Alternatives to Threagile

Get quality translations for your app, website, game, supporting documentation, and on. Invite your own translation team or work with professional translation agencies within Crowdin. Features that ensure quality translations and speed up the process • Glossary – create a list of terms to get consistent translations • Translation Memory (TM) – no need to translate identical strings • Screenshots – tag source strings to get context-relevant translations • Integrations – set up integration with GitHub, Google Play, API, CLI, Android Studio, and on • QA checks – make sure that all the translations have the same meaning and functions as the source strings • In-Context – proofreading within the actual web application • Machine Translations (MT) – pre-translate via translation engine • Reports – get insights, plan and manage the project Crowdin supports more than 30 file formats for mobile, software, documents, subtitles, graphics and assets: .xml, .strings, .json, .html, .xliff, .csv, .php, .resx, .yaml, .xml, .strings and on.

OWASP Threat Dragon serves as a modeling tool designed for creating diagrams that represent potential threats within a secure development lifecycle. Adhering to the principles of the threat modeling manifesto, Threat Dragon enables users to document potential threats and determine appropriate mitigation strategies, while also providing a visual representation of the various components and surfaces related to the threat model. This versatile tool is available as both a web-based application and a desktop version. The Open Web Application Security Project (OWASP) is a nonprofit organization dedicated to enhancing software security, and all of its projects, tools, documents, forums, and chapters are accessible for free to anyone eager to improve application security practices. By facilitating collaboration and knowledge sharing, OWASP encourages a community-focused approach to achieving higher security standards in software development.

IriusRisk is an open Threat Modeling platform that can be used by any development and operations team – even those without prior security training. Whether your organization follows a framework or not, we can work with all the threat modeling methodologies, such as STRIDE, TRIKE, OCTAVE and PASTA. We support organisations in financial services, insurance, industrial automation, healthcare, private sector and more. IriusRisk is the industry's leading threat modeling and secure design solution in Application Security. With enterprise clients including Fortune 500 banks, payments, and technology providers, it empowers security and development teams to ensure applications have security built-in from the start - using its powerful threat modeling platform. Whether teams are implementing threat modeling from scratch, or scaling-up their existing operations, the IriusRisk approach results in improved speed-to-market, collaboration across security and development teams, and the avoidance of costly security flaws.

Today, Security Compass is a pioneer in application security that enables organizations to shift left and build secure applications by design, integrated directly with existing DevSecOps tools and workflows. To better understand the benefits, costs, and risks associated with an investment in SD Elements, Security Compass commissioned Forrester Consulting to interview four decision-makers with direct experience using the platform. Forrester aggregated the interviewees’ experiences for this study and combined the results into a single composite organization. The decision-maker interviews and financial analysis found that a composite organization experiences benefits of $2.86 million over three years versus costs of $663,000, adding up to a net present value (NPV) of $2.20 million and an ROI of 332%. Security Compass is the trusted solution provider to leading financial and technology organizations, the US Department of Defense, government agencies, and renowned global brands across multiple industries.

From various assets and countermeasures to factoids, personas, and architectural components, you can enter or upload a diverse array of data related to security, usability, and requirements to uncover valuable insights, including the links between requirements and risks as well as the rationale behind persona traits. Since no single perspective can encompass the complexity of a system, you can effortlessly create 12 distinct views of your developing design that examine aspects such as people, risks, requirements, architecture, and even geographical location. Additionally, as your preliminary design progresses, you can automatically produce threat models like Data Flow Diagrams (DFDs). Utilize open-source intelligence regarding potential threats and viable security architectures to assess your attack surface effectively. Furthermore, you can visualize all the security, usability, and design factors related to the risks associated with your product and how they interact with one another. This comprehensive approach ensures a thorough understanding of your system's vulnerabilities and strengths.

Threat modeling serves as a fundamental aspect of the Microsoft Security Development Lifecycle (SDL), acting as an engineering strategy aimed at uncovering potential threats, attacks, vulnerabilities, and countermeasures that may impact your application. This technique not only aids in the identification of risks but also influences the design of your application, aligns with your organization's security goals, and mitigates potential hazards. The Microsoft Threat Modeling Tool simplifies the process for developers by utilizing a standardized notation that helps visualize system components, data flows, and security boundaries. Additionally, it assists those involved in threat modeling by highlighting various classes of threats to consider, depending on the architectural design of their software. Crafted with the needs of non-security professionals in mind, this tool enhances accessibility for all developers, offering straightforward guidance on the creation and evaluation of threat models, ultimately fostering a more secure software development practice. By integrating threat modeling into their workflow, developers can proactively address security concerns before they escalate into serious issues.

