Alternatives to Kastra

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.

Maetra serves as an AI governance control plane tailored for teams managing tool-utilizing AI agents. It identifies agents and their associated repositories, assesses risks based on established frameworks, and reviews potential actions against versioned governance policies prior to execution. Additionally, it facilitates human approvals, monitors prompts and tool interactions for runtime vulnerabilities, ensures ongoing tasks remain aligned with authorized objectives, and maintains unalterable records of decisions for auditing purposes. The system features several modules, including Govern, Secure, Task Guard, Interaction Guard, Discover, Comply, Audit, and Decision Intelligence, which can function independently or as part of a cohesive control plane, enhancing overall operational efficiency and compliance. Ultimately, this integrated approach ensures robust management and oversight of AI agent activities within organizational frameworks.

Harden AIF serves as a security platform specifically designed for AI coding agents, ensuring agent endpoint security by assessing tool calls prior to execution based on the developer's intent, session context, organizational policy, and the potential impact of the action proposed. This platform effectively safeguards against threats such as harmful commands, unauthorized access, accidental data transfers, exposure of sensitive information, misuse of privileges, and other risky actions undertaken by agents. By allowing legitimate operations to proceed without disruption, it can also safely redact sensitive information during supported workflows while preventing actions that deviate from the developer's intent or exceed their authority from executing. Harden AIF is compatible with a variety of widely used coding agents and development tools, including Claude Code, Codex, Cursor, Antigravity CLI, Kiro, Hermes, and OpenClaw, thus offering a uniform security framework throughout the agent ecosystem. This comprehensive approach not only enhances security but also fosters a safer environment for developers working with AI technologies.

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.

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.

HOL Guard is a security layer designed for AI agents that operates on a local-first basis, monitoring the actions of an AI assistant and preemptively preventing potentially harmful activities. It functions as an intermediary between the agent and the computer, assessing tool calls and local resources for various threats, including the risk of secret and credential leaks, harmful commands, actions driven by prompt injection, and the use of compromised or altered packages, as well as risky configurations and unsafe plugins, skills, hooks, and settings. Threats that are identified can be automatically blocked, while uncertain actions are temporarily halted to seek user consent, ensuring that individuals maintain oversight. Operating entirely on the developer’s local machine, Guard does not require an internet connection and refrains from uploading any files, prompts, or sensitive information. Local evaluations are typically completed in less than 50 milliseconds, and the implementation of Guard does not necessitate modifications to current code or workflows. It is compatible with various coding agents including Claude Code, Cursor, Codex, Gemini CLI, OpenCode, Hermes, and OpenClaw, providing custom integrations that analyze actions prior to their execution. Additionally, this enhances the overall safety and reliability of AI interactions, fostering greater trust in automated processes.

Willow serves as a comprehensive enterprise platform designed to manage AI agents, tools, MCP servers, skills, and plugins. It facilitates the connection of various agents like Claude, ChatGPT, Cursor, Codex, Gemini, n8n, and customized agents to internal frameworks and SaaS applications such as Jira, GitHub, Slack, and databases via an MCP gateway. Each agent is assigned a human-linked identity, specific permissions, and an audit trail for accountability. Security teams are tasked with establishing policies while employees have the ability to self-service approved connectors, skills, and plugins as needed. Among its features are shadow AI discovery, PII redaction, prompt-injection inspection, app- and action-level permissions, as well as integrations for SSO, SCIM, and RBAC with platforms like Okta, Entra ID, and JumpCloud. Additionally, Willow offers capabilities for SIEM export, token and cost tracking, and operates background agents to enhance functionality. The platform is accessible in various deployment models, including SaaS, dedicated cloud, or on-premises within a customer’s VPC. With a SOC 2 Type II attestation and compliance with GDPR, Willow has gained traction and is currently utilized in production by notable companies such as Wix, Innovid, and Riskified, ensuring it meets high industry standards. This versatility and commitment to security make Willow a robust choice for organizations looking to harness the power of AI responsibly.

ZeroDrift serves as an AI enforcement runtime, rigorously evaluating each AI-generated message for compliance with applicable regulations and company guidelines prior to transmission. Its innovative Anchor compliance model integrates a specialized language model with a deterministic rules engine to assess outputs and deliver one of four potential outcomes: pass, rewrite, block, or escalate. Each decision references the specific rule that informed the verdict, and any modified content undergoes a second evaluation before being sent out. Organizations have the flexibility to establish their own internal guidelines, prohibited lists, approval processes, and communication protocols, which ZeroDrift diligently enforces in conjunction with existing regulatory obligations across various AI platforms including chat, email, documents, marketing, APIs, and more. Additionally, Guard offers an enforcement API that can be positioned before any AI agent or language model, enabling applications to respond directly to each determination without the need to overhaul the existing AI infrastructure. This functionality not only streamlines compliance efforts but also enhances the overall governance of AI communications within organizations.

