Business Software for C#

Reduce Mean Time to Detection (MTTD) and Mean Time to Recovery (MTTR) with comprehensive coverage achievable within minutes of deployment. Employ a complete DevSecOps toolchain that spans all your environments, ensuring the implementation and gathering of evidence as part of an ongoing security strategy. This solution is unified and de-duplicated across all orchestrated layers, allowing you to add thousands of checks through a single line of code, enhanced by AI capabilities. Designed with a strong focus on security, it effectively sidesteps prevalent security errors and vulnerabilities, while being adept at understanding contemporary technologies. Every feature is accessible through a REST API, making it easily integrable with CI/CD systems, and it operates in a lightweight and rapid manner. You have the option to self-host for total code governance and transparency, or to utilize a source-available binary exclusively within your own CI/CD pipeline. Opting for a source-available solution grants you complete control and transparency over your security measures. The initial setup is straightforward, necessitating no software installation, and it supports a wide variety of programming languages. This tool is capable of detecting thousands of code and infrastructure-related issues, with the count continually rising. Users can review detected issues, categorize them as false positives, and collaborate effectively on resolutions, fostering a more secure development environment. Continuous updates ensure that the tool remains aligned with emerging security threats and technology advancements.

McAnswers is an innovative AI solution tailored for developers, aimed at streamlining the coding experience. It enables users to swiftly identify and rectify coding mistakes while offering accurate recommendations for enhancing their code. Supporting a variety of programming languages, McAnswers AI serves as a versatile chatbot, functioning as a digital assistant that can assist with numerous programming tasks and challenges. Whether you're debugging or seeking optimization tips, this tool is here to elevate your coding efficiency.

The Mixtral 8x7B model is an advanced sparse mixture of experts (SMoE) system that boasts open weights and is released under the Apache 2.0 license. This model demonstrates superior performance compared to Llama 2 70B across various benchmarks while achieving inference speeds that are six times faster. Recognized as the leading open-weight model with a flexible licensing framework, Mixtral also excels in terms of cost-efficiency and performance. Notably, it competes with and often surpasses GPT-3.5 in numerous established benchmarks, highlighting its significance in the field. Its combination of accessibility, speed, and effectiveness makes it a compelling choice for developers seeking high-performing AI solutions.

Develop a conversational bot that can communicate, listen, comprehend, and adapt to user interactions using Azure Cognitive Services. Take advantage of the open-source SDKs and tools available to create, test, and deploy bots that engage users authentically, no matter their location. Construct secure and scalable solutions that seamlessly integrate with your current IT infrastructure. This will enable you to craft an AI-driven experience that enhances your brand while allowing you to maintain control over your data. The Bot Framework Composer serves as an open-source, visual platform that empowers developers and diverse teams to design and construct engaging conversational interactions. With Azure Bot Service, you can create advanced, intelligent bots and retain ownership over your data. You can start with a basic Q&A bot and progress to developing an elaborate virtual assistant. Leverage comprehensive open-source SDKs and tools to effortlessly link your bot to widely-used channels and devices, providing it with the capabilities to communicate, listen, and understand user needs through seamless integration with Azure Cognitive Services. This approach not only enhances user experience but also enables continuous improvement and learning based on user interactions.

Setting up webhooks often demands significantly more engineering effort, resources, and continuous maintenance than one might initially anticipate. Creating a secure, dependable, and scalable webhook service is both challenging and time-intensive. We have developed this service to allow you to concentrate on what truly matters: your business. It's important to recognize that customer endpoints can fail or become unresponsive more frequently than expected, necessitating automatic retries to guarantee successful delivery. Monitoring webhook deliverability to various endpoints is crucial, as is the ability to disable those that are failing and keep your customers informed. Additionally, webhooks introduce various security challenges, including SSRF, replay attacks, and issues with unauthenticated events. You will also need to develop a user interface that allows users to manage their endpoints, view logs, and receive ongoing reports. Providing an excellent developer experience is essential, which includes features for testing, inspecting, and replaying webhooks to ensure seamless integration and functionality. Ultimately, investing in these areas will lead to a more robust and user-friendly service.

