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Functional Testing Tools
Functional testing tools are software platforms designed to verify that a system or application performs as expected according to its functional requirements. These tools automate the process of testing individual features and functionalities of an application to ensure they work correctly. Functional testing tools typically support a variety of testing types, including unit testing, integration testing, and user acceptance testing (UAT). They allow testers to simulate user interactions with the application, execute test cases, and identify bugs or issues in the functional behavior of the software. By automating repetitive testing tasks and improving accuracy, functional testing tools help accelerate the software development lifecycle and ensure high-quality releases.
Function as a Service (FaaS) Providers
Function as a Service (FaaS) providers are cloud computing services that allow developers to execute small units of code, or functions, in response to events without managing the underlying infrastructure. These providers offer a serverless architecture where the scaling, monitoring, and management of infrastructure are handled automatically, allowing developers to focus on writing code. FaaS platforms typically charge based on the number of executions and the duration of the function, making it a cost-efficient option for event-driven applications, microservices, and real-time data processing.
Shopping Cart Software
Shopping cart software allows businesses and online merchants to implement shopping tools on their eCommerce sites to sell their products and improve customer experience.
Forestry Software
Forestry software provides organizations within the forest industry to optimize the management of their tasks, operations, schedules, inventory and equipment.
Artificial Intelligence Software
Artificial Intelligence (AI) software is computer technology designed to simulate human intelligence. It can be used to perform tasks that require cognitive abilities, such as problem-solving, data analysis, visual perception and language translation. AI applications range from voice recognition and virtual assistants to autonomous vehicles and medical diagnostics.
Machine Learning Software
Machine learning software enables developers and data scientists to build, train, and deploy models that can learn from data and make predictions or decisions without being explicitly programmed. These tools provide frameworks and algorithms for tasks such as classification, regression, clustering, and natural language processing. They often come with features like data preprocessing, model evaluation, and hyperparameter tuning, which help optimize the performance of machine learning models. With the ability to analyze large datasets and uncover patterns, machine learning software is widely used in industries like healthcare, finance, marketing, and autonomous systems. Overall, this software empowers organizations to leverage data for smarter decision-making and automation.
Serverless Platforms
Serverless platforms are cloud computing services that allow developers to build and deploy applications without managing the underlying infrastructure, such as servers or virtual machines. These platforms automatically handle the scaling, provisioning, and maintenance of resources, allowing developers to focus on writing code and implementing business logic. Serverless platforms typically provide a pay-as-you-go pricing model, where users only pay for the actual resources used during execution rather than for idle time. Features of serverless platforms include automatic scaling, event-driven architecture, and support for various programming languages and services. Popular serverless platforms are commonly used for web applications, microservices, APIs, and data processing.
Dance Studio Software
Dance studio software is software that helps dance studios manage their daily operations and improve overall efficiency. These platforms typically include features for class scheduling, student enrollment, payment processing, attendance tracking, and instructor management. Dance studio software often integrates tools for communication with students and parents, such as reminders for upcoming classes or events, and may offer features for managing recital planning, costume tracking, and registration for competitions. By streamlining administrative tasks, dance studio software allows instructors to focus on teaching while improving the customer experience for students and their families.
Web Application Firewalls (WAF)
Web Application Firewalls (WAFs) are security solutions that protect web applications by filtering and monitoring HTTP traffic between the application and the internet. They detect and block threats such as SQL injections, cross-site scripting (XSS), and other common attacks targeting application vulnerabilities. WAFs analyze incoming requests in real time, applying customizable security rules to distinguish between legitimate and potentially malicious traffic. Many WAFs are cloud-based, enabling flexible and scalable protection without impacting application performance. By acting as a shield between web applications and attackers, WAFs help ensure data security, regulatory compliance, and uninterrupted user access.
Data Preparation Software
Data preparation software helps businesses and organizations clean, transform, and organize raw data into a format suitable for analysis and reporting. These tools automate the data wrangling process, which typically involves tasks such as removing duplicates, correcting errors, handling missing values, and merging datasets. Data preparation software often includes features for data profiling, transformation, and enrichment, enabling data teams to enhance data quality and consistency. By streamlining these processes, data preparation software accelerates the time-to-insight and ensures that business intelligence (BI) and analytics applications use high-quality, reliable data.
Order-to-Cash Software
Order-to-cash (O2C) software enables companies to handle all processes related to sales including receiving an order, receiving payment, onboarding the customer, running a credit risk assessment, and more. Order-to-cash software is also known as quote-to-cash or lead-to-cash software.
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  • 1
    Flyte

