Alternatives to Maetra

BAND creates robust interaction frameworks designed for enterprise-level applications of distributed AI agents. The platform facilitates immediate, collaborative interactions among both agents and humans, incorporating a runtime control plane that upholds policies, defines authority limits, and ensures transparency across diverse systems. Additionally, BAND empowers developers, engineering teams, and leaders of enterprise platforms who are managing multi-agent ecosystems spanning internal infrastructures, SaaS solutions, and environments shared with partners. This support enhances operational efficiency and fosters innovation within complex organizational structures.

JetStream Security serves as a governance platform focused on security, enabling enterprises to gain comprehensive visibility, control, and responsibility over their AI systems by transforming them from unclear, disjointed applications into managed and traceable infrastructures. Functioning as a unified control center, it integrates identity management, operational governance, monitoring, and financial management into one cohesive system, empowering organizations to “monitor every AI action, associate actions with accountable individuals, and ensure workflows stay within authorized limits” while applying policies during runtime. Furthermore, it incorporates agentic identity, linking human, agentic, and non-human identities to specific actions and access rights, thereby ensuring that each invocation, tool usage, or workflow can be tracked and governed according to least-privilege access standards. By maintaining ongoing runtime governance, JetStream continuously evaluates actual AI behavior against pre-approved frameworks, utilizing immutable logging and real-time monitoring to identify deviations, thereby reinforcing security and compliance. This robust approach not only enhances accountability but also supports organizations in navigating the complexities of AI governance effectively.

asqav is a cutting-edge platform focused on AI governance and security, aimed at ensuring that AI agents are always prepared for audits by offering real-time oversight, enforcement, and a reliable record of each action performed by the agents. It features a streamlined SDK that empowers developers to embed governance functionalities directly into their AI agents with minimal code, facilitating comprehensive monitoring throughout the entire lifecycle of AI activities. Additionally, the platform incorporates behavioral analysis to identify potential problems like drift, rate limits, and scope breaches, as well as sophisticated threat detection mechanisms that can recognize issues such as prompt injections, leaks of sensitive information, harmful outputs, and other dangers. Policy enforcement is achieved through customizable “policy gates,” which implement specific rules for each agent, conduct preflight assessments, and provide dynamic approvals before any actions are taken, thereby guaranteeing that agents function within established parameters. Furthermore, asqav enhances security with automated incident response features, allowing for the suspension, isolation, or escalation of agents deemed risky, all of which contribute to a robust framework for maintaining AI accountability and safety. In this way, asqav not only safeguards AI operations but also promotes trust in their deployment across various sectors.

Kastra serves as the crucial authorization framework for AI systems, determining the permissions of agents, models, and tools prior to their execution. Positioned along the execution path of all interactions such as prompts, tool calls, shell commands, database operations, and API requests, it evaluates each action based on deterministic, attribute-driven policies, rendering decisions to allow, deny, redact, or escalate in less than a millisecond. In contrast to monitoring solutions that only track AI actions post-execution, Kastra proactively prevents unauthorized activities before they can impact any tool, API, database, or production environment. Its comprehensive control plane integrates a policy engine, edge decision-making capabilities, various integrations, and a tamper-proof evidence vault that securely signs each decision for auditing and replay purposes. Furthermore, with Kastra Edge, local enforcement is extended to developer environments, safeguarding coding agents such as Claude Code, Cursor, and Codex CLI from harmful commands, unauthorized data extraction, unsafe file modifications, and improper tool usage. This proactive approach to authorization not only enhances security but also ensures compliance and accountability in AI-driven processes.

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.

Tangerin AI serves as a governance platform for artificial intelligence in Brazil, addressing a critical issue that many organizations struggle to resolve: identifying which AI tools—whether officially sanctioned or not, often referred to as Shadow AI—are employed within the organization, who is using them, the associated data risks, and the evidence required for auditing purposes. The data collection process can be accomplished in two distinct ways: through a lightweight endpoint agent compatible with Windows, macOS, and Linux, or through the agentless ingestion of existing logs from Next-Generation Firewalls (NGFW), Secure Service Edge (SSE), and Security Information and Event Management (SIEM) systems. Each signal collected is matched against a unique catalog containing over 6,000 AI tools, detailing aspects such as data risk, processing location, retention policies, and intended uses. Furthermore, every tool is categorized based on established policies as either permitted, restricted, or banned; employees are required to digitally acknowledge the AI usage policy, and the compliance module encompasses 24 different frameworks, including LGPD, ISO 42001, EU AI Act, GDPR, and ISO 27001, complete with automatic evidence crosswalks and views tailored for external auditors. In addition to tracking which AI tools are utilized, the platform logs the timing of usage and the specific workstation involved, while deliberately excluding any conversation content, prompts, or files from its records. This approach reflects a deliberate architectural choice rather than a mere configuration adjustment.

