Alternatives to Superagent

Parasoft's mission is to provide automated testing solutions and expertise that empower organizations to expedite delivery of safe and reliable software. A powerful unified C and C++ test automation solution for static analysis, unit testing and structural code coverage, Parasoft C/C++test helps satisfy compliance with industry functional safety and security requirements for embedded software systems.

Agent Builder is a component of OpenAI’s suite designed for creating agentic applications, which are systems that leverage large language models to autonomously carry out multi-step tasks while incorporating governance, tool integration, memory, orchestration, and observability features. This platform provides a flexible collection of components—such as models, tools, memory/state, guardrails, and workflow orchestration—which developers can piece together to create agents that determine the appropriate moments to utilize a tool, take action, or pause and transfer control. Additionally, OpenAI has introduced a new Responses API that merges chat functions with integrated tool usage, alongside an Agents SDK available in Python and JS/TS that simplifies the control loop, enforces guardrails (validations on inputs and outputs), manages agent handoffs, oversees session management, and tracks agent activities. Furthermore, agents can be enhanced with various built-in tools, including web search, file search, or computer functionalities, as well as custom function-calling tools, allowing for a diverse range of operational capabilities. Overall, this comprehensive ecosystem empowers developers to craft sophisticated applications that can adapt and respond to user needs with remarkable efficiency.

LangProtect serves as a cutting-edge security and governance platform specifically designed for AI, offering robust protection against issues such as prompt injections, jailbreaks, data leaks, and the generation of unsafe or non-compliant outputs in LLM and Generative AI applications. Tailored for production-grade GenAI environments, this platform implements real-time controls at the execution level of AI, meticulously examining prompts, model outputs, and function calls as they occur, enabling teams to intercept high-risk actions before they can affect end users or compromise sensitive information. By doing so, LangProtect ensures that potential threats are neutralized promptly, preserving the integrity of data and user interactions. Furthermore, LangProtect seamlessly integrates with existing LLM infrastructures through an API-first design that maintains low latency, accommodating various deployment models including cloud, hybrid, and on-premise solutions to meet the security and data residency requirements of enterprises. It is also equipped to safeguard contemporary architectures like RAG pipelines and agentic workflows, providing policy-driven enforcement, continuous monitoring, and governance that is ready for audits. This comprehensive approach ensures that organizations can confidently leverage AI technologies while minimizing risks associated with their deployment.

ZenGuard AI serves as a dedicated security platform aimed at safeguarding AI-powered customer service agents from various potential threats, thereby ensuring their safe and efficient operation. With contributions from specialists associated with top technology firms like Google, Meta, and Amazon, ZenGuard offers rapid security measures that address the risks linked to AI agents based on large language models. It effectively protects these AI systems against prompt injection attacks by identifying and neutralizing any attempts at manipulation, which is crucial for maintaining the integrity of LLM operations. The platform also focuses on detecting and managing sensitive data to avert data breaches while ensuring adherence to privacy laws. Furthermore, it enforces content regulations by preventing AI agents from engaging in discussions on restricted topics, which helps uphold brand reputation and user security. Additionally, ZenGuard features an intuitive interface for configuring policies, allowing for immediate adjustments to security measures as needed. This adaptability is essential in a constantly evolving digital landscape where threats to AI systems can emerge unexpectedly.

Alice is an enterprise-grade AI security and trust platform designed to protect applications, agents, and foundation models from adversarial threats. Formerly known as ActiveFence, the company leverages its proprietary Rabbit Hole intelligence engine, built on billions of real-world toxic and abusive data samples, to deliver unmatched safety coverage. Alice protects more than 50% of global online experiences, monitoring over 1 billion daily AI-human interactions across 120+ languages. Its WonderSuite platform provides comprehensive safeguards, including pre-launch stress testing with WonderBuild, dynamic runtime guardrails through WonderFence, and continuous automated red-teaming via WonderCheck. These solutions help organizations defend against prompt injection, jailbreaks, model exploitation, and policy misalignment risks. By aligning defenses with regulatory and compliance requirements, Alice supports responsible AI governance and enterprise risk management. Trusted by leading tech companies and model labs, Alice empowers businesses to deploy GenAI systems securely and scale innovation without fear.

Confident AI has developed an open-source tool named DeepEval, designed to help engineers assess or "unit test" the outputs of their LLM applications. Additionally, Confident AI's commercial service facilitates the logging and sharing of evaluation results within organizations, consolidates datasets utilized for assessments, assists in troubleshooting unsatisfactory evaluation findings, and supports the execution of evaluations in a production environment throughout the lifespan of LLM applications. Moreover, we provide over ten predefined metrics for engineers to easily implement and utilize. This comprehensive approach ensures that organizations can maintain high standards in the performance of their LLM applications.