Synadia offers a comprehensive, globally accessible service that operates across multiple clouds and geographic locations, fully managed for your convenience. This service encompasses everything you appreciate about NATS.io, enhanced with features suitable for enterprise needs. With Synadia Cloud, you can rely on them to manage all aspects of infrastructure, monitoring, and maintenance, allowing you to dedicate your time to developing outstanding distributed applications. You can easily structure NATS accounts into teams, as well as create and oversee user accounts and permissions. The platform enables you to implement access controls and effortlessly import and export subjects across accounts. Additionally, you can keep an eye on your NATS systems, utilizing default alert rules for typical problems while also having the freedom to establish custom alerts tailored to your specific application requirements. Each subscription plan provides a designated pool of resources for your NATS accounts, ensuring transparency with no unexpected charges or overages. Resource allocation is simplified with usage charts, which allow you to quickly identify where your resources are being utilized, leading to more efficient management of your distributed applications. In this way, Synadia empowers developers to focus on innovation rather than infrastructure management.

Execute code within a secure, resilient, and automatically scalable framework without the need to create or manage virtual machines. As the demand for function executions rises, the service dynamically provisions extra instances of your function to handle the increased load. All functions operate concurrently, and the runtime environment is distributed across three availability zones to maintain service continuity even if one zone experiences issues. You can set up and ready function instances to handle incoming requests efficiently, which helps to eliminate cold starts and allows for the rapid processing of workloads of any magnitude. Grant your functions access to your Virtual Private Cloud (VPC) to enhance communication with private resources, including database clusters, virtual machines, and Kubernetes nodes. Additionally, Serverless Functions monitors and logs details about function executions, providing insights into operational flow and performance metrics; you also have the option to specify logging methods within your function's code. Furthermore, you can initiate cloud functions in both synchronized mode and with delayed execution capabilities for greater flexibility. This approach allows for streamlined processes that can adapt to varying workloads efficiently.

We have incorporated Llama 3 into Meta AI, our intelligent assistant that enhances how individuals accomplish tasks, innovate, and engage with Meta AI. By utilizing Meta AI for coding and problem-solving, you can experience Llama 3's capabilities first-hand. Whether you are creating agents or other AI-driven applications, Llama 3, available in both 8B and 70B versions, will provide the necessary capabilities and flexibility to bring your ideas to fruition. With the launch of Llama 3, we have also revised our Responsible Use Guide (RUG) to offer extensive guidance on the ethical development of LLMs. Our system-focused strategy encompasses enhancements to our trust and safety mechanisms, including Llama Guard 2, which is designed to align with the newly introduced taxonomy from MLCommons, broadening its scope to cover a wider array of safety categories, alongside code shield and Cybersec Eval 2. Additionally, these advancements aim to ensure a safer and more responsible use of AI technologies in various applications.

This embeddable .NET library is designed for executing workflows within .NET applications and comes equipped with an integrated HTML5 graphical workflow designer. This designer simplifies the process of creating interactive workflows, eliminating the necessity for programmatic drafting, regardless of the complexity involved. Serving as a foundational solution for business process management (BPM), the Workflow Engine allows for the automation of workflow design through user-friendly low-code visual builders. Built on the .NET framework and utilizing JavaScript libraries, it streamlines workflow processing and ensures seamless integration by offering a graphic interface for designing process flow diagrams. Additionally, this software component enhances the management, execution, and visualization of workflow processes, making it versatile for various applications. The integration capabilities extend to systems built on different technologies or databases, which should generally present no challenges. With the Workflow Engine, users have access to all essential components needed to create workflows of any intricacy, thereby empowering organizations to optimize their operations effectively.

We are excited to unveil Codestral, our inaugural code generation model. This open-weight generative AI system is specifically crafted for tasks related to code generation, enabling developers to seamlessly write and engage with code via a unified instruction and completion API endpoint. As it becomes proficient in both programming languages and English, Codestral is poised to facilitate the creation of sophisticated AI applications tailored for software developers. With a training foundation that encompasses a wide array of over 80 programming languages—ranging from widely-used options like Python, Java, C, C++, JavaScript, and Bash to more niche languages such as Swift and Fortran—Codestral ensures a versatile support system for developers tackling various coding challenges and projects. Its extensive language capabilities empower developers to confidently navigate different coding environments, making Codestral an invaluable asset in the programming landscape.

An AI-driven code scanning tool aims to adopt a proactive, shift-left approach for safeguarding sensitive information and ensuring compliance with privacy regulations. The rapid evolution of product development often surpasses the capacity of privacy teams, necessitating frequent updates to outdated data maps, which can significantly burden their workload. With HoundDog.ai’s advanced code scanner, vulnerabilities that traditional SAST scanners might miss can be continuously identified, especially those exposing sensitive data in plaintext through various channels like logs, files, tokens, cookies, or external systems. It provides critical insights and remediation techniques, such as the removal of sensitive data, implementation of masking or obfuscation, or substitution of PII with UUIDs. Users receive timely alerts when new data elements are added, categorized by their sensitivity levels, helping to prevent unauthorized product changes from being released, thus mitigating potential privacy breaches. By automating these processes, the scanner effectively reduces the reliance on manual methods, which are often riddled with errors. This innovative solution not only enhances security but also streamlines workflow for privacy teams, allowing them to focus on more strategic initiatives.

