Top Jozu Alternatives

Llama Guard is an innovative open-source safety model developed by Meta AI that seeks to enhance the security of large language models during their interactions with users. It functions as a filtering system for both inputs and outputs, assessing prompts and responses for potential safety hazards, including toxicity, hate speech, and misinformation. Trained on a carefully curated dataset, Llama Guard competes with or even exceeds the effectiveness of current moderation tools like OpenAI's Moderation API and ToxicChat. This model incorporates an instruction-tuned framework, allowing developers to customize its classification capabilities and output formats to meet specific needs. Part of Meta's broader "Purple Llama" initiative, it combines both proactive and reactive security strategies to promote the responsible deployment of generative AI technologies. The public release of the model weights encourages further investigation and adaptations to keep pace with the evolving challenges in AI safety, thereby stimulating collaboration and innovation in the domain. Such an open-access framework not only empowers the community to test and refine the model but also underscores a collective responsibility towards ethical AI practices. As a result, Llama Guard stands as a significant contribution to the ongoing discourse on AI safety and responsible development.

ZenGuard AI operates as a specialized security platform designed to protect AI-enhanced customer service agents from a variety of potential dangers, thereby promoting their safe and effective functionality. Developed with input from experts affiliated with leading tech companies such as Google, Meta, and Amazon, ZenGuard provides swift security solutions that mitigate the risks associated with AI agents powered by large language models. This platform is adept at shielding these AI systems from prompt injection attacks by recognizing and counteracting any manipulation attempts, which is vital for preserving the integrity of LLM performance. Additionally, it prioritizes the identification and management of sensitive data to prevent potential data breaches while ensuring compliance with privacy regulations. ZenGuard also enforces content guidelines by blocking AI agents from discussing prohibited subjects, which is essential for maintaining brand integrity and user safety. Furthermore, the platform boasts a user-friendly interface for policy configuration, facilitating prompt adjustments to security settings as required. This flexibility is crucial in an ever-changing digital environment where new threats to AI systems can arise at any moment, thus reinforcing the importance of proactive security measures. Ultimately, ZenGuard AI stands as a comprehensive solution for anyone seeking to fortify their AI operations against evolving cyber threats.

Enkrypt AI is an advanced platform tailored for the security, compliance, and governance needs of enterprises in the artificial intelligence sector, with a particular emphasis on protecting large language models, AI agents, multimodal systems, and processes critical to machine operations. It serves various sectors, including finance, healthcare, insurance, and government, enabling organizations to rapidly innovate while prioritizing safety and maintaining their competitive advantages. This platform encompasses a wide range of AI security features, which include: Guardrails: With remarkably low latency of under 50 milliseconds, the policy-driven guardrails effectively reduce risks linked to prompt injections, unauthorized data leaks, dangerous outputs, and non-compliant behavior of agents in real-time situations. Red Teaming: The system executes policy-driven multimodal attack simulations on LLMs and AI agents before their deployment, effectively uncovering potential vulnerabilities. MCP Security: The MCP Scan Hub and Secure MCP Gateway provide thorough protection for MCP servers, tools, and agent toolchains throughout the entire process, ensuring robust security measures are in place. Compliance: Continuous monitoring guarantees compliance with various standards such as NIST AI RMF, OWASP LLM Top 10, the EU AI Act, HIPAA, and FINRA, alongside certifications like ISO 27001 and SOC 2 Type II. Enkrypt AI's recognition as a Gartner Cool Vendor for 2025 further highlights its distinctive position in the market, reinforcing its commitment to secure and compliant AI development.

XecGuard, a product of CyCraft, functions as a protective firewall tailored for reliable and autonomous AI, specifically designed to shield enterprise AI infrastructures from numerous threats, including prompt injection, data breaches, and hazardous outputs. Drawing on CyCraft's vast expertise in both offensive and defensive security operations across sectors such as government, finance, and advanced manufacturing, XecGuard amplifies security by merging AI guardrails with established cybersecurity measures, compliance frameworks, and risk management strategies, thereby promoting the secure integration of enterprise AI. This cutting-edge solution operates as a plug-and-play LoRA security module, enabling organizations to enhance their LLM defenses effortlessly without requiring alterations to the core model framework, which ensures swift deployment while preserving peak performance. By employing proprietary security datasets along with sophisticated multi-stage fine-tuning techniques, XecGuard markedly boosts the robustness of LLMs against adversarial threats, harmful interference, and unauthorized data extraction, establishing itself as a vital asset for any organization looking to strengthen its AI systems effectively. Additionally, its capacity to swiftly adapt to new and emerging threats further highlights its significance in the rapidly changing technological environment. This adaptability not only protects existing systems but also fosters greater confidence in the safe deployment of AI solutions.