MAIHEM develops AI agents designed to consistently evaluate your AI applications. Our platform allows you to fully automate the quality assurance of your AI, guaranteeing optimal performance and safety from the initial stages of development through to deployment. Say goodbye to tedious hours spent on manual testing and the uncertainty of randomly checking for vulnerabilities in your AI models. With MAIHEM, you can automate your AI quality assurance processes, ensuring a thorough analysis of thousands of edge cases. You can generate numerous realistic personas to engage with your conversational AI, allowing for a broad scope of interaction. Additionally, the platform automatically assesses entire dialogues using a customizable array of performance indicators and risk metrics. Utilize the simulation data generated to make precise enhancements to your conversational AI’s capabilities. Regardless of the type of conversational AI you are using, MAIHEM is equipped to help elevate its performance. Furthermore, our solution allows for easy integration of AI quality assurance into your development workflow with minimal coding required. The user-friendly web application provides intuitive dashboards, enabling comprehensive AI quality assurance with just a few clicks, streamlining the entire process. Ultimately, MAIHEM empowers developers to focus on innovation while maintaining the highest standards of AI quality assurance.

Cekura offers a comprehensive testing and monitoring solution for voice AI agents to ensure seamless, high-quality conversational experiences. Users can simulate diverse workflows, personas, and real audio scenarios to rigorously evaluate agent responses against custom metrics. The platform supports parallel execution of test calls, speeding up evaluations and identifying issues before deployment. Real-time monitoring delivers detailed logs, trend analysis, and instant alerts for critical performance issues, enabling proactive maintenance. Cekura’s easy-to-use dashboard facilitates data-driven decision-making and continuous optimization of AI agents. With trusted clients across multiple sectors, Cekura enhances voice agent reliability and user satisfaction. The solution is fully compliant with industry standards such as SOC2 Type 2 and HIPAA, making it suitable for sensitive and regulated environments. Cekura is a critical tool for teams aiming to deploy voice AI agents confidently and efficiently.

Amazon Bedrock Guardrails is a flexible safety system aimed at improving the compliance and security of generative AI applications developed on the Amazon Bedrock platform. This system allows developers to set up tailored controls for safety, privacy, and accuracy across a range of foundation models, which encompasses models hosted on Amazon Bedrock, as well as those that have been fine-tuned or are self-hosted. By implementing Guardrails, developers can uniformly apply responsible AI practices by assessing user inputs and model outputs according to established policies. These policies encompass various measures, such as content filters to block harmful text and images, restrictions on specific topics, word filters aimed at excluding inappropriate terms, and sensitive information filters that help in redacting personally identifiable information. Furthermore, Guardrails include contextual grounding checks designed to identify and manage hallucinations in the responses generated by models, ensuring a more reliable interaction with AI systems. Overall, the implementation of these safeguards plays a crucial role in fostering trust and responsibility in AI development.

QualGent is an innovative mobile application quality assurance platform that harnesses the power of AI to automate comprehensive testing for both iOS and Android apps. By utilizing intelligent agents that replicate the actions of human testers, it eliminates reliance on brittle scripted tests and manual quality assurance, thereby allowing development teams to identify bugs more effectively, enhance their confidence in releases, and accelerate their shipping process without the need to increase their QA workforce. The platform's AI capabilities facilitate the automatic generation of thorough test plans by integrating with various resources such as code repositories, product requirement documents, Figma designs, or simply by interpreting plain-English instructions on what to test. It continuously executes these tests around the clock on real devices and emulators, providing video recordings, logs, and detailed reports that encompass multi-lingual and cross-platform support. Furthermore, QualGent adeptly manages dynamic UI changes through its self-healing features, which substantially lower maintenance efforts. Additionally, the platform seamlessly fits into continuous integration and continuous delivery (CI/CD) pipelines along with issue tracking tools like GitHub, Slack, and Linear, allowing tests to be conducted with each code commit and delivering actionable insights without delay. This integration streamlines the development process and supports teams in maintaining high-quality standards throughout their project lifecycle.

GLM-4.7 Flash serves as a streamlined version of Z.ai's premier large language model, GLM-4.7, which excels in advanced coding, logical reasoning, and executing multi-step tasks with exceptional agentic capabilities and an extensive context window. This model, rooted in a mixture of experts (MoE) architecture, is fine-tuned for efficient inference, striking a balance between high performance and optimized resource utilization, thus making it suitable for deployment on local systems that require only moderate memory while still showcasing advanced reasoning, programming, and agent-like task handling. Building upon the advancements of its predecessor, GLM-4.7 brings forth enhanced capabilities in programming, reliable multi-step reasoning, context retention throughout interactions, and superior workflows for tool usage, while also accommodating lengthy context inputs, with support for up to approximately 200,000 tokens. The Flash variant successfully maintains many of these features within a more compact design, achieving competitive results on benchmarks for coding and reasoning tasks among similarly-sized models. Ultimately, this makes GLM-4.7 Flash an appealing choice for users seeking powerful language processing capabilities without the need for extensive computational resources.

GitAuto is an AI-driven coding assistant that seamlessly connects with GitHub (and optionally Jira) to assess backlog tickets or issues, evaluate your repository's structure and code, and autonomously create and review pull requests, usually completing this process in around three minutes per ticket. It is capable of managing bug fixes, implementing feature requests, and enhancing test coverage. You can activate it through specific issue labels or selections on a dashboard, allowing it to write code or unit tests, initiate a pull request, execute GitHub Actions, and continuously rectify any failing tests until they succeed. Supporting ten programming languages, such as Python, Go, Rust, and Java, GitAuto is free for basic use, with paid plans available for those requiring a greater volume of pull requests and additional enterprise functionalities. Adhering to a strict zero data-retention policy, it processes your code through OpenAI without retaining it. Built to speed up delivery by allowing teams to address technical debt and backlogs without the need for extensive engineering resources, GitAuto functions as an AI backend engineer that drafts, tests, and refines code, thereby significantly enhancing development efficiency. This innovative tool not only streamlines workflows but also empowers teams to focus on more strategic tasks.