    Flyte

    Union.ai

    The workflow automation platform for complex, mission-critical data and ML processes at scale. Flyte makes it easy to create concurrent, scalable, and maintainable workflows for machine learning and data processing. Flyte is used in production at Lyft, Spotify, Freenome, and others. At Lyft, Flyte has been serving production model training and data processing for over four years, becoming the de-facto platform for teams like pricing, locations, ETA, mapping, autonomous, and more. In fact, Flyte...
    Starting Price: Free
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  • 2
    XpertRule

    XpertRule

    XpertRule Software

    We are a software business, founded by AI and engineering pioneers, that creates exceptional technology, to solve the most complex process challenges. We want to help create more sustainable businesses, with improved performance against all the metrics that matter - cost, quality, delivery and human experience. By deploying our advanced decision intelligence products - viabl.ai and XpertFactory - we allow organisations to harness the power of their two most valuable assets – the expertise...
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  • 3
    Sama

    Sama

    Sama

    We offer the highest quality SLA (>95%), even on the most complex workflows. Our team assists with anything from implementing a robust quality rubric to raising edge cases. As an ethical AI company, we have provided economic opportunities for over 52,000 people from underserved and marginalized communities. ML Assisted annotation created up to 3-4x efficiency improvement for a single class annotation. We quickly adapt to ramp-ups, focus shifts, and edge cases. ISO certified delivery centers...
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  • 4
    MLReef

    MLReef

    MLReef

    ... already well-known and established git repositories to create explorable, interoperable, and versioned AI modules. AI Modules created by your data scientists become drag-and-drop elements. These are adjustable by parameters, versioned, interoperable, and explorable within your entire organization. Data handling often requires expert knowledge that a single data scientist often lacks. MLReef enables your field experts to relieve your data processing task, reducing complexities.
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  • 5
    Ametnes Cloud
    Introducing Ametnes: Streamlined Data Application Deployment and Management Experience the future of data application deployment with Ametnes. Our cutting-edge solution revolutionizes the way you handle data applications in your private environment. Say goodbye to the complexities and security concerns of manual deployment. Ametnes addresses these challenges head-on by automating the entire process, ensuring a seamless and secure experience for our valued customers. With our intuitive...
    1 Rating
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  • 6
    scikit-learn

    scikit-learn

    scikit-learn

    ... learning engineers, and researchers. The library is organized into a consistent and flexible framework, where various components can be combined and customized to suit specific needs. This modularity makes it easy for users to build complex pipelines, automate repetitive tasks, and integrate scikit-learn into larger machine-learning workflows. Additionally, the library’s emphasis on interoperability ensures that it works seamlessly with other Python libraries, facilitating smooth data processing.
    Starting Price: Free
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  • 7
    Indexima Data Hub
    Reshape your perception of time in data analytics. Instantly access your business’ data in no time and work directly on your dashboard without going back and forth with the IT team. Meet Indexima DataHub, a new space-time where operational and functional users gain instant access to their data, in no time. With a combination of its unique indexing engine and machine learning, Indexima allows businesses to access all their data to simplify and speed up analytics. Robust and scalable...
    Starting Price: $3,290 per month
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  • 8
    Ludwig

    Ludwig

    Uber AI

    ...Speed), parameter efficient fine-tuning (PEFT), 4-bit quantization (QLoRA), and larger-than-memory datasets. Expert level control: retain full control of your models down to the activation functions. Support for hyperparameter optimization, explainability, and rich metric visualizations. Modular and extensible: experiment with different model architectures, tasks, features, and modalities with just a few parameter changes in the config. Think building blocks for deep learning.
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