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.

Many enterprise AI initiatives struggle due to their inability to access data stored within operational systems. Usermode addresses this challenge by integrating your existing systems—such as ERP, property management, inspection databases, and Microsoft 365—through custom MCP integrations. It then implements a controlled network of specialized agents focused on various tasks, including credit control, compliance, management accounts, and bid writing, which operate seamlessly across channels like email, WhatsApp, and Teams. Each action is governed by a deny-by-default policy engine, requiring prior approval for any communication, while a tamper-evident ledger meticulously records all activities. Currently, it is actively utilized in property management and industrial inspection, overseeing more than 3,300 residential units. Notably, all intellectual property remains under your ownership, ensuring complete control over your innovations. This approach not only enhances operational efficiency but also fortifies security and compliance protocols.

Enkrypt AI is an AI security and compliance platform built to protect generative AI applications, autonomous agents, models, data, and AI infrastructure. It provides security agents and controls for detecting vulnerabilities, preventing threats, continuously monitoring AI systems, and automating compliance processes. Enkrypt AI's red teaming capabilities dynamically generate use-case-specific attacks that adapt during testing to uncover security, safety, and brand risks that static evaluations may miss. The platform addresses threats including prompt injection, jailbreaking, data leakage, model inversion, adversarial attacks, policy violations, hallucinations, model drift, bias, toxic content, deceptive behavior, and unmonitored agent actions. Real-time guardrails inspect AI interactions and can stop threats as they occur while continuously adapting based on prompts and observed activity. Monitoring capabilities provide ongoing visibility into AI risk and compliance so organizations can identify issues, track protection effectiveness, and maintain evidence for audits. Enkrypt AI can translate internal organizational policies and external regulatory requirements into automated guardrails to reduce manual compliance work. Its product portfolio includes Agent Red Teaming, Agent Guardrails, an Agent Policy Engine, AI Data Risk Audit, MCP Scanner, and MCP Gateway, with solutions for customer-facing agents, frontier models, third-party AI risk, AI compliance, MCP security, and secure AI development. The company also maintains an LLM Safety Leaderboard that continuously red teams and benchmarks more than 200 AI models to help organizations evaluate model security and safety.

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.

Inficy serves as a cloud-based control center for the documentation of AI agent execution evidence. It transforms recorded agent activities into clear, tamper-proof execution logs that detail the tools used, services engaged, timing of events, failures encountered, recoveries made, and any human interventions. Users can review, export, and authenticate these records offline, with the possibility of obtaining independent certification for specific executions via the NexArt framework. This platform is tailored for engineering teams, operators, as well as risk and audit reviewers who oversee AI agents performing tangible actions within production environments. Its robust features ensure that all activities can be scrutinized and validated, providing peace of mind for stakeholders.

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.

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.

Pushary alerts you on your phone whenever your AI agents require your input. Agents like Claude Code, Codex, and Cursor halt their processes for your approval on potentially risky actions, such as executing shell commands, writing files, or deploying updates. Each time an action is paused, Pushary sends you a notification that you can accept or decline directly from your lock screen, allowing your agents to continue operating seamlessly while you are not at your desk. Establish permission policies tailored to each tool: automatically approve safe operations, demand your approval for those deemed risky, and maintain a comprehensive audit trail of every interaction. You can manage an entire fleet of agents and monitor their activities from a single dashboard. In addition, Pushary facilitates push notifications for e-commerce and SaaS platforms, offering features like subscriber capture, marketing campaigns, automated workflows, customizable templates, and insightful analytics. You can effortlessly connect any agent using a straightforward CLI or MCP, and the package includes native applications for both iOS and Android devices. With Pushary, you gain a robust solution for managing both AI agents and notifications across various platforms.