Straiker is a cutting-edge security solution meticulously crafted to protect enterprise AI applications and autonomous agents, specifically targeting the new risks introduced by "agentic AI" systems that interact with a multitude of tools, APIs, and sensitive data. By providing extensive visibility and management across the complete AI stack, it scrutinizes behavioral signals from models, prompts, tools, identities, and infrastructure, enabling swift identification and mitigation of AI-specific risks such as prompt injection, privilege escalation, data exfiltration, and tool misuse. The platform seamlessly incorporates continuous discovery, adversarial testing, and runtime safeguarding through vital components like Discover AI, Ascend AI, and Defend AI, which collaborate to recognize all active agents, simulate possible attacks to uncover vulnerabilities, and enforce real-time protective measures during operation. Its complex, layered architecture captures deep contextual signals from user interactions, network behavior, and agent workflows, thereby ensuring a formidable defense against constantly evolving threats. As advancements in AI technologies progress at an unprecedented rate, the demand for such specialized security measures will only grow, making them essential for enterprises striving to thrive in this intricate environment. Ultimately, the proactive approach of platforms like Straiker is crucial in maintaining the integrity and safety of AI-driven operations.

iDox.ai Guardrail acts as an immediate protective layer for AI applications, aimed at preventing the exposure of sensitive data during generative AI activities. This cutting-edge solution operates at the endpoint level, intercepting user prompts, uploaded documents, and all forms of AI interactions before any data is sent from the user's device. Guardrail utilizes policy-based strategies to detect and block the unauthorized dissemination of sensitive information, such as personally identifiable information (PII), protected health information (PHI), payment card information (PCI), intellectual property, and various other confidential business details. Unlike traditional data loss prevention (DLP) systems, Guardrail is specifically designed for AI applications, constantly monitoring user interactions with platforms like ChatGPT, Microsoft Copilot, and Claude, while implementing protective measures in real-time to maintain security. Its notable features include continuous oversight of user prompts and file submissions, the capability to recognize sensitive data with AI awareness, immediate anonymization and sanitization of data, protection against risks posed by AI agents—such as unauthorized access incidents (like OpenClaw)—and the enforcement of website whitelisting along with strict policy implementation. Moreover, Guardrail not only bolsters user trust in AI technologies but also aligns with data privacy regulations, ensuring that users can engage with AI tools without concerns about compromising their sensitive information. This proactive approach positions Guardrail as an essential component in the evolving landscape of AI security.

Alice is a leading AI safety and adversarial intelligence platform built to secure the rapidly evolving landscape of generative AI, agents, and emerging technologies. Rebranded from ActiveFence, Alice combines a decade of real-world adversarial research with the industry’s most comprehensive toxic and abuse dataset to protect platforms, applications, and foundation models at scale. Its proprietary Rabbit Hole intelligence engine continuously ingests and analyzes billions of manipulative, harmful, and abusive data samples, enabling proactive threat detection before incidents become public crises. Today, Alice safeguards more than 3 billion users worldwide and monitors over 1 billion daily AI-human interactions across 120+ languages. The company’s WonderSuite platform delivers end-to-end AI security, including WonderBuild for pre-deployment stress testing, WonderFence for dynamic runtime guardrails, and WonderCheck for ongoing automated red-teaming. These capabilities address emerging risks such as prompt injection, jailbreaks, application-level exploits, compliance failures, and unintended GenAI behavior. Alice allows organizations to customize policy alignment based on regulatory obligations and risk tolerance, ensuring trusted interactions across text, image, and multimodal systems. By strengthening governance frameworks and reducing reputational exposure, Alice helps enterprises and frontier model labs deploy AI responsibly and confidently. Trusted by leading global technology companies, Alice serves as a foundational layer of safety for more than half of the world’s online experiences.