Jozu functions as an AI-driven platform focused on securing supply chains by validating artifacts prior to their execution, managing agent activities in real-time, and maintaining a record of all actions taken afterward. The Jozu Hub acts as a self-hosted repository for models, agents, MCP servers, and skills, ensuring that each artifact is consolidated with cryptographic signatures, attestations, thorough scanning, policy regulations, and audit trails. This platform's security analysis, tailored specifically for AI, addresses various threats including concealed executable code within model packages, compromised weights, data poisoning, prompt injection, insecure tools, and violations of licensing. Users can create policies once, which are then distributed as signed OCI artifacts, and these policies are enforced during the processes of pulling, promoting, admitting, or executing artifacts. Additionally, Jozu Agent Guard operates in conjunction with workloads across servers, desktops, edge devices, and isolated systems, implementing local filtering for prompts and input-output, access controls for tools, requirement for approvals, and enforcement of policies in real-time. Through this comprehensive approach, Jozu not only enhances security but also ensures a robust framework for managing and safeguarding AI-related artifacts throughout their lifecycle.

Barndoor serves as a robust management layer for data and access, ensuring that artificial intelligence systems interact securely with enterprise data and infrastructure. Acting as a unified control center, it oversees AI agents and applications, empowering organizations to set policies, automatically enforce access rules, and retain comprehensive oversight of AI tool operations within business frameworks. Moving beyond traditional identity-based permissions, Barndoor employs context-aware governance, which allows administrators to dictate the allowed actions of an AI agent by considering variables such as the user in charge of the agent, the system being accessed, the nature of the data, and the task at hand. This system assesses each AI request in real time to apply policies before actions are undertaken, thereby thwarting unsafe or unauthorized operations from affecting internal systems or altering sensitive data. Furthermore, by integrating such a nuanced approach to governance, organizations can enhance both security and compliance, ultimately fostering a more trustworthy AI ecosystem.

Prisma AIRS AI Runtime Security is a specialized solution aimed at safeguarding applications, agents, models, and data that utilize LLM technology during their operational phases, providing real-time oversight, assurance, and governance throughout the AI lifecycle. This system continuously observes AI behavior, implementing protective measures that identify and mitigate threats which conventional security tools often overlook, such as prompt injection, harmful code, toxic outputs, data leakage, and unauthorized or unsafe actions. It empowers organizations to uncover all AI assets in operation, including shadow AI, while gaining insights into the interactions among agents, applications, and models across various environments. By consistently evaluating risk through the testing of AI systems, managing permissions, and monitoring the security posture in real-time, it incorporates controls that prevent manipulation and exposure during runtime engagements. With its adaptive defense mechanism, it protects against both evolving threats and zero-day vulnerabilities, leveraging real-time analysis of inputs, outputs, and execution processes. Ultimately, this innovative solution enhances an organization's ability to maintain a secure AI framework while promoting trust and compliance in AI deployments.

Preloop serves as an open-source control plane designed for AI agents that perform tangible actions. It integrates a multi-layered security approach featuring an MCP firewall for managing tool access, an AI model gateway that ensures cost-effectiveness, safety, and accountability, along with policy-as-code that incorporates human oversight, all while providing runtime session visibility and audit trails—all within a self-hosted environment. Given the rapid capabilities of AI agents to deploy code, modify infrastructure, manage financial transactions, access production data, and incur model costs almost instantaneously, Preloop empowers teams to regulate agent activities, monitor expenditures, and determine which actions necessitate human consent. It is compatible with a variety of tools such as OpenClaw, Hermes, Claude Code, Codex CLI, Cursor, Gemini CLI, Windsurf, Cline, OpenCode, and any agents that adhere to MCP standards. Additionally, access rules can evaluate not only the tool names but also arguments and context, utilizing CEL expressions to establish detailed conditions. Furthermore, teams have the flexibility to initiate with observability features and progressively introduce approval and denial protocols without the need for SDKs or extensive modifications to existing applications, thus streamlining the implementation process. This comprehensive approach ensures that organizations remain in control of their AI agents' functionalities and impacts.

Enkrypt AI is a specialized platform designed for enterprise-level security, compliance, and governance in the realm of artificial intelligence, focusing particularly on safeguarding large language models, AI agents, multimodal systems, and machine-critical processes. Catering to industries such as finance, healthcare, insurance, and government, Enkrypt AI empowers organizations to innovate quickly while ensuring safety and maintaining a competitive edge. The platform addresses the entire spectrum of AI security through several key features: Guardrails: With ultra-low latency (under 50 milliseconds), policy-driven guardrails effectively mitigate risks associated with prompt injections, unauthorized data exposure, hazardous outputs, and non-compliant behavior of agents in real-time. Red Teaming: The system implements policy-driven multimodal attack simulations for LLMs and AI agents prior to their deployment in order to identify vulnerabilities. MCP Security: The MCP Scan Hub and Secure MCP Gateway offer comprehensive protection for MCP servers, tools, and agent toolchains throughout the entire process. Compliance: Ongoing monitoring ensures adherence to standards such as NIST AI RMF, OWASP LLM Top 10, the EU AI Act, HIPAA, and FINRA, with certifications including ISO 27001 and SOC 2 Type II. Recognized as a Gartner Cool Vendor for 2025, Enkrypt AI sets itself apart in the industry.