Rapid Global's AI Safety Software serves as a cutting-edge computer vision platform aimed at improving workplace safety through the real-time identification of unsafe behaviors and hazardous situations. It is designed to be compatible with a wide range of IP cameras, allowing for effortless integration into current surveillance frameworks, which facilitates quick deployment and ensures that data is processed securely on-site. Users have the ability to customize their monitoring settings by choosing specific objects, areas, and time intervals, in addition to configuring customized alarm notifications to immediately flag unsafe actions as they happen. The platform is adept at recognizing when personal protective equipment is not being worn, tracking near misses between forklifts and pedestrians, and detecting unauthorized activities in restricted zones, such as individuals standing on conveyor belts or straying from designated walkways. These functionalities empower organizations to take a proactive approach in preventing incidents, thereby significantly enhancing overall safety outcomes in the workplace. Furthermore, the ability to adapt the system to evolving safety needs allows companies to maintain compliance with industry regulations and improve their safety culture continuously.

ZeroStep harnesses the capabilities of GPT-3.5 and GPT-4 to streamline Playwright testing, making it more adaptable to changes. Rather than relying on CSS selectors or XPath locators, ZeroStep's AI assistant interprets your plain-text instructions to decide on actions at runtime. This tool integrates seamlessly with Playwright, allowing you to weave AI into as many or as few tests as desired without disrupting your existing development processes. You can script intricate interactions and assertions simply by using plain-text commands. By leveraging the strengths of Playwright while sidestepping typical E2E testing challenges, ZeroStep eliminates the need for selectors altogether. The AI assistant continually assesses what actions should be executed in real time. Build your tests efficiently by articulating actions and assertions in straightforward text. If you can convey your testing requirements, automation becomes achievable. Additionally, since the tests remain independent of the application's implementation specifics, they lend themselves well to a Test-Driven Development (TDD) methodology for crafting E2E tests. Ultimately, ZeroStep revolutionizes the testing landscape by making it more intuitive and less error-prone.

Organizations face the ongoing challenge of keeping pace with and leading in digital transformation efforts. To achieve this, they require solutions that integrate intelligence into their workflows, particularly in areas like document control and print management, which ultimately drive business success, reduce expenses, and positively influence profitability. Tungsten Output Manager provides a robust governance framework for document control and print management, ensuring organizations can operate efficiently. Its advanced security features enhance document protection, reduce inefficiencies, and address compliance challenges effectively. With its top-tier print and document control functionalities, Tungsten Output Manager streamlines processes through intelligent redaction and efficient re-routing, thereby boosting workforce productivity. Additionally, it safeguards printed materials and prevents the unauthorized dissemination of sensitive data, reinforcing an organization’s commitment to security and efficiency. By implementing such comprehensive solutions, organizations can not only enhance their operational capabilities but also gain a significant competitive advantage in the marketplace.

TestMu AI, previously known as LambdaTest, is a comprehensive AI-driven Quality Engineering platform that equips teams with the tools needed to optimize testing processes and accelerate deployment. Designed to handle large-scale operations, it provides a complete suite of AI agents that assist in planning, authoring, executing, and analyzing software quality. With its AI-first approach, the platform supports the testing of web, mobile, and enterprise applications across various real devices, browsers, and tailored real-world scenarios, ensuring versatility and efficiency in quality assurance. This innovative solution not only enhances productivity but also drives continuous improvement in software delivery.

Promptfoo proactively identifies and mitigates significant risks associated with large language models before they reach production. The founders boast a wealth of experience in deploying and scaling AI solutions for over 100 million users, utilizing automated red-teaming and rigorous testing to address security, legal, and compliance challenges effectively. By adopting an open-source, developer-centric methodology, Promptfoo has become the leading tool in its field, attracting a community of more than 20,000 users. It offers custom probes tailored to your specific application, focusing on identifying critical failures instead of merely targeting generic vulnerabilities like jailbreaks and prompt injections. With a user-friendly command-line interface, live reloading, and efficient caching, users can operate swiftly without the need for SDKs, cloud services, or login requirements. This tool is employed by teams reaching millions of users and is backed by a vibrant open-source community. Users can create dependable prompts, models, and retrieval-augmented generation (RAG) systems with benchmarks that align with their unique use cases. Additionally, it enhances the security of applications through automated red teaming and pentesting, while also expediting evaluations via its caching, concurrency, and live reloading features. Consequently, Promptfoo stands out as a comprehensive solution for developers aiming for both efficiency and security in their AI applications.