Amazon Bedrock Guardrails serves as a versatile safety mechanism designed to enhance compliance and security for generative AI applications created on the Amazon Bedrock platform. This innovative system enables developers to establish customized controls focused on safety, privacy, and accuracy across various foundation models, including those hosted on Amazon Bedrock, as well as fine-tuned or self-hosted variants. By leveraging Guardrails, developers can consistently implement responsible AI practices, evaluating user inputs and model outputs against predefined policies. These policies incorporate a range of protective measures like content filters to prevent harmful text and imagery, topic restrictions, word filters to eliminate inappropriate language, and sensitive information filters to redact personally identifiable details. Additionally, Guardrails feature contextual grounding checks that are essential for detecting and managing inaccuracies or hallucinations in model-generated responses, thus ensuring a more dependable interaction with AI technologies. Ultimately, the integration of these safeguards is vital for building trust and accountability in the field of AI development while also encouraging developers to remain vigilant in their ethical responsibilities.

GuardionAI functions as both an Agent and a MCP Security Gateway, providing all-encompassing security for AI agents and Model Context Protocol tools that engage with enterprise data. Strategically integrated within the execution path, it proficiently detects and redacts sensitive information, enforces protective measures, and grants improved visibility into activities often overlooked by traditional SIEM, DLP, and identity frameworks. Every action taken by agents is thoroughly monitored, enforced, and recorded at the protocol level, covering a wide array of components including AI agents, LLM applications, RAG systems, chatbots, coding assistants, MCP servers, internal applications, databases, operating systems, and cloud infrastructures. GuardionAI is specifically engineered to mitigate critical vulnerabilities in AI, such as prompt injection, system overrides, web-based attacks, MCP tool tampering, harmful code execution, inappropriate content exposure, leakage of personally identifiable information and credentials, unauthorized access to sensitive data, off-topic drift, and violations of access control, all in accordance with the OWASP LLM Top 10 and agentic AI threat frameworks. Furthermore, the gateway features a formidable four-layer protection system, ensuring that organizations can effectively secure their AI assets like never before. This comprehensive strategy not only bolsters security but also equips teams with the necessary insights to adeptly navigate the intricacies of modern AI landscapes, ultimately fostering a more robust defense against emerging threats. In an age where data integrity is paramount, GuardionAI stands as a critical partner in safeguarding enterprise resources.

Streamline the management and sharing of artifacts across multiple accounts, ensuring that your teams and build systems have the appropriate access rights. By opting for a fully managed service, you can avoid the hassles of establishing and maintaining your own artifact server or infrastructure. Costs are based solely on the software packages you store, your request volume, and any data you transfer out of the region, following a pay-as-you-go pricing model. CodeArtifact allows you to pull packages from well-known public repositories such as npm Registry, Maven Central, Python Package Index (PyPI), and NuGet. Furthermore, you can securely share private packages among different organizations by publishing them to a centralized repository within your company. Elevate your operational efficiency by integrating automated approval workflows using CodeArtifact APIs and Amazon EventBridge, while keeping track of your packages with AWS CloudTrail. You can also seamlessly retrieve dependencies from CodeArtifact within AWS CodeBuild and publish new versions of your private packages, with robust protection ensured through AWS Identity and Access Management (IAM). This cohesive strategy not only streamlines package management but also fosters enhanced collaboration among teams and organizations, ultimately leading to greater productivity and innovation. By implementing such a system, you create a more agile and interconnected environment for software development.

LangProtect is an innovative security and governance solution crafted specifically for AI, providing strong defenses against challenges such as prompt injections, jailbreaks, data breaches, and the creation of unsafe or non-compliant outputs in LLM and Generative AI systems. Designed for advanced GenAI production environments, the platform applies real-time controls at the execution level, carefully analyzing prompts, model responses, and function calls as they happen, which allows teams to block high-risk actions before they can impact users or jeopardize sensitive data. In doing so, LangProtect promptly neutralizes potential threats, thereby safeguarding the integrity of both data and user interactions. Moreover, LangProtect's API-first architecture allows for effortless integration with existing LLM systems while ensuring low latency, and it supports a variety of deployment models, including cloud, hybrid, and on-premise configurations to satisfy the security and data residency needs of organizations. The platform is also adept at protecting modern architectures like RAG pipelines and agentic workflows, offering policy-driven enforcement, ongoing monitoring, and governance that are prepared for audits. This all-encompassing strategy empowers organizations to harness AI technologies confidently while significantly reducing the risks tied to their implementation. Ultimately, LangProtect stands out as a vital resource for businesses aiming to navigate the complexities of AI security effectively.