Zof AI serves as an autonomous platform focused on software reliability and verification, aimed at assisting engineering teams in testing applications, recognizing potential risks, and managing modifications prior to deployment. By leveraging AI agents, automated testing, and an analysis of system dependencies, the platform ensures continuous validation of software performance and readiness for release. Its System Graph effectively visualizes services, APIs, infrastructure, dependencies, and workflows, allowing teams to pinpoint which components are impacted by code alterations. Supporting a total of 19 verification categories, Zof encompasses unit testing, integration testing, regression testing, performance testing, security testing, and compliance validation among others. Furthermore, its governed remediation features enable teams to delve into failures, suggest solutions, and confirm changes—all while upholding human oversight and maintaining thorough audit trails. This versatile platform seamlessly integrates with existing CI/CD pipelines, development tools, and cloud infrastructures, and it accommodates private cloud, on-premises, and air-gapped deployment scenarios. In addition to its robust features, Zof AI empowers engineering teams to enhance their software development lifecycle efficiently and with greater confidence.

Openlayer is the enterprise AI governance platform for discovering, testing, monitoring, securing, and governing AI systems from development through production. Openlayer brings AI evaluation, observability, guardrails, compliance, gateway enforcement, and cost controls into one platform.

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.

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.

Antaeus serves as a semantic policy engine designed for developers tasked with assessing human-written rules related to language, context, intent, or exceptions. It features an open-source core built in Go and a command-line interface that can load policy artifacts in YAML or JSON formats, validating these against versioned schemas while executing named regression tests. The evaluation process yields clear outcomes such as allow, review, deny, or failure, accompanied by policy identification and evidence for the decisions made, while leaving the responsibilities of authentication, authorization, and any consequential actions to the application itself. Developers have the option to operate a deterministic, credential-free local workflow or utilize an experimental hosted dashboard and API for managing policies and evaluating various inputs. Additionally, there is an experimental OpenAI evaluator available for use. It is important to note that Antaeus is still in its early stages; thus, the capacity of the hosted service is limited and does not come with a production-level service level agreement (SLA), which may affect reliability during high-demand situations.

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.

AgentScan is a no-cost, deterministic security scanner specifically designed for evaluating AI agent skills. It meticulously inspects a skill directory, which includes platforms like Claude Code, Codex, OpenCode, and MCP servers, for various vulnerabilities such as prompt injection, hidden secrets, network activity, malware signatures, and obfuscation techniques prior to installation. Each identified issue is accompanied by specific file:line references and an associated confidence score. The tool operates without executing the skill or uploading any data, functioning entirely offline. Being free and open-source under the MIT license, it also offers the Trust Pack feature, which facilitates the addition of 90 pre-audited skills with a single command. This ensures users can enhance their security measures efficiently.

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.

What tools are your people actually using to get work done with AI, and does anyone know? Tangerin AI is the independent AI governance platform built to answer that question for organizations of any size, not just in Brazil but around the world. Sanctioned or not (the latter being what's commonly called Shadow AI), every AI tool in use gets discovered, assessed for risk, brought under policy, and backed by evidence an external auditor can check. Detection runs two ways: a small agent on Windows, macOS and Linux endpoints, or an agentless route that reads existing NGFW, SSE and SIEM logs. Whatever comes in gets checked against a constantly updated catalog of thousands of AI tools, each one carrying its data risk level, where it processes data, how long it retains it, and whether it trains on customer data. From there, policy marks each tool allowed, restricted or banned; staff sign off on the AI usage policy digitally; and more than twenty regulatory frameworks, NIST AI RMF and SOC 2 among them, alongside LGPD, ISO 42001, the EU AI Act and GDPR, are covered with automatic evidence mapping between equivalent frameworks and a dedicated view for outside auditors. What gets logged is which tool, by whom, when, and on which machine. Conversation content, prompts, and files never do; that line was drawn in the architecture, not left to a settings toggle.

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.

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.

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.

Attestly operates as an advanced AI governance and compliance platform that automates the transformation of operational execution traces into documentation that meets the standards of the EU AI Act. Tailored for companies, AI developers, and compliance professionals, the platform actively collects real-time execution logs from AI agents and produces verifiable documentation to ensure adherence to Article 12 requirements. Notable Features Include: - Automated Article 12 Compliance: Real-time capture of AI agent trace data is conducted continuously. - Zero-Trust Cryptographic Ledger: This feature utilizes append-only ledgers, cryptographic hash chaining, and Merkle tree proofs to ensure the immutability of the evidence collected. - Regulator-Ready Auditing: The platform offers independent WASM verifiers that facilitate transparent validation by third parties while safeguarding sensitive payload data. - Continuous Runtime Visibility: Attestly eliminates the need for periodic manual audits by implementing automated logging of decisions and ongoing risk monitoring, enhancing overall operational transparency. The result is a comprehensive solution that not only streamlines compliance but also bolsters trust in AI operations.