XecGuard, developed by CyCraft, serves as a firewall for trustworthy and agentic AI, specifically engineered to safeguard enterprise AI systems against various threats such as prompt injection, data leakage, and unsafe outputs. Leveraging CyCraft's extensive experience in red and blue teaming within sectors like government, finance, and high-tech manufacturing, XecGuard enhances security measures by integrating AI guardrails with cybersecurity protocols, compliance safeguards, and risk management tactics, ultimately facilitating the safe adoption of enterprise AI. This innovative solution functions as a plug-and-play LoRA security module, allowing organizations to bolster their LLM defenses seamlessly without necessitating modifications to the underlying model architecture, thus ensuring rapid implementation while maintaining optimal performance. By utilizing proprietary security datasets and advanced multi-stage fine-tuning methods, XecGuard significantly improves the resilience of LLMs against adversarial attacks, malicious interventions, and unauthorized extraction of sensitive information, making it an essential component for any enterprise aiming to fortify its AI systems effectively. Furthermore, its ability to adapt quickly to emerging threats underscores its value in today’s fast-evolving technological landscape.

Tenable One 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.

Elsai Foundry serves as a governance-centric platform that facilitates the creation, deployment, and management of AI agents tailored for regulated business processes. It integrates compliance measures, redaction of PHI and PII, management of prompts, and real-time observability through ARMS into all workflows. The platform's design encompasses orchestration of multiple agents, enforcement of policies and approvals, controls involving human oversight, domain-specific intelligence, and a collection of pre-configured agents across sectors such as healthcare, life sciences, insurance, procurement, and supply chain management. By prioritizing governance, Elsai Foundry ensures that AI deployment aligns with regulatory standards while enhancing operational efficiency.

Onyx serves as a robust AI control platform designed for the discovery, protection, governance, optimization, and evaluation of AI agents and models within an organization. It provides crucial visibility for security, governance, and AI teams into both authorized and unauthorized AI activities across various environments, including SaaS applications, cloud services, endpoints, and code, encompassing aspects such as prompts, responses, and agent behaviors. The AI Security feature enhances the organization's security posture by pinpointing vulnerabilities and implementing real-time safeguards against potential threats and misuse. Meanwhile, AI Governance ensures compliance with security standards and regulatory mandates by offering opt-in coverage and allowing policy controls to be articulated in natural language. Additionally, AI Orchestration streamlines the process of deploying agents and Multi-Cloud Platforms (MCPs), while optimizing for cost, accuracy, and latency. The AI ROI component facilitates the measurement of adoption, the establishment of objectives, and the tracking of results across various departments within the organization. Furthermore, the Onyx Guardian Agent functions as an overseeing AI, perpetually identifying risks and resolving issues throughout the platform, thereby enabling organizations to effectively manage a large number of agents seamlessly. Ultimately, Onyx empowers businesses to harness the full potential of AI while maintaining control and oversight.

Lunar.dev serves as a comprehensive AI gateway and API consumption management platform designed to empower engineering teams with a singular, integrated control interface for overseeing, regulating, safeguarding, and enhancing all outbound API and AI agent interactions. This includes tracking communications with large language models, utilizing Model Context Protocol tools, and interfacing with external services across various distributed applications and workflows. It offers instantaneous insights into usage patterns, latency issues, errors, and associated costs, enabling teams to monitor every interaction involving models, APIs, and agents in real time. Furthermore, it allows for the enforcement of policies such as role-based access control, rate limiting, quotas, and cost management measures to ensure security and compliance while avoiding excessive usage or surprise expenses. By centralizing the management of outbound API traffic through features like identity-aware routing, traffic inspection, data redaction, and governance, Lunar.dev enhances operational efficiency. Its MCPX gateway further streamlines the management of multiple Model Context Protocol servers by integrating them into a single secure endpoint, providing robust observability and permission oversight for AI tools. Thus, the platform not only simplifies the complexity of API management but also significantly boosts the ability of teams to harness AI technologies effectively.

Unity AI Gateway offers a unified framework for governance, monitoring, and expenditure management across various AI systems within an enterprise, enabling organizations to oversee agents, tools, models, MCPs, and AI frameworks from a single, regulated interface. It ensures consistent governance across AI services such as Databricks-hosted AI, external models, coding agents, and agent harnesses, while avoiding vendor lock-in for teams. Policies that are aware of user identities regulate agent access, permissible actions, and tool usage, while integrated, custom, and third-party safeguards maintain safety and compliance throughout prompts, responses, and interactions. This system records prompts, traces, tool interactions, payload logs, audit trails, token usage, and policy decisions to facilitate behavior monitoring, incident investigations, and compliance assistance. Furthermore, centralized financial controls enable tracking of consumption across various users, teams, applications, agents, and providers, incorporating budgets, rate limits, and strict spending caps to optimize resource allocation. By streamlining these processes, Unity AI Gateway empowers organizations to harness AI technologies effectively while adhering to their governance and budgetary frameworks.