ThreatModeler™, an enterprise threat modeling platform, is an automated solution that reduces the effort required to develop secure applications. Today's information security professionals have a pressing need to create threat models of their organizations' data and software. We do this at the scale of their IT ecosystem and with the speed of innovation. ThreatModeler™, which empowers enterprise IT organizations, allows them to map their unique security requirements and policies directly into the enterprise cyber ecosystem. This provides real-time situational awareness of their threat portfolio and risks. InfoSec executives and CISOs gain a complete understanding of their entire attack landscape, defense-in depth strategy, and compensating control, which allows them to strategically allocate resources and scale up their output.

A surge of vulnerabilities can be overwhelming, but addressing every single one isn't feasible. Utilize comprehensive threat intelligence and innovative prioritization techniques to reduce expenses, streamline processes, and ensure that your teams concentrate on the most significant threats to your organization. This approach embodies Modern Risk-Based Vulnerability Management. Our Risk-Based Vulnerability Management software is pioneering a new standard in the field. It guides your security and IT teams on which infrastructure vulnerabilities to address and when to take action. The newest iteration demonstrates that exploitability can be quantified, and effectively measuring it can aid in its reduction. Cisco Vulnerability Management (previously known as Kenna.VM) merges practical threat and exploit insights with sophisticated data analytics to identify vulnerabilities that present the greatest risk while allowing you to deprioritize lesser threats. Expect your extensive list of “critical vulnerabilities” to diminish more quickly than a wool sweater in a hot wash cycle, providing a more manageable and efficient security strategy. By adopting this modern methodology, organizations can enhance their overall security posture and respond more effectively to emerging threats.

User-friendly interface, established taxonomies, and versatile output options are all present. The Tutamen Threat Model Automator is crafted to support security measures during the architectural phase, a time when correcting any flaws is most cost-effective. By minimizing human error and inconsistencies, it allows for a streamlined input of variables. This tool creates a dynamic threat model that adapts as the design evolves. Moreover, the Tutamen Threat Model Automator can produce various reports tailored for different stakeholders across your organization, not limited to just your current project. You are already familiar with its functionality, as there is no need to learn any new software. Additionally, it integrates seamlessly with tools you often use, such as Microsoft Visio and Excel, making it even more convenient. Ultimately, it empowers teams to enhance their security protocols with minimal disruption to their existing workflows.

MITRE ATT&CK® serves as a comprehensive, publicly-accessible repository detailing the tactics and techniques employed by adversaries, grounded in actual observations from the field. This repository acts as a crucial resource for shaping targeted threat models and strategies across various sectors, including private enterprises, government agencies, and the broader cybersecurity industry. By establishing ATT&CK, MITRE is advancing its commitment to creating a safer world through collaborative efforts aimed at enhancing cybersecurity efficacy. The ATT&CK framework is freely available to individuals and organizations alike, making it an invaluable tool for improving security practices. Adversaries often engage in active reconnaissance scans to collect pertinent information that aids in their targeting efforts, utilizing direct network traffic to probe victim infrastructure rather than employing indirect methods. This proactive approach to gathering intelligence underscores the importance of vigilance in cybersecurity to counter such tactics effectively.

Discover the ultimate solution for identifying, tracking, and safeguarding sensitive information on a large scale. This comprehensive data security platform is designed to swiftly mitigate risks, identify unusual activities, and ensure compliance without hindering your operations. Combining a robust platform, a dedicated team, and a strategic plan, it equips you with a competitive edge. Through the integration of classification, access governance, and behavioral analytics, it effectively secures your data, neutralizes threats, and simplifies compliance processes. Our tried-and-true methodology draws from countless successful implementations to help you monitor, protect, and manage your data efficiently. A team of expert security professionals continuously develops sophisticated threat models, revises policies, and supports incident management, enabling you to concentrate on your key objectives while they handle the complexities of data security. This collaborative approach not only enhances your security posture but also fosters a culture of proactive risk management.

Podman is a container engine that operates without a daemon, designed for the development, management, and execution of OCI Containers on Linux systems. It enables users to run containers in both root and rootless modes, effectively allowing you to think of it as a direct replacement for Docker by using the command alias docker=podman. With Podman, users can manage pods, containers, and container images while offering support for Docker Swarm. We advocate for the use of Kubernetes as the primary standard for creating Pods and orchestrating containers, establishing Kubernetes YAML as the preferred format. Consequently, Podman facilitates the creation and execution of Pods directly from a Kubernetes YAML file through commands like podman-play-kube. Additionally, it can generate Kubernetes YAML configurations from existing containers or Pods using podman-generate-kube, streamlining the workflow from local development to deployment in a production Kubernetes environment. This versatility makes Podman a powerful tool for developers and system administrators alike.