Notenic operates as a governance and orchestration platform designed to oversee and safeguard autonomous AI agents, often referred to as "digital labor," especially in high-stakes environments where failures could result in severe regulatory, legal, or operational consequences. As an integral infrastructure layer, it seamlessly integrates into the execution pathways of AI systems to implement stringent governance measures before any interaction occurs with systems of record, thereby circumventing the challenges posed by post-output filters or controls that are applied during prompting. The platform is built on a zero-trust runtime architecture, which is defined by core principles like zero-persistence that guarantees no data retention after each session and execution-path control that enforces policies at the moment actions are performed. This architecture prioritizes independence from the model's context, effectively shielding against adversarial inputs that could undermine governed behavior. Additionally, Notenic provides a holistic control plane for the administration of AI agents, treating them as operational entities with specific roles and necessary oversight, which boosts organizational efficiency and accountability. Ultimately, this comprehensive framework ensures that all AI operations are executed in a secure, compliant, and well-regulated manner, reinforcing trust in automated processes. In a landscape where AI technology continues to evolve rapidly, Notenic stands out as a vital solution for maintaining the integrity and reliability of digital labor.

Lunary acts as a comprehensive platform tailored for AI developers, enabling them to manage, enhance, and secure Large Language Model (LLM) chatbots effectively. It features a variety of tools, such as conversation tracking and feedback mechanisms, analytics to assess costs and performance, debugging utilities, and a prompt directory that promotes version control and team collaboration. The platform supports multiple LLMs and frameworks, including OpenAI and LangChain, and provides SDKs designed for both Python and JavaScript environments. Moreover, Lunary integrates protective guardrails to mitigate the risks associated with malicious prompts and safeguard sensitive data from breaches. Users have the flexibility to deploy Lunary in their Virtual Private Cloud (VPC) using Kubernetes or Docker, which aids teams in thoroughly evaluating LLM responses. The platform also facilitates understanding the languages utilized by users, experimentation with various prompts and LLM models, and offers quick search and filtering functionalities. Notifications are triggered when agents do not perform as expected, enabling prompt corrective actions. With Lunary's foundational platform being entirely open-source, users can opt for self-hosting or leverage cloud solutions, making initiation a swift process. In addition to its robust features, Lunary fosters an environment where AI teams can fine-tune their chatbot systems while upholding stringent security and performance standards. Thus, Lunary not only streamlines development but also enhances collaboration among teams, driving innovation in the AI chatbot landscape.

Superagent is an open-source platform dedicated to enhancing AI safety and agent development, aimed at aiding developers and organizations in the creation, deployment, and protection of AI-driven applications and assistants by embedding crucial safety protocols, runtime security measures, and compliance regulations within their agent workflows. It provides specialized models and APIs, including Guard, Verify, and Redact, which are effective in thwarting prompt injections, preventing malicious tool usage, stopping data leaks, and ensuring safe outputs in real-time; additionally, red-teaming assessments scrutinize production systems for potential vulnerabilities and offer practical strategies for remediation. By facilitating seamless integration with existing AI systems at both inference and tool-call levels, Superagent can meticulously filter inputs and outputs, remove sensitive information such as personally identifiable information (PII) and protected health information (PHI), enforce policy rules, and thwart unauthorized actions before they can occur. The platform further bolsters security and engineering processes by delivering extensive observability, live trace logs, comprehensive policy controls, and thorough audit trails, which empower teams to sustain rigorous oversight of their AI systems consistently. Ultimately, Superagent equips organizations to adeptly navigate the challenges of AI safety, fostering a responsible approach to the deployment of cutting-edge technologies, while also promoting ethical standards in artificial intelligence practices. This commitment to safety and responsibility positions Superagent as a crucial ally in the evolving landscape of AI development.

