Optery vs IBM
Side-by-side comparison of AI visibility scores, market position, and capabilities
Personal data privacy service removing information from 500+ data brokers; PCMag Editors' Choice 2022-2025 competing with DeleteMe named as potential unicorn by Business Insider.
About
Optery is a personal data privacy service that automatically removes users' personal information from data brokers — the companies that aggregate and sell personal data including home addresses, phone numbers, email addresses, financial information, and relatives' data. Founded in 2020 in San Francisco, Optery raised $6 million from investors and has won PCMag's Editors' Choice award for data privacy services from 2022 through 2025, earned multiple Cybersecurity Excellence Awards, and was named by Business Insider as one of 30 startups most likely to become a unicorn in 2025.\n\nOptery's service works by identifying which data brokers are selling each user's personal information, then submitting opt-out requests to remove those records under applicable privacy laws (California CCPA, Virginia VCDPA, and voluntary broker opt-outs in other states). Because data brokers constantly re-scrape and re-list data, the removal process is ongoing rather than one-time — Optery continuously monitors for re-listed records and re-submits removal requests. Users get a dashboard showing which sites had their data, which have been removed, and which are pending.\n\nIn 2025, Optery competes in the personal data privacy and deletion market with Privacy Bee, DeleteMe, and Abine (Blur) for data broker opt-out services. The category has grown as consumers have become more aware that their personal information is sold commercially, and as concerns about doxxing, stalking, and identity theft have increased. State privacy laws have expanded data subject rights, giving services like Optery legitimate legal levers for removal requests. Business Insider's unicorn prediction reflects the large addressable market (most internet-connected adults in the US have data broker exposure) and Optery's PCMag award wins validating product quality. The 2025 strategy focuses on growing consumer subscriptions, building enterprise offerings (companies protecting executives' personal data), and expanding international coverage as GDPR and other privacy laws expand broker opt-out rights.
Armonk NY hybrid cloud and enterprise AI (NYSE: IBM) at $62.8B revenue; $6B+ generative AI bookings, record $12.7B free cash flow 2024, DataStax acquisition for watsonx vector database competing with Microsoft Azure for enterprise AI.
About
International Business Machines Corporation (IBM) is an Armonk, New York-based global technology and consulting company — publicly traded on the New York Stock Exchange (NYSE: IBM) as an S&P 500 component — providing hybrid cloud infrastructure, artificial intelligence software, and enterprise IT consulting through approximately 270,300 employees in 170 countries with $62.8 billion in annual revenue. Founded on June 16, 1911, as Computing-Tabulating-Recording Company through a merger orchestrated by financier Charles Ranlett Flint, renamed IBM in 1924 under Thomas Watson Sr., IBM has undergone multiple strategic transformations over its 110+ year history: building the System/360 mainframe platform (1964), launching the IBM PC (1981), selling the PC division to Lenovo (2005, $1.75B), and completing the $34 billion Red Hat acquisition (2019) that repositioned IBM as a hybrid cloud platform company. CEO Arvind Krishna (appointed April 2020) has focused IBM's strategy on three areas: hybrid cloud (powered by Red Hat OpenShift, the enterprise Kubernetes platform), AI (the watsonx platform for enterprise AI model development and deployment), and enterprise consulting. Under Krishna, IBM recorded $12.7 billion in free cash flow in 2024 (a company record), surpassed $6 billion in generative AI bookings since June 2023, and saw the stock price double — trading at all-time highs through 2024-2025. IBM announced the DataStax acquisition in 2025 to deepen watsonx's data layer with AstraDB (vector database for AI applications), DataStax Enterprise (Apache Cassandra), and Langflow (low-code AI agent development).
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