OneTrust AI Governance is a comprehensive tool designed to safeguard the return on investment in artificial intelligence by converting AI-related risks into actionable controls, thereby enabling teams to effectively govern while maintaining agility. It bridges the gap between enterprise governance and technical realities, allowing organizations to accelerate AI implementation, mitigate risks, and uphold trust as AI technologies advance in real-world applications. The platform assists teams in organizing their AI systems and evaluating risks through a central inventory that tracks models, datasets, agents, and vendors, while also designating ownership, lifecycle status, and understanding interdependencies of components. By utilizing global frameworks such as the EU AI Act, NIST, and ISO 42001, it standardizes the process of identifying AI risks and features automated workflows for risk categorization based on use cases, systems, or components, along with mapped risk and control frameworks for continuous compliance. Additionally, OneTrust enhances the efficiency of approvals, attestations, scoping, evidence collection, and reporting that is ready for audits through customizable intake and approval workflows. This ensures that organizations can maintain a robust governance structure while swiftly adapting to the fast-evolving landscape of AI technologies.

Superagent is an open-source platform focused on AI safety and agent development, designed to assist developers and organizations in creating, deploying, and safeguarding AI-driven applications and assistants by incorporating essential safety measures, runtime security, and compliance controls into their agent workflows. It features purpose-trained models and APIs—such as Guard, Verify, and Redact—that effectively prevent prompt injections, malicious tool usage, data leaks, and unsafe outputs in real-time, while red-teaming tests evaluate production systems for vulnerabilities and provide actionable remediation strategies. Superagent seamlessly integrates with current AI systems at both inference and tool-call levels, enabling it to filter inputs and outputs, eliminate sensitive information like personally identifiable information (PII) and protected health information (PHI), enforce policy constraints, and prevent unauthorized actions before they can take place. Furthermore, it enhances security and engineering operations by offering comprehensive observability, live trace logs, policy controls, and detailed audit trails, ensuring that teams can maintain robust oversight of their AI systems at all times. Ultimately, Superagent empowers organizations to navigate the complexities of AI safety while facilitating the responsible use of innovative technologies.

OpenBox serves as a robust AI governance platform tailored for enterprises, aiming to ensure that AI systems remain transparent, auditable, and securely deployable on a large scale by instituting real-time monitoring of every action taken by agents and interactions within the system. By offering a cohesive governance framework, it amalgamates identity, policy, risk management, and compliance into a singular runtime environment, thereby addressing the common issue of fragmentation associated with using multiple tools and allowing organizations to maintain standardized oversight over AI activities. Seamlessly integrating with current AI workflows via a streamlined SDK, it necessitates no modifications to existing architectures while providing immediate insights into the operational behavior, decision-making processes, and inter-system communications of AI agents. Furthermore, OpenBox proactively supervises and assesses each action prior to its execution, implementing policy enforcement and regulatory evaluations instantaneously to avert any non-compliant or high-risk activities, ensuring a more preventative approach rather than simply responding to issues post-factum. This proactive stance not only enhances compliance but also fosters a culture of accountability in AI operations.

Tuning Engines serves as a comprehensive AI control and governance framework designed for teams engaged in building production intelligence that spans various models, agents, tools, and specialized systems. This platform consolidates the entire AI lifecycle into a single, regulated environment, encompassing aspects like inference, model routing, fallback strategies, fine-tuning tasks, datasets, evaluations, model imports and exports, custom models, agents, MCP servers, reusable skills, guardrails, AGT YAML policies, data capture, runtime tracing, usage analytics, API management, billing, team roles, and numerous integrations. Developers benefit from APIs compatible with OpenAI, routes aligned with Anthropic, CLI workflows, MCP access, and seamless coding-agent integrations, along with a comprehensive resource catalog for models, agents, tools, and skills. Moreover, teams have the ability to link various AI workflows, including Claude Code, OpenCode, Aider, Cline, Roo, Continue.dev, Cursor, VS Code, Windsurf, and more, all through a singular, governed platform that enhances collaboration and efficiency.