Peta serves as an advanced control plane for the Model Context Protocol (MCP), streamlining, securing, governing, and overseeing how AI clients and agents interact with external tools, data, and APIs. This platform integrates a zero-trust MCP gateway, a secure vault, a managed runtime environment, a policy engine, human-in-the-loop approvals, and comprehensive audit logging into a cohesive solution, enabling organizations to implement nuanced access controls, safeguard raw credentials, and monitor all tool interactions conducted by AI systems. At the heart of Peta is Peta Core, which functions as both a secure vault and gateway, encrypting credentials, generating short-lived service tokens, verifying identity and compliance with policies for each request, managing the MCP server lifecycle through lazy loading and auto-recovery, and injecting credentials during runtime without revealing them to agents. Additionally, the Peta Console empowers teams to specify which users or agents can access particular MCP tools within designated environments, establish approval protocols, manage tokens, and review usage statistics and associated costs. This multifaceted approach not only enhances security but also fosters efficient resource management and accountability within AI operations.

We develop an extensive memory system for your web application along with the interactions we participate in. Our quality assurance testing agent is designed to pinpoint specific actions and goals. You can set up the tests using your personal user credentials and relevant data. Various personas supervise the agent, leading to the identification of defects that differ in severity. Our AI-driven agent analyzes situations and takes necessary actions to fulfill testing objectives. It automatically provides comments on your pull requests, delivering actionable insights. Additionally, it produces bug reports that are friendly to developers, encompassing essential details like console logs and network requests. The testing process can divert attention from developing new features and necessitate updates to the test code for even minor app modifications. Issues in production can create pressure on customer support, disrupt developers, and potentially result in the loss of customers. Relying on manual testing incurs high costs and often results in sluggish feedback cycles, which may hinder timely releases. Ultimately, an efficient testing framework is crucial for maintaining the overall health of your application and ensuring customer satisfaction.

Certified penetration testers collaborate with generative AI to enhance your penetration testing experience, ensuring top-notch security and fostering customer trust with our comprehensive and competitively priced services. Instead of waiting weeks for your pentest to begin, only to receive automated scan reports, you can securely initiate your pentest immediately with our team of in-house certified professionals. Our AI evaluates your application and infrastructure to effectively define the scope of your penetration test. A certified expert is swiftly allocated and scheduled to commence your pentest promptly. Unlike the typical "deploy and forget" approach, we maintain ongoing surveillance of your security posture to ensure continuous protection. Your dedicated cyber success manager will assist your team in addressing any remediation efforts needed. Every time you roll out a new version, it becomes crucial to remember that your previous pentest may no longer be relevant. There are significant risks associated with falling out of compliance with regulations, insufficient documentation, and potential vulnerabilities such as data leakage, ineffective encryption, and poor access controls. In today’s digital landscape, safeguarding your customers' data is paramount; therefore, you should adopt best practices to ensure its protection effectively. Ultimately, a proactive approach to cybersecurity can significantly mitigate risks and enhance your organization’s overall resilience.

Shiplight revolutionizes quality-assurance workflows by incorporating autonomous AI agents that autonomously generate, execute, and maintain comprehensive end-to-end tests, allowing development teams to "ship fast and break nothing." Within just a few days, it achieves full test coverage without the need for any scripting; instead, it automatically creates test flows from various sources such as product flows, documentation, and support tickets. The system employs parallel execution and intelligent caching to provide quick and trustworthy feedback, while visual editors and natural-language prompts empower non-technical users, like product managers and QA analysts, to create, review, and manage tests effortlessly. Over time, the underlying agent adapts to the application’s behavior, skillfully navigating UI elements, interacting with flows, and adjusting to any UI modifications, significantly minimizing maintenance challenges and unreliable tests. Additionally, it seamlessly integrates into existing CI/CD pipelines and features an agent-driven execution layer, enhancing overall efficiency in the development process. This innovative approach not only streamlines testing but also fosters collaboration among team members, regardless of their technical expertise.

BugHunter AI is an innovative testing and quality assurance solution powered by artificial intelligence, designed to automatically and continuously assess games and software for critical issues before they enter production. This technology assists development studios in decreasing quality assurance expenses, speeding up release timelines, and enhancing overall product quality. By employing intelligent automation, it conducts tests around the clock on various platforms, eliminating the necessity for additional QA personnel and uncovering edge cases that manual testing may overlook, which leads to quicker bug identification and more comprehensive coverage. Furthermore, it integrates effortlessly with current workflows, often producing results in approximately 30 days, providing automated validations that cover aspects such as level design, game mechanics, monetization features, UI stability, crashes, and other bugs, all designed to reflect genuine gameplay scenarios. With BugHunter AI, studios can expect substantial reductions in conventional QA overhead, achieving up to 75% lower costs for quality assurance and accelerating bug detection by up to 67%. This transformative approach not only streamlines the testing process but also empowers developers to focus more on creativity and innovation in their projects.