ARIA Advanced Detection and Response (ADR) is an automated AI-driven security operations center (SOC) solution designed with the functionalities of seven distinct security tools, including SIEMs, IDS/IPSs, EDRs, threat intelligence tools, network traffic analyzers, user and entity behavior analytics, and security orchestration, automation, and response systems. By utilizing this all-encompassing solution, organizations can avoid the pitfalls of inadequate threat surface coverage and the challenges associated with integrating and managing various tools that incur high costs with minimal benefits. ARIA ADR employs machine learning-enhanced threat models, powered by AI, to swiftly detect and neutralize severe network threats, including ransomware, malware, intrusions, zero-day vulnerabilities, advanced persistent threats, and more, all within a matter of minutes. This capability offers a significant edge over conventional security operations methods, which tend to generate more false alarms than actual threats and necessitate a team of highly skilled security personnel. Additionally, a cloud-based version of ARIA ADR is available, serving as an excellent entry-level solution for organizations looking to bolster their security posture without extensive investment. This flexibility makes ARIA ADR accessible to a wider range of businesses, enhancing their ability to defend against evolving cyber threats.

Axolotl is an innovative open-source tool crafted to enhance the fine-tuning process of a variety of AI models, accommodating numerous configurations and architectures. This platform empowers users to train models using diverse methods such as full fine-tuning, LoRA, QLoRA, ReLoRA, and GPTQ. Additionally, users have the flexibility to customize their configurations through straightforward YAML files or by employing command-line interface overrides, while also being able to load datasets in various formats, whether custom or pre-tokenized. Axolotl seamlessly integrates with cutting-edge technologies, including xFormers, Flash Attention, Liger kernel, RoPE scaling, and multipacking, and it is capable of operating on single or multiple GPUs using Fully Sharded Data Parallel (FSDP) or DeepSpeed. Whether run locally or in the cloud via Docker, it offers robust support for logging results and saving checkpoints to multiple platforms, ensuring users can easily track their progress. Ultimately, Axolotl aims to make the fine-tuning of AI models not only efficient but also enjoyable, all while maintaining a high level of functionality and scalability. With its user-friendly design, it invites both novices and experienced practitioners to explore the depths of AI model training.

Open Interpreter is an open-source tool that provides a natural language interface for users to run code via conversational prompts within a terminal setting. It accommodates various programming languages like Python, JavaScript, and Shell, making it suitable for a diverse array of tasks such as data analysis, file management, and even web surfing. To improve user engagement, it features interactive mode commands that enhance the overall experience. Users have the ability to customize default settings through YAML files, allowing for easy adjustments without the need to modify command-line arguments each time they run a command. Furthermore, Open Interpreter can be seamlessly integrated with FastAPI, enabling the creation of RESTful endpoints that allow for programmatic control of its features. In addition to these functionalities, it prioritizes user safety by requesting confirmation before executing any code that may affect the local environment, thus reducing potential risks associated with unintended code execution. Overall, Open Interpreter represents a significant advancement in making coding more accessible and user-friendly.

Ludwig serves as a low-code platform specifically designed for the development of tailored AI models, including large language models (LLMs) and various deep neural networks. With Ludwig, creating custom models becomes a straightforward task; you only need a simple declarative YAML configuration file to train an advanced LLM using your own data. It offers comprehensive support for learning across multiple tasks and modalities. The framework includes thorough configuration validation to identify invalid parameter combinations and avert potential runtime errors. Engineered for scalability and performance, it features automatic batch size determination, distributed training capabilities (including DDP and DeepSpeed), parameter-efficient fine-tuning (PEFT), 4-bit quantization (QLoRA), and the ability to handle larger-than-memory datasets. Users enjoy expert-level control, allowing them to manage every aspect of their models, including activation functions. Additionally, Ludwig facilitates hyperparameter optimization, offers insights into explainability, and provides detailed metric visualizations. Its modular and extensible architecture enables users to experiment with various model designs, tasks, features, and modalities with minimal adjustments in the configuration, making it feel like a set of building blocks for deep learning innovations. Ultimately, Ludwig empowers developers to push the boundaries of AI model creation while maintaining ease of use.

Configuration as code allows for pipelines to be set up using a straightforward and legible file that can be committed to your git repository. Each step in the pipeline runs within a dedicated Docker container, which is automatically retrieved at the time of execution. Drone is compatible with various source code management systems, effortlessly integrating with platforms like GitHub, GitHubEnterprise, Bitbucket, and GitLab. It supports a wide range of operating systems and architectures, including Linux x64, ARM, ARM64, and Windows x64. Additionally, Drone is flexible with programming languages, functioning seamlessly with any language, database, or service that operates in a Docker container, offering the choice of utilizing thousands of public Docker images or providing custom ones. The platform also facilitates the creation and sharing of plugins by leveraging containers to insert pre-configured steps into your pipeline, allowing users to select from hundreds of available plugins or develop their own. Furthermore, Drone simplifies advanced customization options, enabling users to implement tailored access controls, establish approval workflows, manage secrets, extend YAML syntax, and much more. This flexibility ensures that teams can optimize their workflows according to their specific needs and preferences.