Openlayer is an AI governance, evaluation, and observability platform designed for teams building traditional machine learning, generative AI, RAG, and agentic systems. The platform helps organizations test, monitor, and improve AI applications from early experimentation through production deployment. Openlayer provides more than 100 automated tests that evaluate data quality, model performance, safety, reliability, fairness, and behavior across AI workflows. Its observability capabilities give teams traceability across prompts, retrieval steps, agents, tool calls, responses, and complex multi-step execution paths. Real-time guardrails help block or reduce risks such as prompt injections, PII leakage, bias, toxicity, hallucinations, and unsafe outputs. Openlayer also supports automated model evaluations so teams can continuously assess AI systems instead of relying only on manual review. For governance teams, the platform helps operationalize responsible AI requirements and align internal processes with frameworks such as NIST and the EU AI Act. Enterprises can use Openlayer to create safer AI development practices, maintain oversight, and document how models perform over time. By combining evaluation, observability, guardrails, governance automation, and workflow traceability, Openlayer helps companies deploy AI systems with more confidence and control.

Darktrace / SECURE AI offers a comprehensive AI security solution that consolidates all AI interactions within an organization into a unified perspective, enabling teams to grasp intentions, evaluate risks, safeguard sensitive information, and ensure compliance with policies. It provides real-time monitoring of prompts, sessions, and responses across various enterprise GenAI tools like Microsoft Copilot and ChatGPT Enterprise, as well as low-code environments such as Microsoft Copilot Studio, high-code platforms like Amazon Bedrock and SageMaker, SaaS applications, and secure access service edge (SASE). Utilizing behavioral analytics, it effectively differentiates between routine business activities and notable or hazardous anomalies, thereby identifying conversational prompt attacks, harmful chaining, and other unsafe actions without solely depending on historical attack patterns. Darktrace's unique ability to learn directly from the environment it secures enables it to recognize new and AI-related threats upon their initial occurrence. This adaptive learning capability enhances its effectiveness in proactively addressing emerging security challenges within an increasingly complex technological landscape.

Ensure that AI implementation complies with corporate policies through our user-friendly AI governance control plane. By simplifying the process, you can enhance visibility and securely foster AI adoption with SurePath AI. The platform seamlessly integrates with your existing security infrastructure, private models, and enterprise data sources. It supports SSO, SCIM, and SIEM as core features. Monitor AI utilization at the network level while managing access and scrutinizing requests to prevent sensitive data leaks. Additionally, it allows for the redaction of sensitive information within requests directed at public models. The ability to modify requests in real-time promotes efficiency while minimizing risks. You can also redirect traffic to your private AI models, utilizing SurePath AI's access controls to create a custom-branded enterprise AI portal. With policy-driven controls, user requests are enriched with only the data they are authorized to access, resulting in responses that are contextually relevant to your business needs. Furthermore, user prompts are automatically optimized to ensure outputs align with your organization's strategic objectives while maintaining compliance.

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.

Agent Control represents a groundbreaking open-source framework designed to manage the behavior of AI agents on a large scale, setting a new benchmark for governance in this domain. It addresses the issue of disjointed and hardcoded checks by providing teams with a unified governance layer that enforces regulations at each step, all managed from a single control interface that can be updated dynamically without altering the agent's underlying code. Developers can easily designate any function as governable by applying the control() decorator, thereby transforming key decision points within an agent into independently regulated control points, each equipped with its own governance policies. When a decorated function runs, Agent Control assesses the input or output against the prevailing policy and generates a response that could be to deny, steer, warn, log, or allow the action. If a denial occurs, the SDK triggers a ControlViolationError, preventing any unsafe actions from being executed. This separation of policies from the actual code empowers developers to strategically position control hooks, while policy teams determine the enforcement specifics of those hooks, ensuring a collaborative approach to governance. The flexibility and robustness of Agent Control make it an invaluable tool for organizations looking to standardize AI agent governance effectively.

Rawctx serves as an AI evidence layer specifically designed for teams developing customer-facing AI assistants, copilots, and agents. It meticulously logs every response along with the officially approved meanings, source/context references, metadata from model runs, trace identifiers, correction histories, and exportable proof bundles. This feature enables teams to scrutinize the rationale behind each AI-generated answer, including the evidence and business definitions utilized, any modifications made post-review, and the current status of trust proof, whether it is anchored, pending, or local-only. Additionally, rawctx encompasses capabilities for maintaining answer audit logs, facilitating exports in JSON, CSV, or proof formats, binding source reference evidence, and implementing verification workflows that can be either public or private, catering to critical areas such as support, sales, finance, legal, and operations. Ultimately, rawctx empowers organizations to ensure accountability and transparency in their AI interactions.

Enhance your observability framework to swiftly identify data and machine learning challenges, facilitate ongoing enhancements, and prevent expensive incidents. Begin with dependable data by consistently monitoring data-in-motion to catch any quality concerns. Accurately detect shifts in data and models while recognizing discrepancies between training and serving datasets, allowing for timely retraining. Continuously track essential performance metrics to uncover any decline in model accuracy. It's crucial to identify and mitigate risky behaviors in generative AI applications to prevent data leaks and protect these systems from malicious attacks. Foster improvements in AI applications through user feedback, diligent monitoring, and collaboration across teams. With purpose-built agents, you can integrate in just minutes, allowing for the analysis of raw data without the need for movement or duplication, thereby ensuring both privacy and security. Onboard the WhyLabs SaaS Platform for a variety of use cases, utilizing a proprietary privacy-preserving integration that is security-approved for both healthcare and banking sectors, making it a versatile solution for sensitive environments. Additionally, this approach not only streamlines workflows but also enhances overall operational efficiency.