F5 AI Guardrails is a comprehensive AI security and governance solution built to protect AI applications, large language models, autonomous agents, and the sensitive data they access. The platform delivers runtime security controls that help organizations manage the growing risks associated with AI deployments in production environments. It provides protection against adversarial threats such as prompt injection, jailbreak attacks, harmful content generation, unauthorized actions, and model manipulation attempts. Organizations can define and enforce security policies that govern how AI systems interact with users, applications, and enterprise data sources. Real-time inspection and distributed data protection capabilities help prevent sensitive information exposure, policy violations, and compliance breaches across AI ecosystems. The platform supports customizable guardrails that can be tailored to specific operational, regulatory, and business requirements. Automated compliance tools assist organizations in aligning AI operations with frameworks such as GDPR, HIPAA, and the European Union AI Act while maintaining detailed audit trails. Advanced observability features provide continuous visibility into AI interactions, allowing teams to investigate incidents, assess risks, and strengthen governance practices. Dynamic model routing and low-latency security enforcement ensure that protection measures do not negatively impact application performance. The solution is designed to work across a wide range of enterprise and open-source AI models, making it adaptable to evolving technology environments. By combining threat mitigation, data protection, compliance management, and operational visibility, F5 AI Guardrails enables organizations to deploy and scale AI systems with greater confidence and control.

display.dev acts as a secure platform for publishing artifacts created by agents, ensuring that every report, dashboard, specification, design prototype, or document is stored in a trustworthy and accessible manner. Even though agents can generate high-quality artifacts that include interactive charts, dynamic filters, hover states, and professional layouts, the act of sharing these creations can often hinder the user experience due to the common use of screenshots, raw HTML files, collapsed documents, public links, or complicated deployment methods. To solve this problem, display.dev enables users to securely publish any HTML or Markdown artifact behind company authentication with just a single command, a concise sentence in an agent's workflow, or a straightforward web upload. Once an artifact is published, viewers can easily access a permanent link, log in using their Google or Microsoft work accounts, or use a one-time password to see the artifact exactly as intended. The platform also works smoothly with Claude Code, Codex, Cursor, Claude Desktop, shell scripts, and any other tools that can produce HTML or Markdown content, making it a flexible option for a variety of users. This functionality ensures that sharing and collaborating on these artifacts can happen without sacrificing quality or usability, which significantly boosts overall workflow efficiency. Furthermore, this streamlined process contributes to a more cohesive team environment by simplifying access and enhancing collaboration on shared resources.

Snapper functions as an all-encompassing security framework designed specifically for AI agents, focusing on the governance and safeguarding of organizations that deploy AI across a multitude of applications, networks, and systems. It enforces runtime regulations by meticulously examining each action performed by an agent, including interactions with tools, API requests, and data access demands, before they are executed, employing a sophisticated, multi-layered, policy-driven rule engine. Furthermore, Snapper offers a comprehensive overview of AI activities by scrutinizing network traffic, browser activity, DNS queries, and active processes to detect unauthorized tools and concealed AI applications. In addition, it takes proactive steps to intercept outgoing requests to large language models through SDK wrappers and a network proxy, enabling real-time assessment, redaction, and documentation of sensitive data. To bolster its protective capabilities, Snapper incorporates advanced threat detection systems capable of identifying prompt injection strategies, exploit chains, abnormal behaviors, and intricate attack patterns, using behavioral baselines, kill chain analysis, and an integrated trust scoring framework for enhanced security. This combination of features makes Snapper an invaluable resource for organizations striving to manage the inherent risks linked to AI implementation while ensuring the integrity of their operations. Ultimately, the platform not only mitigates potential threats but also empowers organizations to confidently leverage AI technology.

Warestack is a cutting-edge platform powered by AI that focuses on enhancing release security by seamlessly integrating with your GitHub organization and implementing customized, context-aware guardrails at each stage of the development lifecycle. Users can express their protection protocols using simple language—for instance, requiring approvals for any pull requests that aren’t hotfixes or banning deployments on Fridays—while Warestack automatically recognizes or blocks high-risk actions and monitors activities like pull requests, issues, deployments, and workflow executions in real-time, all displayed in a unified dashboard. Additionally, the platform is compatible with widely-used tools such as GitHub, Slack, and Linear, delivering smart alerts and notifications, along with one-click access to audit logs and reports tailored to meet SOC-2 and compliance standards. Moreover, Warestack can easily adjust to diverse teams and repositories by applying scoped rules and role-based enforcement, utilizing a transparent open-source rule engine known as Watchflow that simplifies policy creation. This flexibility allows organizations to uphold rigorous security and compliance levels in their development environments while tailoring their protection strategies to fit their specific needs. As a result, teams can work more efficiently, knowing their processes are safeguarded against potential risks.