Languine is an innovative localization platform powered by AI that aims to automate and enhance the translation process for applications, facilitating smooth integration into development workflows. This platform provides intelligent, context-sensitive translations in more than 100 languages, ensuring that the brand's voice and tone remain consistent throughout. With a command-line interface and support for continuous integration/continuous deployment, developers can easily manage translations manually or set up automation in their existing pipelines. Languine accommodates a variety of file formats, such as JSON, YAML, and Markdown, making it suitable for a wide range of project needs. Furthermore, it includes fine-tuning capabilities that allow for the customization of translations to better reflect unique brand qualities. In addition to its core features, Languine provides a GitHub Action that automates the localization process directly within GitHub, ensuring that translations remain up-to-date with every commit and deployment. This comprehensive tool not only saves time but also enhances collaboration among team members working on multilingual projects.

The online JSON Editor provided by JSON Formatter is an intuitive tool crafted for the purposes of editing, viewing, and analyzing JSON data efficiently. Among its numerous features are capabilities for formatting, beautifying, and validating JSON, in addition to converting it into other formats like XML, CSV, and YAML. Users have the option to load their JSON data through file uploads or by entering URLs, and they can conveniently share their edited JSON via generated links. Operating entirely within the browser guarantees that data remains local, which significantly boosts both security and performance. This makes it an ideal choice for developers and data analysts alike who prioritize data privacy while working with various JSON formats.

APIFuzzer analyzes your API specifications and systematically tests the fields to ensure your application can handle modified parameters, all without the need for programming. It allows you to import API definitions from either local files or remote URLs, supporting both JSON and YAML formats. Every HTTP method is accommodated, and it can fuzz the request body, query strings, path parameters, and request headers. Utilizing random mutations, it also integrates seamlessly with continuous integration systems. The tool can produce test reports in JUnit XML format and has the capability to send requests to alternative URLs. It supports HTTP basic authentication through configuration settings and stores reports of any failed tests in JSON format within a designated folder, thus ensuring that all results are easily accessible for review. Additionally, this enhances your ability to identify vulnerabilities and improve the reliability of your API.

JSON Crack is a versatile open-source application that converts intricate data formats like JSON, YAML, CSV, XML, and TOML into engaging and easy-to-understand graphs, thereby facilitating better data analysis and understanding. Users have the flexibility to enter data directly, upload files, or provide links, with the platform seamlessly creating a visual tree graph based on the input. Additionally, it offers capabilities for transforming data between various formats, such as converting JSON to CSV or XML to JSON, while also incorporating functions for JSON formatting, validation, and automatic code generation for TypeScript interfaces, Golang structs, and JSON Schemas. Furthermore, it features sophisticated tools for decoding JWTs, executing JQ queries, and running JSON Path commands. Users can conveniently export their visualizations in formats like PNG, JPEG, or SVG, and importantly, all data processing takes place locally on the user's device to maintain privacy. This comprehensive tool not only enhances usability but also empowers users to handle their data in a secure and efficient manner, making it an invaluable resource for developers and data analysts alike.

Easily create and oversee cloud resources utilizing straightforward templates. Google Cloud Deployment Manager enables you to outline all necessary resources for your application in a declarative format using YAML. Additionally, Python or Jinja2 templates can be employed to parameterize the configuration, facilitating the reuse of standard deployment methods like a load-balanced, auto-scaled instance group. By considering your configuration as code, you can achieve repeatable deployments effortlessly. Through the creation of configuration files that delineate the resources, the resource creation process can be replicated consistently and reliably. Unlike many tools that follow an imperative approach, which requires users to specify each step involved in resource creation and configuration, a declarative approach empowers users to define desired configurations and allows the system to determine the necessary steps. This shift in focus lets users concentrate on the collective resources that make up their application or service rather than managing each resource in isolation. Ultimately, this methodology streamlines the deployment process, enhancing efficiency and reliability.

CloudKnit is a progressive delivery platform that is open-source and designed for the management of cloud environments. It features user-friendly dashboards that facilitate the visualization and monitoring of these environments. Users can define entire environments in a clear and straightforward YAML format, allowing for a declarative approach to configuration. By using this declarative format, organizations can efficiently provision their environments, identify and address any drift, and dismantle resources when they are no longer necessary. The platform includes a control plane that oversees the state of the environment, ensuring proper management of resource dependencies as well as drift detection and reconciliation. Furthermore, the Environment as Code (EaC) abstraction simplifies the utilization of cloud-native tools, making the entire process more streamlined. With CloudKnit, users benefit from a powerful tool that enhances the management and organization of their cloud environments.