Spur represents the pioneering advancement in AI-driven QA engineering, automating the testing process effectively. Its intelligent agents can mimic the behavior of countless users within minutes, identifying bugs before they reach the end-users. Unlike traditional methods that rely on CSS and XPaths, Spur's agents interact with web elements directly, achieving an impressive 99% reliability and minimizing false positives. By utilizing Spur, a single QA professional can exponentially increase their output, executing thousands of regression tests daily. With the integrated scheduler, tests can be aligned seamlessly with release timelines, eliminating any potential delays. The reporting process is streamlined with features such as one-click bug reports, notifications, video replays of testing sessions, and comprehensive step-by-step analysis. Moreover, Spur's AI agents are exceptionally tailored to deliver high-quality testing and insights, while also ensuring the security of data with advanced encryption protocols, both during storage and transmission. This innovative tool not only enhances efficiency but also empowers teams to maintain high standards in software quality assurance.

Posium is an innovative platform that harnesses artificial intelligence to transform the comprehensive software testing landscape for both web and mobile applications. Utilizing a range of specialized AI agents, it automates and simplifies the testing workflow. By evaluating applications, Posium determines their type and identifies critical test scenarios. It crafts intricate test flows through an analysis of user interfaces, generating robust test scripts that are compatible with various programming languages and frameworks. The platform empowers users to effortlessly plan, develop, execute, monitor, and maintain automated tests, offering features such as AI-driven insights, extensive logging capabilities, and access to authentic mobile device infrastructure. Additionally, Posium enables the importation of test specifications from platforms like Jira, facilitating the conversion of manual tests into automated test suites. By leveraging its advanced AI agents and intuitive user interface, Posium not only seeks to boost productivity but also aims to uphold continuous reliability in the realm of software testing, making it a vital tool for development teams. Its commitment to enhancing the efficiency of testing processes signifies a notable advancement in the quality assurance sector.

Guardrails play an essential role in the upkeep of AI systems, and LangWatch serves to protect both you and your organization from the risks of disclosing sensitive information, prompt injection, and potential AI misbehavior, thereby safeguarding your brand from unexpected harm. For businesses employing integrated AI, deciphering the interactions between AI and users can present significant challenges. To guarantee that responses remain accurate and suitable, it is vital to maintain consistent quality through diligent oversight. LangWatch's safety protocols and guardrails effectively mitigate prevalent AI challenges, such as jailbreaking, unauthorized data exposure, and irrelevant discussions. By leveraging real-time metrics, you can monitor conversion rates, assess output quality, gather user feedback, and identify gaps in your knowledge base, thus fostering ongoing enhancement. Additionally, the robust data analysis capabilities enable the evaluation of new models and prompts, the creation of specialized datasets for testing purposes, and the execution of experimental simulations tailored to your unique needs, ensuring that your AI system evolves in alignment with your business objectives. With these tools, businesses can confidently navigate the complexities of AI integration and optimize their operational effectiveness.

Tenable AI Exposure is a robust, agentless solution integrated into the Tenable One exposure management platform, designed to enhance visibility, context, and control over the utilization of generative AI tools such as ChatGPT Enterprise and Microsoft Copilot. This tool empowers organizations to track user engagement with AI technologies, providing insights into who is accessing them, the nature of the data involved, and the execution of workflows, while identifying and addressing potential risks like misconfigurations, insecure integrations, and the leakage of sensitive information, including personally identifiable information (PII), payment card information (PCI), and proprietary business data. Furthermore, it protects against threats like prompt injections, jailbreak attempts, and policy breaches by implementing security measures that do not interfere with daily operations. Compatible with leading AI platforms and ready for deployment in just minutes with zero downtime, Tenable AI Exposure facilitates the governance of AI use, making it an essential component of an organization's overall cyber risk management strategy, ultimately ensuring safer and more compliant AI operations. By integrating these security protocols, organizations can foster a culture of responsible AI usage while mitigating potential vulnerabilities.

Docket is an advanced test automation platform that leverages AI to utilize vision-based browser agents rather than fragile DOM selectors for independently testing any web interface. This innovative approach merges visual comprehension with natural language commands, allowing Docket to effectively automate intricate user interfaces, including everything from dashboards and video editing tools to canvas elements. As a result, users can expect a more robust and adaptable testing solution that can handle various complexities in web applications.

Garak evaluates the potential failures of an LLM in undesirable ways, examining aspects such as hallucination, data leakage, prompt injection, misinformation, toxicity, jailbreaks, and various other vulnerabilities. This free tool is designed with an eagerness for development, continually seeking to enhance its functionalities for better application support. Operating as a command-line utility, Garak is compatible with both Linux and OSX systems; you can easily download it from PyPI and get started right away. The pip version of Garak receives regular updates, ensuring it remains current, while its specific dependencies recommend setting it up within its own Conda environment. To initiate a scan, Garak requires the model to be analyzed and, by default, will conduct all available probes on that model utilizing the suggested vulnerability detectors for each. During the scanning process, users will see a progress bar for every loaded probe, and upon completion, Garak will provide a detailed evaluation of each probe's findings across all detectors. This makes Garak not only a powerful tool for assessment but also a vital resource for researchers and developers aiming to enhance the safety and reliability of LLMs.