AccuroAI is an advanced platform focused on enterprise-level AI security, data protection, and governance, created to provide organizations with comprehensive oversight and management of AI tool usage within their environments. This platform consistently identifies and catalogs both approved and unauthorized AI applications, covering various areas including browsers, SaaS solutions, networks, and autonomous agents, while meticulously tracing every interaction back to the specific user, application, and intent. By functioning in real time between users and AI models, it scrutinizes both prompts and responses to identify and mitigate risks such as the exposure of sensitive information, prompt injection threats, and the generation of harmful outputs. Furthermore, it implements dynamic data loss prevention techniques that detect and redact sensitive material, including personally identifiable information, financial details, source code, and health records, ensuring that these do not reach the model while maintaining seamless workflow processes. AccuroAI also consolidates regulatory oversight with a comprehensive policy engine that ensures governance is consistently applied across both human interactions and agent activities. Through these features, organizations can enhance their security posture while effectively managing the complexities of AI deployment.

Constellation is a real-time governance infrastructure platform that helps organizations manage decision-making across teams, systems, and AI tools. It works by encoding institutional rules and cross-functional constraints into a system that evaluates every action before it is executed. This ensures that actions comply with policies related to finance, privacy, communications, and other critical areas. The platform replaces slow, manual approval processes with automated checks that maintain both speed and compliance. Constellation also generates detailed records of every decision, creating a transparent and auditable trail of actions. It is model-agnostic, meaning it can work with AI systems like Claude, OpenAI, Gemini, and others. The platform enables organizations to reduce coordination costs while improving accountability and operational efficiency. By integrating governance into the execution layer, Constellation ensures that teams and AI systems operate within defined boundaries. This allows organizations to scale decision-making confidently without increasing risk.

DesignVerse serves as an AI-driven platform for software development, establishing the contextual framework necessary for producing enterprise software within large organizations. It empowers teams to create intricate enterprise applications that are reliable by integrating design systems, architectural patterns, engineering protocols, code repositories, business documentation, workflows, and product logic into a cohesive system-wide context. Rather than producing generic prototype code, DesignVerse converts organized design frameworks into software that is ready for production while adhering to the existing rules, APIs, components, and governance of the organization. Teams can seamlessly import their established systems, translate them through reusable engineering logic, and deliver deployable user interfaces and software that comply with approved standards. This platform is specifically designed to mitigate issues such as implementation drift, fragmented execution, redundant development efforts, and discrepancies between design and production phases. Furthermore, DesignVerse enhances collaboration by ensuring that all stakeholders are on the same page throughout the software development lifecycle.

Notenic serves as a runtime orchestration and governance platform aimed at managing and securing autonomous AI agents, also known as "digital labor," in real-time scenarios where failures could lead to significant regulatory, legal, or operational repercussions. Functioning as an infrastructure layer, it integrates directly into the execution path of AI systems to enforce strict governance protocols prior to any interaction with systems of record, thus avoiding the limitations of post-output filters or controls applied at the prompt level. The platform incorporates a zero-trust runtime architecture characterized by foundational principles such as zero-persistence, which ensures no data is retained after each session, and execution-path control that enforces policies right at the moment actions are taken. This design also emphasizes independence from model context, effectively preventing any adversarial inputs from compromising governed behavior. In addition, Notenic offers a comprehensive control plane that encompasses the management of AI agents, treating them as operational units with clearly defined roles and appropriate oversight, which enhances organizational efficiency and accountability. This robust framework ultimately ensures that AI operations are conducted within a secure and compliant environment.

AICtrlNet actively implements AI governance rather than merely monitoring it. In contrast to other tools that assess or oversee AI risk, this platform takes charge by coordinating AI agents, human participants as integral contributors rather than mere approval checkpoints, and enterprise systems within a cohesive governance framework. It is adaptable to various models including OpenAI, Claude, Gemini, and local runtimes like Ollama and vLLM. The system features a 6-phase Control Spectrum that defines autonomy levels for different workflows and agents. It provides a collection of 43 agent templates tailored for specific roles and over 177 workflow templates spanning 41 industry sectors. Rather than supplanting existing automation tools, it integrates with n8n, Zapier, and Make as functional nodes. AICtrlNet is designed with compliance in mind, supporting regulatory frameworks such as HIPAA, GDPR, SOC2, and the EU AI Act through its inherent governance and accountability features. The software is available in open-core editions: the Community edition is MIT-licensed, free, and self-hostable, while the Business edition enhances governance and risk assessment with machine learning capabilities, and the Enterprise edition introduces multi-tenancy and federation options. Users can access the platform through the HitLai visual no-code interface, REST API, or MCP, ensuring flexibility and ease of use. With its robust capabilities, AICtrlNet aims to redefine the landscape of AI governance by promoting a proactive rather than reactive approach.