Hdiv solutions provide comprehensive, all-encompassing security measures that safeguard applications from within while facilitating easy implementation across diverse environments. By removing the necessity for teams to possess specialized security knowledge, Hdiv automates the self-protection process, significantly lowering operational expenses. This innovative approach ensures that applications are protected right from the development phase, addressing the fundamental sources of risk, and continues to offer security once the applications are live. Hdiv's seamless and lightweight system requires no additional hardware, functioning effectively with the standard hardware allocated to your applications. As a result, Hdiv adapts to the scaling needs of your applications, eliminating the conventional extra costs associated with security hardware. Furthermore, Hdiv identifies security vulnerabilities in the source code prior to exploitation, utilizing a runtime dataflow technique that pinpoints the exact file and line number of any detected issues, thereby enhancing overall application security even further. This proactive method not only fortifies applications but also streamlines the development process as teams can focus on building features instead of worrying about potential security flaws.

Enhanced operators for enterprise applications feature a comprehensive application graph and declarative integration that caters to both Kubernetes environments and legacy systems. Through Juju operator integration, we can simplify each operator, enabling their composition to form intricate application graph topologies that handle complex scenarios while providing a user-friendly experience with significantly reduced YAML requirements. The UNIX principle of ‘doing one thing well’ is equally applicable in the realm of large-scale operational code, yielding similar advantages in clarity and reusability. The charm of small-scale design is evident here: Juju empowers organizations to implement the operator pattern across their entire infrastructure, including older applications. Model-driven operations lead to substantial savings in maintenance and operational expenses for traditional workloads, all without necessitating a shift to Kubernetes. Once integrated with Juju, legacy applications also gain the ability to operate across multiple cloud environments. Furthermore, the Juju Operator Lifecycle Manager (OLM) uniquely accommodates both containerized and machine-based applications, ensuring smooth interoperability between the two. This innovative approach allows for a more cohesive and efficient management of diverse application ecosystems.

Rkt is an advanced application container engine crafted specifically for contemporary cloud-native environments in production. Its design incorporates a pod-native methodology, a versatile execution environment, and a clearly defined interface, making it exceptionally compatible with other systems. The fundamental execution unit in rkt is the pod, which consists of one or more applications running in a shared context, paralleling the pod concept used in Kubernetes orchestration. Users can customize various configurations, including isolation parameters, at both the pod level and the more detailed per-application level. In rkt, each pod operates directly within the traditional Unix process model, meaning there is no central daemon, allowing for a self-sufficient and isolated environment. Rkt also adopts a contemporary, open standard container format known as the App Container (appc) specification, while retaining the ability to run other container images, such as those generated by Docker. This flexibility and adherence to standards contribute to rkt's growing popularity among developers seeking robust container solutions.

YAML stands for "YAML Ain't Markup Language" and serves as a user-friendly data serialization format that is compatible with various programming languages. Its design prioritizes readability and ease of use for developers.

The push for digital transformation is compelling IT departments to expand their capabilities significantly. You are now responsible for gaining expertise in emerging technologies, collaborating with business units to shape digital strategies, and advising on strategic investments that ensure future growth. How can you confidently enhance your contributions? Turn to Alfabet, the leading solution in enterprise architecture management, IT portfolio management, and IT planning tools. Recognized by industry analysts, Alfabet empowers you to make informed IT investments by effectively managing your existing portfolio while proactively planning for what lies ahead. Leverage the most comprehensive meta-model for your IT initiatives, encompassing areas such as portfolio rationalization, strategy alignment, API management, Agile innovation, cloud management, project execution, M&A due diligence, risk management, GDPR compliance, IT governance, and beyond. Engage your stakeholders in the digital transformation process by tailoring Alfabet to resonate with each individual's preferences, ensuring the relevance of information and establishing straightforward procedures for task execution. Additionally, produce tailored roadmaps, insightful reports, and streamlined workflows that align with stakeholder interests and objectives, fostering a collaborative environment for successful digital initiatives. This approach not only enhances stakeholder buy-in but also drives a more cohesive digital strategy across the organization.

The collaboration between humans and machines allows computers to handle repetitive tasks, thus enabling people to concentrate on more creative and engaging aspects of their work. Saifr was built upon a vast array of documents that reflect the expertise of regulatory and compliance professionals, along with insights from numerous content creators. This extensive information has shaped Saifr's Natural Language Understanding (NLU) models, empowering the platform to effectively reduce regulatory and reputational risks. In contrast to traditional content processes, which often involve numerous hand-offs and email exchanges that can lead to inefficiencies and potential security vulnerabilities, Saifr's innovative solutions promote seamless teamwork among professionals, both within and beyond their organizations. By integrating with our NLU engine, these solutions ensure that compliant materials are generated, assessed, approved, and submitted in a more streamlined manner. Consequently, businesses benefit from the ability to produce compliant public communications at a significantly faster pace. Ultimately, the partnership between technology and human creativity enhances overall productivity and fosters a more efficient approach to compliance.