Sapiom serves as a financial and access infrastructure platform that allows AI agents and API-driven applications to securely access, provision, and pay for various third-party services, APIs, tools, and compute resources in real-time, eliminating the need for manual onboarding, individual management of API keys, and the necessity of pre-purchased credits. It features a centralized dashboard that enables organizations to keep track of overall spending, agent activities, service utilization, and real-time analytics, while also allowing the establishment of rule-based spending and usage limits, alongside the enforcement of governance policies to ensure that autonomous agents operate securely within set financial boundaries. Additionally, Sapiom offers SDKs and APIs that empower developers to link agents to a selective network of services, including verification processes, web searching, AI models through OpenRouter, and automation of image/audio generation and browser tasks, facilitating automated authentication and micro-payments for each use. This system meticulously tracks every API invocation, associated costs, and execution traces, ensuring comprehensive visibility and control over operations, which ultimately enhances the operational efficiency of organizations leveraging its capabilities.

Selenium tests often suffer from instability and maintenance challenges. Parasoft Selenic addresses prevalent issues in your existing Selenium projects without imposing vendor restrictions. When your team relies on Selenium for developing and testing the user interface of software applications, it's crucial to ensure that the testing process effectively uncovers genuine problems, formulates relevant and high-quality tests, and minimizes maintenance efforts. Although Selenium provides numerous advantages, maximizing the efficiency of your UI testing while utilizing your current processes is essential. With Parasoft Selenic, you can pinpoint actual UI problems and receive prompt feedback on test outcomes, enabling you to deliver superior software more swiftly. You can enhance your existing library of Selenium web UI tests or quickly generate new ones using a versatile companion that integrates effortlessly into your setup. Parasoft Selenic employs AI-driven self-healing to resolve frequent Selenium issues, significantly reduces test execution time through impact analysis, and provides additional features to streamline your testing workflow. Ultimately, this tool empowers your team to achieve more effective and reliable testing results.

MASST (Mobile Application Security Suite & Tools) serves as an integrated platform focused on ensuring the security of mobile applications by identifying, safeguarding, and overseeing them throughout their development and operational phases. Within its Threat Detection component, the suite incorporates various modules, including CodeLock for analyzing vulnerabilities across more than 50 vectors, RunLock for conducting runtime evaluations and simulating attacks, APILock for identifying and securing API endpoints, and ThreatLock for comprehensive red-teaming evaluations. To mitigate potential threats, the suite provides protective measures such as Defender, which employs RASP for real-time shielding; Shield, designed to prevent reverse-engineering and intellectual property theft; and Guard, which securely manages local storage of sensitive data, keys, and certificates using white-box cryptography. Additionally, the Threat Visibility layer features the ThreatLens Dashboard, which enables real-time surveillance, analytical assessments, and practical insights related to attacks, anomalies, and the overall security status of applications. This holistic approach not only safeguards mobile applications but also empowers developers with the tools necessary to enhance their security measures continuously.

An advanced AI-driven testing solution for web applications that identifies issues prior to user encounters is now available. This intelligent agent not only determines the necessary tests but also generates and maintains them to ensure their relevance over time. You can execute these tests directly from our platform or seamlessly integrate them into your CI/CD workflow. The reliability of end-to-end testing has been a significant concern, as failures can stem from more than just faulty code. Factors like external dependencies, timing discrepancies, unpredictable behaviors, race conditions, and state leaks contribute to the unpredictability of test outcomes. To address these challenges, we are implementing effective strategies to help you save valuable time that would otherwise be spent troubleshooting perfectly functioning code. By enhancing the stability of testing processes, we aim to boost overall software quality and developer confidence.

MiniMax M2 is an open-source foundational model tailored for agent-driven applications and coding tasks, achieving an innovative equilibrium of efficiency, velocity, and affordability. It shines in comprehensive development environments, adeptly managing programming tasks, invoking tools, and executing intricate, multi-step processes, complete with features like Python integration, while offering impressive inference speeds of approximately 100 tokens per second and competitive API pricing at around 8% of similar proprietary models. The model includes a "Lightning Mode" designed for rapid, streamlined agent operations, alongside a "Pro Mode" aimed at thorough full-stack development, report creation, and the orchestration of web-based tools; its weights are entirely open source, allowing for local deployment via vLLM or SGLang. MiniMax M2 stands out as a model ready for production use, empowering agents to autonomously perform tasks such as data analysis, software development, tool orchestration, and implementing large-scale, multi-step logic across real organizational contexts. With its advanced capabilities, this model is poised to revolutionize the way developers approach complex programming challenges.

CoTester stands as the pioneering AI agent for software testing, poised to revolutionize the field of software quality assurance. This innovative tool is capable of identifying bugs and performance problems both prior to and following deployment, delegating these issues to team members, and ensuring their resolution. Designed to be onboardable, taskable, and trainable, CoTester can perform daily tasks akin to a human software tester, smoothly fitting into current workflows. With its pre-training in advanced software testing principles and the Software Development Life Cycle (SDLC), it significantly enhances the efficiency of quality assurance teams by facilitating the writing, debugging, and execution of test cases at a speed up to 50% faster. Furthermore, CoTester exhibits conversational adaptability, enabling it to comprehend and address intricate testing scenarios while constructing high-quality context tailored to specific project needs. Its seamless integration with existing knowledge bases allows for effective access and utilization of current project documentation, making it an essential asset for any software development team. As a result, CoTester not only improves testing efficiency but also enhances collaboration among team members, ultimately contributing to superior software quality.