Kontra Hands-On Labs and e-Learning Courses provide a practical and scalable way to embed secure coding skills into development teams. The training combines 50+ short-form video lessons with over 300 interactive vulnerability labs that simulate real-world security failures. Developers don’t just hear about issues—they actively exploit vulnerabilities like Log4Shell and learn to fix them using code that matches their actual stacks. Covering 25+ technologies, each lab delivers a fast, focused experience with most exercises completed in under 10 minutes. This keeps developers engaged without disrupting their workflow. Completion rates are over 3x higher than traditional training models, helping AppSec leaders embed secure practices earlier in the SDLC. Training is role-based and aligned with major compliance frameworks including PCI-DSS, ISO 27001, and NIST. Optional ISC2 co-branded certifications are available, providing a path for developers to validate their secure coding competencies. Content is SCORM-compliant and can be delivered flexibly—either hosted or deployed directly into your own LMS. This ensures easy adoption whether you’re centralizing training or enabling business units to self-manage. L&D and AppSec leaders gain immediate visibility into training status with reporting on completions, coverage by framework, and readiness across teams. This supports both audit prep and internal program performance tracking. With developer-first content, flexible deployment, and measurable outcomes, Kontra + Courses helps security and engineering teams build software that’s secure by design—without slowing down delivery.

Ensure your team remains secure and current with seamless automatic updates for dependencies, thorough license checks, and scanning for security vulnerabilities. We meticulously review library changelogs and release notes, scrutinize your codebase, and handle dependency updates, even addressing any breaking changes that may arise. Our robust tools cater to effective dependency management, accommodating teams of any size, from as small as two to as large as 200. With all your dependencies visible in a single location, there's no need for tedious searches through various repositories. Prevent legal complications by verifying that your dependencies are properly licensed. Additionally, receive timely alerts whenever a dependency poses a security risk. You can choose to update your code only if the changes impact your project. DepsHub simplifies the process of monitoring and updating dependencies, ultimately saving you valuable time. We proudly support a diverse array of programming languages and frameworks, allowing you to work with the ones you prefer while getting started in just a few minutes. Furthermore, you can integrate your preferred tools, create tickets, and stay informed about new issues, enhancing your overall workflow and productivity.

Entity Framework (EF) Core is a versatile, lightweight, and open-source version of the widely used Entity Framework data access technology that operates across different platforms. It empowers .NET developers to interact with databases through .NET objects, significantly reducing the amount of data-access code that would typically need to be written. In EF Core, data interaction occurs through a model, which consists of entity classes and a context object that acts as a connection to the database. This context object facilitates both querying and data manipulation. Developers can generate a model directly from an existing database or manually create one to correspond with the database schema. After establishing a model, EF migrations can be employed to build a database from it, allowing for the database to evolve in tandem with any changes made to the model. Furthermore, instances of entity classes can be retrieved from the database using Language Integrated Query (LINQ), and operations such as creating, deleting, and modifying records in the database are accomplished through these instances, thus streamlining the data management process. Overall, EF Core simplifies database interactions and enhances the efficiency of data-driven applications.

Mistral Large stands as the premier language model from Mistral AI, engineered for sophisticated text generation and intricate multilingual reasoning tasks such as text comprehension, transformation, and programming code development. This model encompasses support for languages like English, French, Spanish, German, and Italian, which allows it to grasp grammar intricacies and cultural nuances effectively. With an impressive context window of 32,000 tokens, Mistral Large can retain and reference information from lengthy documents with accuracy. Its abilities in precise instruction adherence and native function-calling enhance the development of applications and the modernization of tech stacks. Available on Mistral's platform, Azure AI Studio, and Azure Machine Learning, it also offers the option for self-deployment, catering to sensitive use cases. Benchmarks reveal that Mistral Large performs exceptionally well, securing its position as the second-best model globally that is accessible via an API, just behind GPT-4, illustrating its competitive edge in the AI landscape. Such capabilities make it an invaluable tool for developers seeking to leverage advanced AI technology.