Our software-as-a-service platform facilitates ongoing data audits, governance of information, proactive management of risks, and a compliance toolkit that is readily available when needed. Built on Microsoft’s top-tier infrastructure, this secure and reliable application offers high availability to its users. Trace’s platform can be utilized as a managed service, combining the finest technology tools with personalized human support to provide a comprehensive compliance solution. For Data Protection Officers, we also offer a direct SaaS plan tailored to their needs. With Trace’s application and knowledgeable assistance, organizations can ensure compliance, reduce legal and data-related risks, and enhance their cloud due diligence through intelligent compliance documents, collaborative workflows, and electronic signatures. The platform features on-demand, visual, and easily demonstrable compliance reports for both you and your stakeholders. After utilizing our data mapping tool to model your data, the real value emerges: you gain insight into the locations of your data. Our exclusive global data visualizer allows you to understand where third parties store data, assess its adequacy, and proactively address privacy risks along with any legal deficiencies that may exist. This comprehensive approach not only enhances compliance but also empowers organizations to make informed decisions about their data management practices.

Kestra is a free, open-source orchestrator based on events that simplifies data operations while improving collaboration between engineers and users. Kestra brings Infrastructure as Code to data pipelines. This allows you to build reliable workflows with confidence. The declarative YAML interface allows anyone who wants to benefit from analytics to participate in the creation of the data pipeline. The UI automatically updates the YAML definition whenever you make changes to a work flow via the UI or an API call. The orchestration logic can be defined in code declaratively, even if certain workflow components are modified.

Streamlining your workflow can be accomplished through the implementation of pipelines, which serve as the core of the CI process in Microtica. Each component and microservice undergoes its build process via a pipeline, regardless of whether the trigger is manual or automatic. This build process is governed by a single authoritative document, the microtica.yaml file located in the root directory of the repository. One of the standout features is user customizability, allowing each user to specify their build process and the commands executed simply by modifying the microtica.yaml file. Additionally, this flexibility empowers users to tailor their workflows to better suit their specific project needs.

Enterprise synthetic test data solutions. It is essential that test data accurately reflects the structure of your database or application. This means it must be easy for you to model and maintain each project. Respect the referential integrity of parent/child/sibling relations across data domains within an app database or across multiple databases used for multiple applications. Ensure consistency and integrity of synthetic attributes across applications, data sources, and targets. A customer name must match the same customer ID across multiple transactions simulated by real-time synthetic information generation. Customers need to quickly and accurately build their data model for a test project. GenRocket offers ten methods to set up your data model. XTS, DDL, Scratchpad, Presets, XSD, CSV, YAML, JSON, Spark Schema, Salesforce.

Startupxplore stands out as Spain's premier platform for startup investments, targeting companies with significant growth potential from seed stage to Series A. It provides entrepreneurs with the reliability and backing typically associated with venture capital while maintaining the flexibility and terms characteristic of angel investing. In collaboration with over 12,000 registered investors, Startupxplore fosters a robust investment ecosystem. Furthermore, it boasts the title of the largest startup community in the country, comprising more than 28,000 entrepreneurs, accelerators, and various stakeholders in the entrepreneurship sector. The primary aim of Startupxplore is to empower its users to build a balanced and diversified investment portfolio comprising high-quality emerging businesses. To achieve this, we prioritize thorough company analysis and proactive risk management strategies, ensuring that our investors are well-informed and prepared for potential challenges in the startup landscape. This dedication to due diligence allows us to create meaningful connections between investors and innovative startups.

The Voyager SDK is specifically designed for edge-based Computer Vision, allowing clients to effortlessly implement AI solutions tailored to their business needs on edge devices. By utilizing the SDK, users can integrate their applications into the Metis AI platform and operate them on Axelera’s robust Metis AI Processing Unit (AIPU), regardless of whether the applications are built with custom or commonly used industry models. With its comprehensive end-to-end integration, the Voyager SDK ensures API compatibility with prevailing industry standards, maximizing the capabilities of the Metis AIPU and providing high-performance AI that can be deployed swiftly and smoothly. Developers can outline their complete application workflows using an easy-to-understand, high-level declarative language known as YAML, which accommodates one or more neural networks along with associated pre- and post-processing tasks, encompassing advanced image processing techniques. This approach not only simplifies the development process but also enhances the efficiency of deploying complex AI solutions in real-world scenarios.