Test-Lab.ai is a modern AI-driven test automation solution that replaces brittle scripts with autonomous browser-based testing. It allows teams to define tests using natural language instead of writing and maintaining test code. AI agents execute tests in real browsers, following actual user journeys across complex workflows. The platform automatically detects bugs, broken flows, and UI regressions without manual intervention. Test-Lab.ai produces actionable reports with screenshots, step-by-step execution logs, and failure explanations. Tests run in parallel and complete in minutes, providing rapid feedback for fast-moving teams. Self-healing intelligence adapts to layout changes and renamed elements, keeping tests reliable. The platform supports authentication, multi-step forms, and dynamic single-page applications. CI/CD integration takes only minutes, enabling continuous testing on every deployment. Test-Lab.ai helps teams ship faster while maintaining confidence in product quality.

ContextQA is an innovative solution designed to help organizations boost their automation testing capabilities, improve software quality, accelerate product release timelines, and significantly reduce costs associated with maintaining software standards by leveraging AI-powered SaaS technology. By transforming manual test cases and user stories into automated tests, AI agents streamline the testing process. Additionally, ContextQA gathers evidence and conducts root-cause analysis when bugs are detected. It identifies key user journeys and highlights deficiencies in the software testing framework. With comprehensive end-to-end testing, including contract testing, there is no longer a necessity for distinct tools for front-end and back-end testing. It allows for the identification of issues, performance improvements, and ensures smooth user interactions across various browsers, mobile devices, and operating systems. Furthermore, ContextQA makes it easier to integrate test cases with minimal effort, facilitating a swift increase in automation coverage for your products and services while ultimately enhancing productivity and efficiency.

TestDriver is an innovative AI-powered autonomous agent aimed at transforming the process of end-to-end testing for both web and desktop applications. In contrast to conventional testing frameworks that depend on selectors or static analysis, TestDriver leverages AI vision and hardware emulation to mimic genuine user interactions, allowing it to assess any application and manage any operating system configuration. This method streamlines the setup process by removing the necessity for complicated selectors, decreases maintenance burdens as tests endure code modifications, and broadens testing capabilities far beyond traditional limitations. The AI autonomously navigates applications to create customized test plans, enhancing the onboarding experience and ensuring that essential user flows are verified with minimal user intervention. Additionally, its seamless integration into CI/CD pipelines facilitates ongoing, automated quality assurance, instilling confidence in the integrity of the code. The AI's ability to adjust to UI modifications eliminates fragile tests, ensuring stability as the application matures. Ultimately, TestDriver not only improves efficiency but also empowers teams to focus more on innovation rather than tedious testing tasks.

QASolve.ai is a no-code platform powered by artificial intelligence, aimed at achieving rapid application quality assurance while minimizing the need for manual involvement. With the promise of generating over 80% of test automation within a single week, it leverages an AI model capable of crafting tests without the necessity for source code, specifications, or human scripting. The platform incorporates self-healing technology to minimize flaky tests and facilitates extensive parallel execution across various platforms and devices, enabling teams to conduct thorough test suites efficiently. Upon registering their application URL and roles, users benefit from QASolve’s “Discovery” AI agents, which meticulously analyze user journeys, workflows, and relationships to generate relevant test cases and test data. These agents also seamlessly integrate into CI/CD pipelines through APIs, offering dashboards that deliver real-time insights, failure analysis, and ongoing maintenance of tests through different software releases. Additionally, QASolve.ai allows for the export of tests to popular frameworks such as Playwright or Selenium, thereby preventing vendor lock-in and providing flexibility for development teams. This comprehensive approach not only streamlines the testing process but also enhances overall application quality assurance.

MagnifAI is an innovative quality assurance platform powered by artificial intelligence that transforms the landscape of software testing workflows through the use of automation and generative AI technologies. This platform empowers teams to convert intricate testing scenarios into automated tests by directly generating test cases and automation code from specific project requirements. Utilizing agentic AI, MagnifAI crafts personalized workflows that can be executed immediately, allowing teams to customize the testing process according to their unique demands. Additionally, it significantly enhances visual testing capabilities, ensuring uniformity across various designs, layouts, and environments, while also providing seamless integration with existing test management tools and frameworks. Importantly, MagnifAI prioritizes security for sensitive data, safeguarding project documents and test plans from unauthorized access. By streamlining the overall testing process, the platform effectively reduces technical debt, optimizes testing efficiency, and boosts productivity, as it facilitates quicker creation and execution of test cases. Furthermore, MagnifAI’s innovative solution not only increases the frequency of testing but also minimizes the time spent on monotonous tasks, ultimately leading to a more efficient software development lifecycle.

Shift Technology’s Underwriting Risk Detection, an AI-driven SaaS platform, assists insurance companies in refining their underwriting processes by pinpointing instances of fraud, misrepresentation, premium leakage, and network-related risks throughout policy applications. By employing advanced predictive models and anomaly detection techniques, it scrutinizes quotes and applications, tracks alterations after binding and during renewals, and identifies threats such as identity fraud, agent collusion, ghost broking, policy hijacking, and tampering with documents or photos. The platform seamlessly integrates various external data sources, delivers real-time alerts, and offers underwriters comprehensible outputs that include contextual decision-making insights. Additionally, it facilitates continuous learning, allowing the system to evolve as new risk trends arise. Its design aims to expedite the underwriting process, enhance pricing precision, safeguard policyholders, mitigate losses, and empower organizations to expand their portfolios with greater confidence by detecting risky behaviors at an early stage. Overall, this innovative solution represents a significant advancement in the insurance industry's approach to risk management.

