
Compliance work eats engineering time. Hyperproof exists to give that time back by automating the parts of GRC that don't need a human: pulling evidence out of GitHub, Jira, ServiceNow, Snyk, and cloud storage on a schedule, running recurring tests against high-frequency controls, and kicking off a task automatically the moment something fails instead of waiting for the next audit cycle to find out.
Under the hood, Hyperproof maps one control to 160+ frameworks (SOC 2, ISO 27001, HIPAA, NIST, and others), so a control tested once can satisfy several standards instead of forcing teams to rebuild the same work per framework. AI agents handle the first pass on evidence review and gap-flagging, leaving humans to make the actual judgment calls rather than hunting down documentation.
Teams using it report cutting audit prep by roughly 350 hours a year, a 66% drop in duplicate controls, and about $150K saved annually on control orchestration. It also scales to messier org charts, with the ability to scope controls by business unit or entity instead of flattening everything into one program.
Built in 2018 out of the Seattle area, Hyperproof is used by engineering and security-heavy orgs like Reddit, Fortinet, Appian, and Outreach that are tired of treating compliance as a manual, spreadsheet-and-email process and want it to run more like the rest of their infrastructure: automated, monitored, and auditable.
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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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MongoDB
MongoDB is a versatile, document-oriented, distributed database designed specifically for contemporary application developers and the cloud landscape. It offers unparalleled productivity, enabling teams to ship and iterate products 3 to 5 times faster thanks to its adaptable document data model and a single query interface that caters to diverse needs. Regardless of whether you're serving your very first customer or managing 20 million users globally, you'll be able to meet your performance service level agreements in any setting. The platform simplifies high availability, safeguards data integrity, and adheres to the security and compliance requirements for your critical workloads. Additionally, it features a comprehensive suite of cloud database services that support a broad array of use cases, including transactional processing, analytics, search functionality, and data visualizations. Furthermore, you can easily deploy secure mobile applications with built-in edge-to-cloud synchronization and automatic resolution of conflicts. MongoDB's flexibility allows you to operate it in various environments, from personal laptops to extensive data centers, making it a highly adaptable solution for modern data management challenges.
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Amazon DocumentDB
Amazon DocumentDB, which is compatible with MongoDB, offers a rapid, scalable, highly reliable, and fully managed solution for document database needs, specifically catering to MongoDB workloads. This service simplifies the storage, querying, and indexing of JSON data, making it an ideal choice for developers. Built from the ground up as a non-relational database, Amazon DocumentDB ensures the performance, scalability, and availability crucial for handling mission-critical MongoDB workloads on a large scale. One of its key features is the separation of storage and compute, which allows each component to scale independently. Users can enhance read capacity to millions of requests per second in a matter of minutes by adding up to 15 low-latency read replicas, irrespective of data volume. Additionally, Amazon DocumentDB is engineered for 99.99% availability, maintaining six copies of data across three different AWS Availability Zones (AZs) to ensure redundancy and reliability. This architecture not only enhances data safety but also significantly improves the overall performance of applications that rely on it.
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