LLM Guard provides a comprehensive array of safety measures, such as sanitization, detection of harmful language, prevention of data leaks, and protection against prompt injection attacks, to guarantee that your interactions with large language models remain secure and protected. Designed for easy integration and deployment in practical settings, it operates effectively from the outset. While it is immediately operational, it's worth noting that our team is committed to ongoing improvements and updates to the repository. The core functionalities depend on only a few essential libraries, and as you explore more advanced features, any additional libraries required will be installed automatically without hassle. We prioritize a transparent development process and warmly invite contributions to our project. Whether you're interested in fixing bugs, proposing new features, enhancing documentation, or supporting our cause, we encourage you to join our dynamic community and contribute to our growth. By participating, you can play a crucial role in influencing the future trajectory of LLM Guard, making it even more robust and user-friendly. Your engagement not only benefits the project but also enriches the overall experience for all users involved.

asqav stands out as an innovative platform dedicated to the governance and security of artificial intelligence, ensuring that AI agents are consistently prepared for audits through real-time monitoring, enforcement, and a dependable log of every action taken. It boasts an efficient SDK that allows developers to seamlessly integrate governance capabilities into their AI agents with minimal code, enabling thorough oversight throughout the entire AI activity lifecycle. The platform also employs behavioral analysis to detect potential issues such as drift, exceeded rate limits, and scope violations, along with advanced threat detection systems that identify risks like prompt injections, leaks of sensitive data, and harmful outputs. Policy enforcement is facilitated by customizable “policy gates,” which establish specific rules for each agent, perform preflight evaluations, and offer dynamic approvals prior to any actions, ensuring that agents operate within defined boundaries. Moreover, asqav strengthens security with automated incident response functionalities that permit the suspension, isolation, or escalation of agents assessed as high-risk, thereby creating a comprehensive framework for maintaining accountability and safety in AI applications. Through these features, asqav not only protects AI operations but also fosters confidence in their use across a multitude of industries, thereby enhancing the overall efficacy and reliability of AI technologies. Ultimately, asqav serves as a crucial ally in the responsible deployment of AI, championing best practices in governance and security.

Acontext functions as a holistic platform tailored for AI agents, facilitating the storage of diverse multi-modal messages and artifacts, while also monitoring the task statuses of these agents. Utilizing a Store → Observe → Learn → Act framework, it identifies successful execution patterns, allowing for autonomous agents to boost their intelligence and achieve increased success over time. Benefits for Developers: Minimized Repetitive Tasks: Developers can effortlessly integrate multi-modal context and artifacts without the complexity of configuring systems like Postgres, S3, or Redis; this is accomplished with minimal coding required. Acontext relieves developers from the tedious process of extensive configuration, saving them valuable time. Self-Adapting Agents: In contrast to Claude Skills, which depend on rigid rules, Acontext enables agents to learn from past experiences, drastically reducing the need for continuous manual adjustments and fine-tuning. Streamlined Implementation: Being open-source, it offers a one-command setup, simplifying deployment and making installation straightforward. Enhanced Efficiency: By improving agent performance and decreasing the number of operational steps, Acontext drives down costs while boosting overall results. Furthermore, the platform’s capacity for continuous adaptation ensures that agents remain proficient in an ever-evolving landscape, solidifying its role as an essential tool for developers seeking to optimize AI agent capabilities.

Cisco AI Defense serves as a comprehensive security framework designed to empower organizations to safely develop, deploy, and utilize AI technologies. It effectively addresses critical security challenges, such as shadow AI, which involves the unauthorized use of third-party generative AI tools, while also improving application security through enhanced visibility into AI resources and implementing controls that prevent data breaches and minimize potential threats. Key features of this solution include AI Access for managing third-party AI applications, AI Model and Application Validation that conducts automated vulnerability assessments, AI Runtime Protection offering real-time defenses against adversarial threats, and AI Cloud Visibility that organizes AI models and data sources across diverse distributed environments. By leveraging Cisco's expertise in network-layer visibility and continuous updates on threat intelligence, AI Defense ensures robust protection against the evolving risks associated with AI technologies, thereby creating a more secure environment for innovation and advancement. Additionally, this solution not only safeguards current assets but also encourages a forward-thinking strategy for recognizing and addressing future security challenges. Ultimately, Cisco AI Defense is a pivotal resource for organizations aiming to navigate the complexities of AI integration while maintaining a solid security posture.