Singulr is a comprehensive platform designed for enterprise AI governance and security, providing a cohesive control framework that aids organizations in discovering, securing, and optimizing their AI implementations on a large scale. By tackling the widening gap between the rapid deployment of AI technologies and the constraints of governance, it offers unparalleled visibility into all AI systems utilized within the organization, which includes custom applications, integrated AI solutions, public tools, and shadow AI that often evade detection by security teams. It systematically identifies and catalogs AI resources throughout the organization, creating a real-time inventory of agents, models, and services while evaluating their associated risks through thorough contextual assessments of data management, model lineage, vulnerabilities, and compliance requirements. The platform's intelligence layer, Singulr Pulse, processes millions of AI systems, assigns risk ratings, and facilitates automated onboarding processes that significantly shorten approval timelines from weeks to mere hours, all while ensuring robust security measures are in place. This innovative approach not only enhances the efficiency of AI adoption but also empowers organizations to maintain a strong governance framework as they navigate the complexities of AI integration.

iDox.ai Guardrail serves as an immediate security measure for AI applications, designed to safeguard sensitive information from being exposed during generative AI tasks. This innovative solution functions at the endpoint, intercepting user prompts, uploaded files, and any AI interactions prior to data transmission from the device. Guardrail employs policy-driven mechanisms to identify and prevent the leakage of sensitive information, including personally identifiable information (PII), protected health information (PHI), payment card information (PCI), intellectual property, and other confidential business data. In contrast to conventional data loss prevention (DLP) systems, Guardrail is tailored specifically for AI applications. It continuously observes user engagement with AI platforms like ChatGPT, Microsoft Copilot, and Claude, applying protective measures in real-time to ensure security. Among its key features are: - Continuous monitoring of prompts and file submissions - Detection of sensitive data with AI awareness - Real-time anonymization and sanitization processes - Defense against risks associated with AI agents, such as unauthorized file access incidents (e.g., OpenClaw) - Implementation of website whitelisting and strict policy enforcement. Additionally, Guardrail enhances user confidence in utilizing AI technologies while ensuring compliance with data privacy regulations.

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.

Trail ML serves as an AI governance copilot platform designed to assist organizations in establishing reliable, compliant, and transparent AI systems by automating tedious governance and documentation activities. It consolidates a variety of essential functions such as AI registry management, policy formulation, risk assessment, automated documentation, development oversight, audit trails, and compliance workflows into a single system, allowing teams to effectively categorize and monitor all AI applications, trace decisions from initial data and model stages to final outcomes, and minimize the burden of manual documentation and governance tasks. Additionally, it incorporates various governance frameworks and templates, facilitates the development of tailored AI policies, and aids teams in recognizing and addressing risks while preparing for audits and adhering to standards like ISO 42001, as well as regulations such as the EU AI Act. Trail employs a combination of curated knowledge, risk libraries, and AI-driven automation to manage governance responsibilities, convert regulatory mandates into actionable tasks, and enhance collaboration among stakeholders, ultimately fostering a more efficient governance environment. By streamlining these processes, organizations can focus more on innovation and less on compliance concerns.

F5 AI Guardrails is an enterprise AI security platform that provides runtime protection for deployed AI models, agents, and applications across diverse environments. The solution is designed to address emerging AI risks by monitoring interactions, enforcing policies, and preventing malicious attempts to manipulate AI behavior. Organizations can use the platform to defend against prompt injection attacks, jailbreak techniques, data leakage incidents, and other adversarial threats targeting AI systems. Distributed data protection capabilities inspect AI interactions in real time and help enforce data loss prevention policies across applications and models. The platform includes automated compliance features that support frameworks and regulations such as GDPR, HIPAA, and the European Union AI Act. Advanced observability and auditing tools provide detailed records of AI activity, enabling stronger governance and accountability. F5 AI Guardrails also supports dynamic model routing and low-latency security controls to maintain operational performance while enforcing protections. Model-agnostic functionality allows organizations to secure both proprietary and open-source AI models using a unified approach. By integrating security, compliance, observability, and runtime protection, F5 AI Guardrails helps organizations confidently scale their AI initiatives.

WrangleAI is a robust platform designed for enterprises, providing essential oversight, control, and governance regarding their AI deployments and expenditures. Serving as a "control plane" for generative AI tools such as GPT-4, Claude, and Gemini, it allows organizations to track usage in real-time, gain insights into costs, monitor infrastructure, and implement spending limits to prevent excessive budgets. Additionally, WrangleAI enhances AI observability by enabling teams to discern which models are utilized, by whom, and for which objectives, while also offering intelligent workload routing to more economical models without compromising quality. The platform further incorporates governance mechanisms, including role-based access control and compliance assistance with standards like SOC 2 and ISO 27001, facilitating collaboration among finance, engineering, and leadership teams to enforce policies and receive actionable insights for optimizing AI investments. This comprehensive approach not only streamlines AI management but also empowers organizations to make informed decisions about their AI strategies.

