
Retool is a modern AI-native application development platform designed to help teams build internal software quickly and efficiently. It enables users to create agents, workflows, dashboards, and full-stack apps using natural language prompts and visual tools. Retool connects directly to databases, APIs, vector stores, and AI models to ensure applications work seamlessly with existing systems. The platform allows teams to transform raw data into actionable tools such as dashboards, admin panels, and monitoring systems. With drag-and-drop UI building, code-level customization, and AI-assisted generation, Retool supports multiple development styles. Built-in workflows automate complex processes while maintaining auditability and security. Retool fits naturally into standard engineering stacks with support for CI/CD and version control. Enterprise-grade permissions and hosting options ensure sensitive data stays protected. Used by thousands of companies worldwide, Retool helps teams ship AI-powered software faster. It bridges the gap between idea and production with speed and control.
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Most enterprise invoices are never paid from an emailed invoice. Across the $2B+ in receivables Monk manages, 92% have to be submitted through the buyer accounts payable portal instead, and a failed submission is usually silent.
Monk is an AI-native accounts receivable platform built around that problem. It files invoices into more than 600 corporate AP portals, including Coupa, Ariba and SAP Business Network, uploads 87% without a person, and brings each rejection back onto the invoice record with the reason attached.
Collections runs on the same data. Julia, the Monk agent for Intelligent Collections, reads inbound replies and answers what the customer wrote instead of advancing a dunning schedule, clearing 90% of invoices without escalation. Outbound mail sends through your existing Gmail or Microsoft 365 mailbox.
Payments match at 80%, rising to 95% once rules are added. Runs on QuickBooks, NetSuite or Dynamics 365 Business Central. SOC 2 Type II. Live in one to three days.
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easybooking JULIA
As a host, you often find yourself dedicating countless hours to managing tasks like responding to inquiries, creating bills, and overseeing room availability. Fortunately, with JULIA, the innovative virtual receptionist, those burdens are lifted! JULIA is not merely a hotel management program; it functions as a comprehensive solution that autonomously manages bed sales around the clock through seamless online bookings and effective channel management. This intelligent system streamlines various aspects such as room administration, guest communication, registration, and accounting, among others. Thanks to a wide array of interfaces connecting to popular booking platforms like Booking.com, Airbnb, and Expedia, JULIA adeptly satisfies the needs of guests, hosts, and small hotel operators alike. From the initial inquiry to the final thank-you email, JULIA ensures that open offers are followed up on, arrival details are communicated, and invoices are generated—all automatically and available in up to seven different languages. This level of efficiency allows hosts to focus on providing exceptional experiences for their guests.
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JupyterLab
Project Jupyter is dedicated to the creation of open-source tools, standards, and services that facilitate interactive computing in numerous programming languages. At the heart of this initiative is JupyterLab, a web-based interactive development environment designed for Jupyter notebooks, coding, and data manipulation. JupyterLab offers remarkable flexibility, allowing users to customize and organize the interface to cater to various workflows in fields such as data science, scientific research, and machine learning. Its extensibility and modular nature enable developers to create plugins that introduce new features and seamlessly integrate with existing components. The Jupyter Notebook serves as an open-source web application enabling users to produce and share documents that incorporate live code, mathematical equations, visualizations, and descriptive text. Common applications of Jupyter include data cleaning and transformation, numerical simulations, statistical analysis, data visualization, and machine learning, among others. Supporting over 40 programming languages—including popular ones like Python, R, Julia, and Scala—Jupyter continues to be a valuable resource for researchers and developers alike, fostering collaborative and innovative approaches to computing challenges.
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