Qwen2 represents a collection of extensive language models crafted by the Qwen team at Alibaba Cloud. This series encompasses a variety of models, including base and instruction-tuned versions, with parameters varying from 0.5 billion to an impressive 72 billion, showcasing both dense configurations and a Mixture-of-Experts approach. The Qwen2 series aims to outperform many earlier open-weight models, including its predecessor Qwen1.5, while also striving to hold its own against proprietary models across numerous benchmarks in areas such as language comprehension, generation, multilingual functionality, programming, mathematics, and logical reasoning. Furthermore, this innovative series is poised to make a significant impact in the field of artificial intelligence, offering enhanced capabilities for a diverse range of applications.

Semantic Kernel is an open-source development toolkit that facilitates the creation of AI agents and the integration of cutting-edge AI models into applications written in C#, Python, or Java. This efficient middleware accelerates the deployment of robust enterprise solutions. Companies like Microsoft and other Fortune 500 firms are taking advantage of Semantic Kernel's flexibility, modularity, and observability. With built-in security features such as telemetry support, hooks, and filters, developers can confidently provide responsible AI solutions at scale. The support for versions 1.0 and above across C#, Python, and Java ensures reliability and a commitment to maintaining non-breaking changes. Existing chat-based APIs can be effortlessly enhanced to include additional modalities such as voice and video, making the toolkit highly adaptable. Semantic Kernel is crafted to be future-proof, ensuring seamless integration with the latest AI models as technology evolves, thus maintaining its relevance in the rapidly changing landscape of artificial intelligence. This forward-thinking design empowers developers to innovate without fear of obsolescence.

Qodana’s static code analysis empowers development teams to adhere to established quality benchmarks, ensuring they produce code that is not only readable and maintainable but also secure. Developed by JetBrains, this tool has been refined through over two decades of experience in code analysis, enriched by input from millions of users across the community. By leveraging the insights derived from JetBrains IDEs, Qodana extends their intelligence into the continuous integration (CI) environment. Its analysis is precise yet unobtrusive, adeptly recognizing the intricacies of your codebase. The integration with commonly used tools, including JetBrains IDEs, facilitates seamless interaction with Qodana’s findings in the environment that developers prefer. Additionally, Qodana goes beyond merely identifying issues; it actively recommends automatic solutions to enhance code quality. To ensure budget-friendly usage, Qodana calculates licenses based on active contributors, avoiding unexpected costs associated with project growth, as it does not factor in lines of code. Furthermore, it is available at no cost for open-source initiatives, encouraging innovation and collaboration within the developer community. This commitment to fostering quality and accessibility makes Qodana a valuable asset for any coding team.

Looking beyond mere lines of code or the frequency of commits, teams that focus on measuring developer productivity have a higher likelihood of meeting their deadlines. The average company listed on the S&P 500 faces considerable financial setbacks for each employee due to ineffective productivity levels. A significant portion of engineering leaders—over one-third—struggle with accurately assessing developer efficiency. Implementing a standardized evaluation framework can yield precise insights into shipping velocity, regardless of the variety within your tech stack. With access to a tailored dashboard, you can monitor the shipping velocity of your engineering teams across various departments. Our approach standardizes the code evaluation process across multiple programming languages, ensuring consistency and fairness. Additionally, we offer an engineer performance index that allows for performance comparisons against industry peers with similar characteristics. This understanding enables you to gain insights into how much time your engineers dedicate to resolving bugs or managing unexpected tasks, ultimately enhancing overall productivity and efficiency.

Aider is an AI pair programming assistant designed to work seamlessly from the terminal, enabling developers to collaborate with advanced language models while coding. It allows users to start fresh projects or enhance existing repositories with AI-generated improvements that respect the structure of their codebase. By mapping the entire project, Aider maintains strong contextual awareness, even across large and multi-file applications. The tool supports more than 100 programming languages, covering most modern and legacy development stacks. Aider integrates tightly with Git, automatically creating commits that are easy to review, track, or roll back. Developers can interact with Aider from within their IDE or editor by simply adding comments to their code. It also supports images, web pages, and reference documents to provide richer context during development. Voice-to-code functionality enables developers to request features or fixes verbally. Built-in linting and testing ensure code quality after every AI-driven change. Aider can also work with browser-based LLMs by streamlining copy-and-paste workflows when APIs are unavailable.