Proofpoint AI Security is an integrated solution aimed at assisting organizations in managing, monitoring, and safeguarding the deployment of AI technologies, including large language models and autonomous agents. This platform offers insight into both approved and unapproved AI activities, allowing security teams to identify unauthorized AI tools, track prompts and responses, and analyze AI interactions with sensitive information in real-time. By utilizing intent-based detection and behavioral analysis, it effectively spots anomalies, attempts at prompt injections, and potentially dangerous interactions, while simultaneously enforcing policies during operation to avert data breaches and misuse. Furthermore, it reconstructs comprehensive AI transactions from the initial user query to the actions and results produced by the agents, ensuring organizations maintain complete traceability and are prepared for audits. With its capabilities extending to endpoints, web browsers, and AI agent connections, it facilitates detailed access governance, guaranteeing that AI systems are restricted to utilizing and sharing only the necessary information. This comprehensive control enhances the overall security posture of the enterprise as it navigates the complexities of AI system integration.

DueDel is a next-generation AI risk intelligence platform designed to streamline due diligence by automating research and surfacing early warning signals across financial, legal, and reputational domains. Powered by advanced NLP and sentiment analysis, the system identifies subtle risk patterns that traditional manual research often misses. Users can run comprehensive scans by entering their target entity and keywords, after which DueDel generates consolidated reports featuring red flags, stakeholder mapping, litigation traces, and tone analytics. Executive summaries turn complex findings into actionable insights, allowing leadership teams to make confident decisions more quickly. DueDel reduces manual research time by up to 80%, enabling analysts to focus on strategy rather than data gathering. It integrates easily with existing workflows, making it suitable for investment firms, compliance departments, and risk management teams. The platform is backed by founders with deep expertise in AI safety, LLM research, and financial risk governance. Award recognition and partnerships with major financial institutions highlight its credibility in transforming modern risk intelligence.

OpenWeave serves as a governance mechanism for AI agents and autonomous systems, functioning as a server-enforced state machine that regulates the actions of AI agents and the timing of those actions. Users can outline workflows comprising states, transitions, and authorized triggers; the backend consistently enforces transitions with a strict 403 error, while pivotal states require human approval, effectively preventing bots from acting until a human intervenes. The monitoring feature provides insights into agent activities, ensuring that OpenWeave stops inappropriate actions before they occur. Instead of hardcoding transitions, agents learn about permissible transitions through the API, ensuring that every bot possesses a verifiable identity, and all modifications are logged in an immutable audit trail. The system offers integration through a REST API and a remote MCP server, making it a vital resource for AI-agent developers, AgentOps/MLOps, and platform teams. This comprehensive framework not only enhances security but also streamlines the management of AI workflows, ultimately contributing to safer and more efficient autonomous systems.

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.

Traccia is a comprehensive observability and governance platform designed specifically for production AI agents, leveraging OpenTelemetry for enhanced insights. It provides engineering teams with thorough visibility into various aspects, including every LLM call, tool usage, decision-making process, token management, and expenditure, across different frameworks such as LangChain, CrewAI, OpenAI Agents SDK, AutoGen, and LlamaIndex. In addition to tracking, Traccia empowers organizations to establish governance over their AI systems through runtime policies that identify and mitigate unsafe behaviors, control excessive costs, manage model usage restrictions, and prevent personal identifiable information (PII) breaches prior to any production incidents. The platform’s features, including precise cost attribution, monitoring of agent health, a consolidated agent registry, and generation of evidence for compliance with the EU AI Act, make it an ideal choice for enterprise-level implementations. Moreover, with its lightweight open-source SDK in conjunction with a managed platform, Traccia supports teams in the development, debugging, monitoring, and governance of AI agents at scale, while ensuring freedom from vendor lock-in by utilizing standard OpenTelemetry instrumentation. This versatility allows organizations to maintain control over their AI initiatives while ensuring compliance and operational efficiency.

Velatir serves as a platform for AI governance, aimed at connecting sophisticated AI technologies with necessary compliance and human oversight. Our approach incorporates human-in-the-loop governance that transforms regulatory challenges into opportunities for enhancement. By leveraging a smart policy engine, intelligent routing mechanisms, and streamlined approval workflows through platforms like Slack, Teams, email, or the web, we guarantee that AI integration is secure, transparent, and capable of scaling effectively. Constructed on a fully EU-based infrastructure, Velatir empowers operations, IT, and compliance teams to effectively handle risks, ensure adherence to regulations, and boost efficiency across their processes. This comprehensive solution not only supports regulatory compliance but also fosters a culture of innovation and trust within organizations.