Facilitate the creation, storage, protection, inspection, copying, and management of container images and artifacts through a fully managed, geo-redundant OCI distribution instance. Effortlessly connect diverse environments, including Azure Kubernetes Service and Azure Red Hat OpenShift, along with various Azure services such as App Service, Machine Learning, and Batch. Thanks to the geo-replication feature, users can effectively manage a unified registry that operates across several regions. The OCI artifact repository supports the inclusion of helm charts, singularity compatibility, and new formats that adhere to OCI standards. Enhancing operational efficiency, automated workflows for building and updating containers—including base image revisions and scheduled tasks—are implemented. Comprehensive security measures are put in place, incorporating Azure Active Directory (Azure AD) authentication, role-based access control, Docker content trust, and integration with virtual networks. Azure Container Registry Tasks streamline the building, testing, pushing, and deploying of images to Azure, leading to a more efficient workflow. This holistic management strategy not only fosters improved collaboration but also significantly shortens the development lifecycle within cloud ecosystems, ultimately leading to faster project completions and greater innovation.

CrowdStrike Falcon AI Detection and Response (AIDR) is an all-encompassing security solution designed to protect against the rapidly shifting landscape of AI-related attacks by providing real-time visibility, detection, and response capabilities across diverse AI systems, users, and their interactions. This innovative platform offers a unified perspective on how both human employees and AI agents utilize generative AI, clarifying the relationships among users, prompts, models, agents, and the supporting infrastructure, while maintaining extensive runtime logs for monitoring, compliance, and investigative needs. By continuously tracking AI activities across various endpoints, cloud environments, and applications, organizations can uncover insights into data flows within AI systems and understand the operational boundaries of agents. AIDR excels at recognizing and mitigating AI-specific threats, such as prompt injections, jailbreak attempts, malicious actors, harmful outputs, and unauthorized interactions, leveraging behavioral analysis and integrated threat intelligence. Furthermore, the platform enhances proactive threat management, enabling organizations not only to react to incidents but also to foresee and address potential vulnerabilities within their AI environments. As a result, AIDR empowers organizations to maintain a robust security posture in the face of evolving AI threats while fostering trust in their AI implementations.

GSD 2 is an AI development framework built to make software engineering with AI agents more structured, reliable, and practical. The framework helps teams move beyond basic chat-based coding assistance by introducing a clearer process for defining work, managing context, executing tasks, and validating results. It focuses on turning software requests into organized workflows that AI agents can follow with less ambiguity. GSD 2 supports the use of persistent artifacts, specifications, work contracts, traceability, and review steps to improve the quality of AI-assisted development. This makes it useful for teams that want to reduce the gap between what they asked an agent to build and what actually gets implemented. The framework also encourages developers to maintain oversight, helping prevent overreliance on generated code or documentation. By emphasizing context management, GSD 2 can help AI agents make better decisions based on the project’s goals, constraints, and existing codebase. Its process-driven approach is especially valuable for complex projects where unclear prompts can lead to inconsistent or incomplete results. Teams can use GSD 2 to organize planning, execution, testing, and review in a way that fits real software delivery workflows. The framework reflects a broader shift in AI software development from prompt experimentation toward repeatable engineering systems. GSD 2 helps developers and organizations make AI coding agents more useful, accountable, and aligned with production-quality development practices.

We build confidence and uphold integrity across the entire software development life cycle by providing thorough, cryptographically verifiable tracking and provenance for all artifacts, actions, and dependencies, efficiently and at scale. Our system utilizes the open-source immudb to deliver a rapid, immutable storage solution. It integrates smoothly with existing programming languages and CI/CD workflows. With Codenotary Cloud, every organization, developer, automation engineer, and DevOps professional can safeguard all stages of their CI/CD pipeline. Employing Codenotary Cloud® enables you to create immutable, tamper-resistant solutions that meet auditor criteria and adhere to relevant regulations and legal standards. The Codenotary Trustcenter empowers any organization, developer, automation engineer, or DevOps specialist to bolster the security of their CI/CD pipeline phases. Additionally, the attestation process—comprising notarization and validation of each step in the pipeline, alongside results from vulnerability assessments—is managed through a tamper-proof and immutable service, ensuring compliance with Levels 3 and 4 of the Supply-chain Levels for Software Artifacts (SLSA). This comprehensive framework not only fortifies security but also fosters accountability and transparency throughout the software development lifecycle. Moreover, it provides peace of mind to stakeholders by ensuring that all software components are trustworthy and can be traced back to their origins.