doteval serves as an AI-driven evaluation workspace that streamlines the development of effective evaluations, aligns LLM judges, and establishes reinforcement learning rewards, all integrated into one platform. This tool provides an experience similar to Cursor, allowing users to edit evaluations-as-code using a YAML schema, which makes it possible to version evaluations through various checkpoints, substitute manual tasks with AI-generated differences, and assess evaluation runs in tight execution loops to ensure alignment with proprietary datasets. Additionally, doteval enables the creation of detailed rubrics and aligned graders, promoting quick iterations and the generation of high-quality evaluation datasets. Users can make informed decisions regarding model updates or prompt enhancements, as well as export specifications for reinforcement learning training purposes. By drastically speeding up the evaluation and reward creation process by a factor of 10 to 100, doteval proves to be an essential resource for advanced AI teams working on intricate model tasks. In summary, doteval not only enhances efficiency but also empowers teams to achieve superior evaluation outcomes with ease.

ConvertCSV is a web-based application that facilitates the conversion of CSV files to various formats, including JSON, XML, SQL, KML, YAML, and Markdown, among others. It features a range of utilities, such as CSV viewers and editors, as well as tools designed for data extraction, including emails and URLs. Users can execute operations like querying CSV files using SQL, splitting large datasets, and converting CSV files into fixed-width formats, Excel sheets, or PDFs. The entire processing is done on the client-side, ensuring user privacy, and it is capable of handling large files efficiently. With the ability to use SQL for querying and writing data back to CSV or JSON, users have powerful options at their disposal. The tool's default setting includes an auto-detect mode for field separators, making it user-friendly. Additionally, users can extract emails or URLs from websites, filter data to include or exclude specific records, and sort data either alphabetically or numerically. There is also an option for including double or single quotes around values, while the application can treat all quotes as data when needed. Importantly, all operations occur completely on the client-side, meaning that your data remains securely on your device. This ensures a high level of confidentiality and control over your information throughout the conversion process.

Although not every model possesses the same quality, it is crucial for all models to have governance in place to promote responsible and ethical decision-making within an organization. The IBM® watsonx.governance™ toolkit for AI governance empowers you to oversee, manage, and track your organization's AI initiatives effectively. By utilizing software automation, it enhances your capacity to address risks, fulfill regulatory obligations, and tackle ethical issues related to both generative AI and machine learning (ML) models. This toolkit provides access to automated and scalable governance, risk, and compliance instruments that encompass aspects such as operational risk, policy management, compliance, financial oversight, IT governance, and both internal and external audits. You can proactively identify and mitigate model risks while converting AI regulations into actionable policies that can be enforced automatically, ensuring that your organization remains compliant and ethically sound in its AI endeavors. Furthermore, this comprehensive approach not only safeguards your operations but also fosters trust among stakeholders in the integrity of your AI systems.

Kubernetes is an open-source platform that provides developers and DevOps with an end-to-end security solution. This includes security compliance, risk analysis, security compliance and RBAC visualizer. It also scans images for vulnerabilities. Kubescape scans K8s clusters, Kubernetes manifest files (YAML files, and HELM charts), code repositories, container registries and images, detecting misconfigurations according to multiple frameworks (such as the NSA-CISA, MITRE ATT&CK®), finding software vulnerabilities, and showing RBAC (role-based-access-control) violations at early stages of the CI/CD pipeline. It instantly calculates risk scores and displays risk trends over time. Kubescape is one of the most popular Kubernetes security compliance tools for developers. Its easy-to-use interface, flexible output formats and automated scanning capabilities have made Kubescape one of the fastest growing Kubernetes tools. This has saved Kubernetes admins and users precious time, effort and resources.

Our platform offers a dynamic approach to evaluating and addressing AI-related risks in both models and datasets, focusing on issues like bias, proxy bias, and fairness. With our Responsible AI technology, we enhance the visibility of AI models, ensuring they are both explainable and interpretable. Our algorithms, grounded in research, work to identify and address risks stemming from a lack of robustness. Additionally, the platform conducts thorough reviews of the AI landscape in relation to various AI and MRM regulations, delivering in-depth risk assessments, detailed reporting, and automated remediation strategies. It is crucial to evaluate and mitigate AI risks present in both internally developed systems and those supplied by third parties. The SigmaRed platform facilitates an extensive third-party AI risk management (AI TPRM) process, significantly speeding up the AI risk assessment cycle while offering enhanced visibility, control, stakeholder-specific reporting, and a comprehensive repository of evidence. Furthermore, our technology not only enhances compliance but also fosters trust in AI systems by ensuring that potential risks are proactively managed.