Ranger is an efficient and dependable QA testing platform that combines the power of AI with human expertise. It not only creates and updates QA tests that identify genuine bugs but also empowers teams to progress without interruption. By managing all aspects of QA testing, Ranger saves engineers over 200 hours each year, facilitating quicker deployment of new features. Its web agent navigates your website according to your testing strategy, producing Playwright code that is meticulously reviewed by QA specialists to guarantee both precision and clarity. Additionally, Ranger intelligently triages test failures, with a dedicated team of QA Rangers conducting thorough evaluations to verify actual bugs. As new features are introduced, it updates core testing flows and adapts tests accordingly while integrating smoothly with platforms like Slack, GitHub, and GitLab. Trusted by organizations such as OpenAI, Suno, and Clay, Ranger delivers clear insights into product performance and sustains a high pace of engineering development. This unique combination of automation and human review ensures that teams can maintain confidence in their software quality as they innovate.

Heal is a cutting-edge quality assurance (QA) platform powered by artificial intelligence, crafted to streamline the development and upkeep of comprehensive end-to-end tests, thereby empowering engineering teams to achieve swift and dependable test coverage. Utilizing AI agents, Heal generates Playwright-based tests that are meticulously fine-tuned by human professionals, guaranteeing superior quality outcomes. This innovative methodology enables teams to attain up to 80% test coverage in a matter of weeks, which greatly minimizes the need for manual QA tasks. Designed to eliminate unreliable tests, Heal delivers consistent and dependable results. Additionally, the platform integrates effortlessly with Slack, allowing users to initiate requests for new tests directly within their current workflows. The human-reviewed test results ensure precision, and clients retain full ownership of the generated test code, which provides them with adaptability and prevents vendor lock-in. With Heal, engineering teams can free up around 7 hours of work per engineer each week, expediting QA cycles to a mere 10 minutes. As a result, teams can focus more on innovation and less on time-consuming testing processes.

The rapid pace of change today necessitates a revolutionary approach to testing. Equip your teams with the tools to create resilient and scalable tests that thrive in the cloud environment. Generate AI-driven tests swiftly by utilizing the smart agent (Architect) or seamlessly transition steps articulated in simple English into automated processes through natural language processing. Avoid the inefficiency of constantly repairing malfunctioning tests. Functionize employs machine learning to automatically adapt your tests in response to UI modifications. Identify test failures quickly with instant SmartFix recommendations, and leverage screenshot comparisons along with clear error messages for effortless troubleshooting. Engage with your tests in real-time on the virtual machine using breakpoints with Live Debug functionality. Revise your tests effortlessly with Smart Screenshots and take advantage of one-click SmartFix remedies. Remove the burden of test infrastructure altogether. With Functionize’s Test Cloud, execute an unlimited number of tests frequently across all major browsers at scale, ensuring your testing process remains agile and efficient. This innovative approach not only enhances productivity but also drives higher quality outcomes in software development.

Fire Your QA Today is an innovative quality-assurance platform powered by AI that converts a single screen recording of your web application’s workflow into an autonomous QA agent, which can execute continuous end-to-end testing across multiple releases. Users simply need to install a lightweight browser extension and record their usual testing process, such as navigating through a CRM, ERP, or other internal tools; the platform then learns each step and automatically replays and validates them. This system is adept at managing various web environments, including legacy systems, shadow DOMs, and iframes, without the need for any custom scripts or APIs. It is compatible with web applications, CRMs, ERPs, and internal tools, regardless of their underlying technology stack, facilitating automated validation of user flows, role changes, data entry, and verification of UI modifications. Case studies indicate that organizations experience up to a 90% decrease in manual QA time, achieve complete UAT coverage across all test cases, and benefit from significant weekly time savings, with detailed reports generated in the browser itself. By automating these processes, teams can focus on more critical tasks, leading to improved productivity and efficiency in quality assurance practices.

Arcade.dev is a platform designed for AI tool calling that empowers AI agents to safely carry out real-world tasks such as sending emails, messaging, updating systems, or activating workflows through integrations authorized by users. Serving as a secure authenticated proxy in line with the OpenAI API specification, Arcade.dev allows models to access various external services, including Gmail, Slack, GitHub, Salesforce, and Notion, through both pre-built connectors and custom tool SDKs while efficiently handling authentication, token management, and security. Developers can utilize a streamlined client interface—arcadepy for Python or arcadejs for JavaScript—that simplifies tool execution and authorization processes without complicating application logic with the need for credentials or API details. The platform is versatile, supporting secure deployments in the cloud, private VPCs, or local environments and features a control plane designed for managing tools, users, permissions, and observability. This comprehensive management system ensures that developers can maintain oversight and control while leveraging the power of AI to automate various tasks effectively.