Docmosis is a self-hosted or SaaS template-based document generation solution. Integrate with custom-built software applications or popular third-party apps using the API.
Create templates using MS Word or LibreOffice. Add plain-text placeholders to control: the insertion of text/images/tables; conditionally add/remove any content; perform calculations; loop over repeating data; format data/numbers and much more.
Integrate with: Custom software built using Java, C#, Python, PHP, Ruby and more via a REST API; Low-code and no-code platforms like Appian, Bubble, Mendix, Outsystems; Third-party form builders or apps that can perform a webhook such as FormAssembly or Salesforce.
Used by customers in Finance, Health, Legal, Education, Government, HR, Insurance, Logistics, and Manufacturing to generate customized letters invoices, proposals, contracts, statements, reports and more.
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Teradata VantageCloud: Open, Scalable Cloud Analytics for AI
VantageCloud is Teradata’s cloud-native analytics and data platform designed for performance and flexibility. It unifies data from multiple sources, supports complex analytics at scale, and makes it easier to deploy AI and machine learning models in production. With built-in support for multi-cloud and hybrid deployments, VantageCloud lets organizations manage data across AWS, Azure, Google Cloud, and on-prem environments without vendor lock-in. Its open architecture integrates with modern data tools and standard formats, giving developers and data teams freedom to innovate while keeping costs predictable.
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Jazzer
Jazzer, created by Code Intelligence, is a coverage-guided fuzzer designed for the JVM platform that operates within the process. It draws inspiration from libFuzzer, incorporating several of its advanced mutation features powered by instrumentation into the JVM environment. Users can explore Jazzer's autofuzz mode via Docker, which autonomously produces arguments for specified Java functions while also identifying and reporting any unexpected exceptions and security vulnerabilities that arise. Additionally, individuals can utilize the standalone Jazzer binary available in GitHub release archives, which initiates its own JVM specifically tailored for fuzzing tasks. This flexibility allows developers to effectively test their applications for robustness against various edge cases.
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american fuzzy lop
American fuzzy lop is a security-focused fuzzer that utilizes a unique form of compile-time instrumentation along with genetic algorithms to automatically generate effective test cases that can uncover new internal states within the targeted binary. This approach significantly enhances the functional coverage of the code being fuzzed. Additionally, the compact and synthesized test cases produced by the tool can serve as a valuable resource for initiating other, more demanding testing processes in the future. Unlike many other instrumented fuzzers, afl-fuzz is engineered for practicality, boasting a minimal performance overhead while employing a diverse array of effective fuzzing techniques and strategies for minimizing effort. It requires almost no setup and can effortlessly manage complicated, real-world scenarios, such as those found in common image parsing or file compression libraries. As an instrumentation-guided genetic fuzzer, it excels at generating complex file semantics applicable to a wide variety of challenging targets, making it a versatile choice for security testing. Its ability to adapt to different environments further enhances its appeal for developers seeking robust solutions.
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