The latest iteration of the open-source AI model, which can be fine-tuned and deployed in various environments, is now offered in multiple versions, including 1B, 3B, 11B, and 90B, alongside the option to continue utilizing Llama 3.1. Llama 3.2 comprises a series of large language models (LLMs) that come pretrained and fine-tuned in 1B and 3B configurations for multilingual text only, while the 11B and 90B models accommodate both text and image inputs, producing text outputs. With this new release, you can create highly effective and efficient applications tailored to your needs. For on-device applications, such as summarizing phone discussions or accessing calendar tools, the 1B or 3B models are ideal choices. Meanwhile, the 11B or 90B models excel in image-related tasks, enabling you to transform existing images or extract additional information from images of your environment. Overall, this diverse range of models allows developers to explore innovative use cases across various domains.

Receive immediate notifications for errors and exceptions without needing to probe your users with extra queries. Muscula is an innovative error-logging tool that simplifies the process of gathering and examining errors within your website or application. Stop wasting valuable time sifting through server logs whenever an issue arises. Muscula offers a variety of plans, including free, business, and self-hosted options, all equipped with diverse features. You won’t need to provide a credit card to access the free plan, and you can begin using it right away, with the flexibility to upgrade whenever you choose. Logs play a crucial role in diagnosing both infrastructure and application errors. While some software may excel in select areas, Muscula stands out as a robust solution with a comprehensive feature set. It provides AI-powered explanations, leveraging technology from OpenAI, known for its renowned ChatGPT application. All errors are directed to your centralized dashboard, complete with efficient search and sorting functionalities. Say goodbye to the tedious task of scanning log lines for individual errors; instead, enhance your client satisfaction by resolving issues swiftly and effectively. With Muscula, you can streamline your error management process and ensure a smoother user experience.

Perst is an open source, dual-licensed object-oriented embedded database management system (ODBMS) created by McObject. It comes in two versions: one designed as an all-Java embedded database and another tailored for C# applications within the Microsoft .NET Framework. This database system enables developers to efficiently store, sort, and retrieve objects, ensuring high speed while maintaining low memory and storage requirements. By utilizing the object-oriented features of both Java and C#, Perst showcases a significant performance edge in benchmarks like TestIndex and PolePosition when compared to other embedded database solutions in Java and .NET. One of its standout capabilities is its ability to store data directly in Java and .NET objects, which eliminates the need for translation typical in relational and object-relational databases, thereby enhancing run-time performance. With a compact core comprised of only five thousand lines of code, Perst demands minimal system resources, making it an attractive option for resource-constrained environments. This efficiency not only benefits developers but also contributes to the overall responsiveness of applications utilizing the database.

Base64.ai stands at the forefront of no-code AI solutions, proficiently processing documents, images, and videos. It serves as a comprehensive tool for managing all types of documents, including identification cards, passports, invoices, checks, and various forms. With over 400 no-code integrations available, users can connect to third-party systems in less than an hour. The platform allows for the addition of new document types, integrations, and customizable business rules, empowering users to tailor the AI to their specific requirements. For the majority of document types, the processes of OCR, data extraction, and integration are completed in under three seconds, boasting an impressive extraction accuracy of 99%. As Base64.ai engages with more documents, its efficiency continues to enhance. Users can access Base64.ai through APIs, RPA systems, scanners, and various web and mobile applications within our extensive partner network. Additionally, our document review team operates around the clock to ensure that results are verified for 100% accuracy in data extraction. The platform also provides features to identify and eliminate sensitive information, including names, dates, and document numbers. Proudly collaborating with top organizations in the automation sector, Base64.ai remains committed to delivering exceptional service and innovation in document management. As a result, businesses can trust Base64.ai to streamline their operations while maintaining data integrity.

Our cutting-edge in-memory technology, alongside our application server, allows you to create exceptionally fast enterprise software without the need for custom tools or unfamiliar syntax. Starcounter applications can deliver performance improvements ranging from 50 to 1000 times while maintaining simplicity and ease of use. You can develop these applications using standard C#, LINQ, and SQL, with ACID transactions also implemented in familiar C# code. The platform provides full support for Visual Studio, including features like IntelliSense, a debugger, and a performance profiler—everything you love about development, but without unnecessary complications. By employing standard C# syntax and the MVVM pattern, you can harness our ACID in-memory technology alongside a lightweight client UI to achieve remarkable performance. Starcounter's technology starts delivering business value right from the outset, utilizing proven solutions that are already handling millions of transactions for high-demand clients. This integration of the ACID in-memory database and an application server into a single platform offers unmatched performance, simplicity, and affordability. Ultimately, Starcounter empowers developers to build robust applications that not only meet but exceed modern business demands.