
Adaptive Security is OpenAI’s investment for AI cyber threats. The company was founded in 2024 by serial entrepreneurs Brian Long and Andrew Jones. Adaptive has raised $50M+ from investors like OpenAI, a16z and executives at Google Cloud, Fidelity, Plaid, Shopify, and other leading companies.
Adaptive protects customers from AI-powered cyber threats like deepfakes, vishing, smishing, and email spear phishing with its next-generation security awareness training and AI phishing simulation platform.
With Adaptive, security teams can prepare employees for advanced threats with incredible, highly customized training content that is personalized for employee role and access levels, features open-source intelligence about their company, and includes amazing deepfakes of their own executives.
Customers can measure the success of their training program over time with AI-powered phishing simulations. Hyper-realistic deepfake, voice, SMS, and email phishing tests assess risk levels across all threat vectors. Adaptive simulations are powered by an AI open-source intelligence engine that gives clients visibility into how their company's digital footprint can be leveraged by cybercriminals.
Today, Adaptive’s customers include leading global organizations like Figma, The Dallas Mavericks, BMC Software, and Stone Point Capital. The company has a world class NPS score of 94, among the highest in cybersecurity.
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JOpt.TourOptimizer is an enterprise optimization engine for route planning, scheduling, and resource allocation across logistics, transportation, dispatch, and field service operations. It is built for organizations that need to solve complex planning problems under real-world business constraints rather than simple consumer-grade route calculation. The platform supports vehicle routing and scheduling scenarios such as VRP, CVRP, VRPTW, pickup and delivery, multi-depot planning, heterogeneous fleets, and workforce scheduling.
JOpt.TourOptimizer can model time windows, working hours, visit durations, capacities, skills and expertise levels, territories, zone governance, overnight stays, alternate destinations, and custom business rules. This makes it suitable for production deployments where feasibility, transparency, and operational reliability matter. It is designed to generate practical plans that help teams balance travel time, service commitments, workload distribution, and operational cost in demanding enterprise environments.
The solution is available both as an embedded Java SDK and as a Docker-based REST API with OpenAPI and Swagger support. This allows software vendors, enterprise developers, and system integrators to embed advanced optimization into TMS, ERP, CRM, WMS, dispatch systems, customer platforms, and field service applications. With support for scalable integration and modern service architectures, JOpt.TourOptimizer helps organizations improve planning efficiency, service quality, SLA compliance, transparency, and operational resilience at scale. It also supports enterprise integration strategies that require reproducible optimization runs, structured outputs, and flexible deployment models.
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Grape Ripeness Logger
Mio Vigneto Products is excited to introduce the Grape Ripeness Logger, marking the initial release in a line of affordable software solutions designed to assist Vineyard Managers and Winemakers in improving the quality of their wines. This innovative software facilitates the meticulous recording and organization of vineyard data by year, grape variety, and specific blocks, ensuring that users have reliable historical records. The interface of the Grape Ripeness Logger is optimized for both tablets and desktop computers, enabling seamless data entry in the field as measurements for grape sugar, TA, and pH are taken. Users can easily input vineyard ownership information and create a structured directory based on vineyard names, while subdirectories categorize entries by grape variety and sampling locations. Additionally, the Grape Data screen enables the input of key metrics like Brix, pH, and TA, which subsequently computes the Balance and Ripeness of the grapes. All collected data is conveniently displayed and stored in a user-friendly spreadsheet format. Furthermore, users can also determine the ideal "Harvest Date" based on their target Brix, pH, and TA levels, which enhances planning and decision-making for the harvest season. This tool is poised to offer invaluable support to the wine industry, simplifying the management process for both current and future vintages.
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daisyUI
DaisyUI serves as a component library for Tailwind CSS, streamlining the development process by offering semantic class names for various UI elements, including cards and toggles. This design choice minimizes the necessity for extensive utility class coding, leading to cleaner and more easily manageable HTML structures. Built atop Tailwind CSS, DaisyUI allows for extensive customization of components with Tailwind's utility classes. It functions purely as a CSS plugin without any JavaScript dependencies, ensuring it remains compatible with different JavaScript frameworks. Installation is simple, and it provides support for limitless themes through customizable color names that leverage CSS variables, making it easy to implement features like dark mode without adding extra class names. Furthermore, DaisyUI integrates seamlessly with Tailwind CSS, providing developers the flexibility to customize every aspect using utility classes. This plugin is designed to work flawlessly across all JavaScript frameworks and does not require a separate JavaScript bundle, making it an efficient choice for developers looking to enhance their UI design process.
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