Kubit
Warehouse-Native Customer Journey Analytics—No Black Boxes. Total Transparency.
Kubit is the leading customer journey analytics platform, purpose-built for product, data, and marketing teams that need self-service insights, real-time data visibility, and complete control—without engineering bottlenecks or vendor lock-in.
Unlike legacy analytics solutions, Kubit is natively integrated with your cloud data warehouse (Snowflake, BigQuery, Databricks), so you can analyze customer behavior and user journeys directly at the source. No data exports. No hidden models. No black-box limitations.
With out-of-the-box capabilities for funnel analysis, retention metrics, user pathing, and cohort analysis, Kubit delivers actionable insights across the full customer lifecycle. Layer in real-time anomaly detection and exploratory analytics to move faster, optimize performance, and drive user engagement.
Leading brands like Paramount, TelevisaUnivision, and Miro rely on Kubit for its flexibility, enterprise-grade governance, and best-in-class customer support.
See why Kubit is redefining customer journey analytics at kubit.ai
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MuukTest
It's clear that enhancing your testing efforts could help identify bugs sooner, yet effective QA testing often demands significant time, effort, and resources. With MuukTest, engineering teams can achieve up to 95% coverage of end-to-end tests in a mere three months.
Our team of QA specialists is dedicated to creating, overseeing, maintaining, and updating E2E tests on the MuukTest Platform for your web, API, and mobile applications with unparalleled speed. After reaching 100% regression coverage within just eight weeks, we initiate exploratory and negative testing to discover bugs and further elevate your testing coverage. By managing your testing frameworks, scripts, libraries, and maintenance, we significantly reduce the time you spend on development.
Additionally, we take a proactive approach to identify flaky tests and false results, ensuring that your testing process remains accurate. Consistently conducting early and frequent tests enables you to catch errors during the initial phases of the development lifecycle, thus minimizing the burden of technical debt in the future. By streamlining your testing processes, you can improve overall product quality and enhance team productivity.
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go-fuzz
Go-fuzz is a specialized fuzzing tool that utilizes coverage guidance to effectively test Go packages, making it particularly adept at handling complex inputs, whether they are textual or binary. This type of testing is essential for fortifying systems that must manage data from potentially unsafe sources, such as those arising from network interactions. Recently, go-fuzz has rolled out preliminary support for fuzzing Go Modules, encouraging users to report any issues they experience along with comprehensive details. The tool creates random input data, which is frequently invalid, and if a function returns a value of 1, it prompts the fuzzer to prioritize that input for subsequent tests, though it should not be included in the corpus, even if it reveals new coverage; conversely, a return value of 0 indicates the opposite, while other return values are earmarked for future improvements. It is necessary for the fuzz function to be placed within a package recognized by go-fuzz, thus excluding the main package from testing but allowing for the fuzzing of internal packages. This organized methodology not only streamlines the testing process but also enhances the focus on discovering vulnerabilities within the code, ultimately leading to more robust software solutions. By continuously refining its support and encouraging community feedback, go-fuzz aims to evolve and adapt to the needs of developers.
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Peach Fuzzer
Peach stands out as a sophisticated SmartFuzzer that specializes in both generation and mutation-based fuzzing methodologies. It requires the development of Peach Pit files, which detail the structure, type specifics, and relationships of the data necessary for successful fuzzing efforts. Moreover, Peach allows for tailored configurations during a fuzzing session, including options for selecting a data transport (publisher) and a logging interface. Since its launch in 2004, Peach has seen consistent enhancements and is currently in its third major version. Fuzzing continues to be one of the most effective approaches for revealing security flaws and pinpointing bugs within software systems. By engaging with Peach for hardware fuzzing, students will explore fundamental concepts associated with device fuzzing techniques. This versatile tool is suitable for a variety of data consumers, making it applicable to both servers and embedded systems alike. A diverse range of users, such as researchers, private enterprises, and governmental organizations, utilize Peach to identify vulnerabilities in hardware. This course will focus on using Peach specifically to target embedded devices, while also collecting crucial information in the event of a device crash, thereby deepening the comprehension of practical fuzzing techniques and their application in real-world scenarios. By the end of the course, participants will not only become proficient in using Peach but also develop a solid foundation in the principles underlying effective fuzzing strategies.
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