Buzz acts as a self-hosted platform designed to enhance teamwork between humans and AI agents within a shared digital space, all overseen by a team-operated relay. This innovative workspace consolidates various elements such as discussions, automated agents, workflows, repositories, documents, searches, and more into a unified system that adheres to a single identity framework and maintains a complete event log. Every interaction—including messages, reactions, workflow advancements, approvals, updates to canvases, huddles, or Git actions—is carefully recorded as a cryptographically signed Nostr event, providing both individuals and processes with a reliable audit trail. Unlike conventional bots, the agents in Buzz are regarded as integral team members; they can be added to channels just like any other colleague, possessing unique keys and designated memberships, which allows them to perform a variety of functions such as opening repositories, submitting patches, reviewing code, executing workflows, altering canvases, collaborating with fellow agents, creating channels, participating in voice huddles, and linking the right people to specific tasks. In addition, Buzz facilitates project history searches, offering users pertinent answers along with supporting threads, patches, runs, and approvals, thereby significantly improving the collaborative experience. By cultivating a connected environment, Buzz not only enhances efficiency but also empowers teams to tap into the combined potential of human creativity and AI capabilities. This dual approach fosters innovation and productivity, making it a valuable tool for any modern team.

Overseer AI is an advanced platform designed to guarantee that the content produced by artificial intelligence is both secure and precise, aligning with guidelines set by users. It automates compliance enforcement by following regulatory standards through customizable policy rules, and its real-time moderation feature actively curbs the spread of harmful, toxic, or biased AI-generated content. Moreover, Overseer AI aids in debugging AI outputs by rigorously testing and monitoring responses to ensure alignment with specific safety policies. The platform promotes governance driven by policy by implementing centralized safety measures across all AI interactions, thereby cultivating trust in AI systems through safe, accurate, and brand-consistent outputs. Serving a variety of sectors including healthcare, finance, legal technology, customer support, education technology, and ecommerce & retail, Overseer AI offers customized solutions that ensure AI responses meet the particular regulations and standards relevant to each field. Additionally, developers are provided with comprehensive guides and API references, which streamline the incorporation of Overseer AI into their applications and enhance the user experience. This holistic strategy not only protects users but also empowers businesses to harness AI technologies with assurance, ultimately leading to more innovative applications across industries. As organizations continue to adopt AI solutions, Overseer AI stands out as a critical resource for maintaining integrity and compliance in the evolving digital landscape.

Peta acts as a sophisticated control plane for the Model Context Protocol (MCP), facilitating, securing, regulating, and supervising the interactions between AI clients and agents with external resources, data, and APIs. The platform incorporates a zero-trust MCP gateway, a secure vault, a managed runtime environment, a policy engine, human-in-the-loop approvals, and extensive audit logging into a unified solution, allowing organizations to enforce detailed access controls, protect sensitive credentials, and track all interactions performed by AI systems. Central to Peta is Peta Core, which serves as both a secure vault and gateway, responsible for encrypting credentials, generating ephemeral service tokens, ensuring identity verification and policy compliance for each request, managing the lifecycle of the MCP server through lazy loading and auto-recovery, and injecting credentials at runtime without exposing them to agents. Furthermore, the Peta Console enables teams to determine which users or agents can access specific MCP tools within defined environments, set up approval processes, manage tokens, and analyze usage data along with associated costs. This comprehensive strategy not only bolsters security but also promotes effective resource management and accountability across AI operations, ultimately leading to improved operational efficiency and enhanced oversight. By integrating these functionalities, Peta establishes a robust foundation for organizations seeking to optimize their AI-driven initiatives.

Highly available and fast artifact repositories and container registries can greatly improve the productivity and satisfaction of development teams, operations personnel, and customers. Dist offers a reliable and user-friendly solution for the secure distribution of Docker container images and Maven artifacts to your team, systems, and clients. Our specially engineered edge network ensures optimal performance, no matter where your team members or customers are situated. With Dist being fully managed in the cloud, you can depend on us for operations, maintenance, and backups, allowing you to focus on scaling your business. Access to repositories can be customized through user and group permissions, enabling every user to refine their access via access tokens. In addition, all artifacts, container images, and their associated metadata are safeguarded with encryption both during storage and transmission, ensuring that your data remains secure and private. By emphasizing these essential features, Dist not only secures your assets but also boosts overall efficiency within your organization. Furthermore, our commitment to continuous improvement ensures that we adapt to the evolving needs of your business, setting the foundation for long-term success.