DevOps teams now benefit from a unified platform that allows them to construct, deploy, and oversee applications, enabling swift and secure delivery of fixes, features, and updates to their customers. This all-in-one solution offers extensive integrations and supports rapid scalability. ShuttleOps serves as a no-code continuous delivery platform designed to facilitate the quick and easy management of complex distributed applications. With its intuitive drag-and-drop interface, ShuttleOps empowers teams and organizations to seamlessly adopt and enhance their DevOps practices. The platform supports various technologies, including Chef Habitat, Docker container registries, and tailored build configurations, allowing for deployments that require no YAML configurations. Additionally, it features Persistent Volume Claims, Ingress rules, and effective log management. Users can create customized workflows with integrated collaboration tools, which include acknowledgment and approval gates, along with real-time notifications sent via Slack, email, and the in-app notification center, ensuring that every team member stays informed and engaged throughout the deployment process. This comprehensive approach not only streamlines operations but also fosters enhanced teamwork and productivity within organizations.

Maxeler's cutting-edge dataflow solutions seamlessly fit into operational data centers, allowing for straightforward programming and management. These high-performance systems are specifically crafted to work within production server settings, ensuring compatibility with common operating systems and management applications. Our robust management software oversees resource allocation, scheduling, and data transfer throughout the dataflow computing framework. Furthermore, Maxeler dataflow nodes operate with standard Linux distributions, such as Red Hat Enterprise versions 4 and 5, without the need for any alterations. Any application designed for acceleration can function on a Maxeler node as a conventional Linux executable. Developers can create new applications by integrating the dataflow library into their existing code and utilizing simple function interfaces to access its capabilities. The MaxCompiler tool offers comprehensive debugging support throughout the development process, featuring a high-speed simulator that allows for code validation prior to implementation. This ensures that developers can optimize their applications effectively while minimizing the risk of errors. Additionally, Maxeler’s commitment to innovation guarantees that users can take advantage of the latest advancements in dataflow technology.

Flyte is a robust platform designed for automating intricate, mission-critical data and machine learning workflows at scale. It simplifies the creation of concurrent, scalable, and maintainable workflows, making it an essential tool for data processing and machine learning applications. Companies like Lyft, Spotify, and Freenome have adopted Flyte for their production needs. At Lyft, Flyte has been a cornerstone for model training and data processes for more than four years, establishing itself as the go-to platform for various teams including pricing, locations, ETA, mapping, and autonomous vehicles. Notably, Flyte oversees more than 10,000 unique workflows at Lyft alone, culminating in over 1,000,000 executions each month, along with 20 million tasks and 40 million container instances. Its reliability has been proven in high-demand environments such as those at Lyft and Spotify, among others. As an entirely open-source initiative licensed under Apache 2.0 and backed by the Linux Foundation, it is governed by a committee representing multiple industries. Although YAML configurations can introduce complexity and potential errors in machine learning and data workflows, Flyte aims to alleviate these challenges effectively. This makes Flyte not only a powerful tool but also a user-friendly option for teams looking to streamline their data operations.

AutoLocalise streamlines the localization process for JavaScript applications by removing the need for translation files and tedious locale oversight; it utilizes a lightweight SDK compatible with frameworks like React, React Native (Expo), and Next.js. By simply installing and initializing a TranslationProvider, developers can wrap their app and tag text directly within components, allowing AutoLocalise’s AI-driven engine to provide instantaneous translations in over 100 languages without the hassle of using JSON or YAML files. The translations are dynamically delivered from a global edge network, enabling real-time content updates through an intuitive dashboard, where users can invite collaborators, modify translations instantly, and observe changes in their applications without having to redeploy. Additionally, automatic content change detection guarantees that any newly added or altered strings are recognized promptly, while centralized management of API keys and project settings allows for seamless control over multiple applications and environments. Scaling from a single language to hundreds can be done effortlessly, making it an ideal solution for developers looking to expand their app's reach without additional complexity. Overall, AutoLocalise redefines the localization landscape, ensuring efficiency and ease for developers everywhere.

Proofpoint stands out as a premier people-focused solution for Insider Threat Management (ITM), designed to safeguard against the potential loss of data and damage to reputation caused by insiders acting out of malicious intent, negligence, or ignorance. By analyzing activity and data transactions, Proofpoint enables security teams to pinpoint user risk factors, recognize insider-driven data breaches, and enhance the speed of their incident response. With insider threats accounting for 30% of all data breaches, the financial repercussions of these incidents have surged twofold over the past three years. Additionally, Proofpoint equips security teams with the tools needed to minimize the likelihood and impact of insider threats, streamline their response efforts, and boost the overall efficiency of security operations. We provide a comprehensive collection of resources, including reports and strategies, aimed at helping you effectively manage insider threat risks. Users can visualize and explore correlated data on user activities, interactions, and risks through unified timelines, making it easier to understand and address potential vulnerabilities. This holistic approach not only enhances security measures but also fosters a proactive stance against insider-related risks.