costs less than $1 to process 1000 document signings. Last month, it finished an AWS Well-Architected Review, which concluded that RabbitSign is a “remarkably well-architected workload” and “one of the most efficient and secure accounts” reviewed. AWS will soon publish a case study featuring RabbitSign for its efficient usage of Serverless and compliance related services. RabbitSign also recently passed a multi-week whitebox pentest. Beyond HIPAA, RabbitSign has partnered with Drata for compliance with the SOC 2, ISO 27001, GDPR, and CCPA frameworks. It’s also actively working on providing 21 CFR Part 11 compliance (for medical/drug researchers) and FedRAMP (to save taxpayer dollars). On the philosophical side, RabbitSign is an Activism Corporation, a new kind of company inspired by the Tit-for-tat strategy in Prisoner’s Dilemma ( https://docs.google.com/document/d/1ZlBhH9h6zPVSl8JT-xZKvj5s... ). It aims to use free market forces to combat corporate greed. For the definition of Activism Corporation, please check out the FAQ ( https://docs.google.com/document/d/1fAwZtNfQxsBgrs-8AsTTtrmw... ). Would love to hear any feedback or thoughts on RabbitSign! You can reach me at stanley@rabbitsign.com.

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: ide, 000, io · Missing: https docs, excited, just released
55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: month, google · Missing: mobile apps, ios, personal
39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: google, new · Missing: mac, agents, macos
36%36% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: soon, efficient · Missing: plus, platform, intuitive
35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: profit, active · Missing: arr, mrr, revenue
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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