Klique is a vendor-agnostic enterprise AI control plane designed to manage how AI requests, models, workloads, and compute resources are routed and governed. Its Smart Routing engine sends individual AI requests to suitable models based on policy, cost, latency, and data sensitivity while routing larger workloads according to infrastructure capacity, locality, and price. The platform can work with internal models, open-source models, hosted APIs from providers such as OpenAI and Anthropic, and AI workloads running across private or public infrastructure. AI Service Management turns model endpoints into governed services with centralized token budgets, spend limits, quotas, virtual keys, identity controls, and audit trails. These policies can be applied consistently across human users, software agents, development tools, teams, and projects. Klique’s GPU Orchestration engine pools GPUs, CPUs, and cloud resources so organizations can allocate compute using fractional sharing, quotas, and priority scheduling. It supports use cases including application inference, model training, data processing, research workloads, and production model serving. Klique can be deployed on-premises, in air-gapped environments, across major cloud providers, or in hybrid architectures while maintaining the same governance and visibility model. The platform is intended for enterprises, AI teams, IT organizations, research groups, and regulated environments that need centralized control over AI infrastructure, usage, and spending.

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.

OpenText Core DNS Protection delivers continuous, comprehensive oversight of DNS traffic to defend organizations against stealthy, fast-moving attacks. It inspects every DNS resolution request—from applications, browsers, and background processes—and immediately filters out malicious queries before harm can occur. The solution helps prevent data loss by blocking communication with Command and Control infrastructure used for exfiltration and ransomware operations. With dynamic detection of unauthorized DNS servers, it ensures that encrypted DNS traffic cannot bypass corporate policies. Administrators can centrally manage rules, analyze DNS patterns, and identify vulnerabilities through built-in reporting dashboards. Hybrid and remote workers stay fully protected because the agent enforces DNS policies on any network. Setup is fast and frictionless, giving organizations instant security improvements without major infrastructure changes. By restoring full visibility and control over DNS activity, the platform strengthens the security posture of modern, distributed environments.

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.

ZizkaDB is an operational intelligence platform for AI agents that helps teams debug, monitor, and understand production behavior. The system is designed to go beyond basic logs by storing agent decisions, causal lineage, time-travel state, session replay, semantic history, and drift signals. ZizkaDB helps teams see why an agent made a decision, what changed after a prompt or deployment update, and where behavior diverged from an expected baseline. Developers can replay any session end to end, trace the decision chain, identify root causes, and roll back or fix regressions more quickly. The platform supports Python, TypeScript, MCP, REST API, Docker-based self-hosting, and managed cloud deployment. Its dashboards include Activity, Behavior, Reports, Suggestions, and Fleet features for managed cloud and enterprise users. Security and trust features include open source AGPL licensing, self-hosting, checksum-backed events, and single-tenant VPC deployment options. Pricing includes a free self-hosted plan, Pro and Team cloud plans, and enterprise licensing for private deployments. By combining replay, lineage, drift detection, behavioral baselines, cross-agent visibility, and flexible deployment, ZizkaDB helps teams fix agent behavior before production breaks.

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.

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.

MintMCP serves as a robust Model Context Protocol (MCP) gateway and governance solution designed for enterprises, offering a centralized approach to security, observability, authentication, and compliance for AI tools and agents that interface with internal data, systems, and services. This platform empowers organizations to deploy, oversee, and manage their MCP infrastructure on a large scale, providing real-time insights into each MCP tool interaction while implementing role-based access control and enterprise-level authentication, all while ensuring comprehensive audit trails that adhere to regulatory standards. Functioning as a proxy gateway, MintMCP effectively aggregates connections from various AI assistants, including ChatGPT, Claude, and Cursor, streamlining monitoring processes, mitigating risky behaviors, managing credentials securely, and enforcing detailed policy measures without necessitating individual security implementations for each tool. By centralizing these functions, MintMCP not only enhances operational efficiency but also fortifies the security posture of organizations leveraging AI technologies.

Veeam DataAI Command Platform is a unified DataAI trust platform designed to connect data, backups, identities, systems, and AI into one intelligence and control layer. Powered by Veeam DataAI Command Graph, the platform maps relationships across environments so teams can understand risk in context and take precise action. Its DataAI Security capabilities help discover and classify sensitive data, identify public sharing, detect excessive access, and prioritize high-risk exposure scenarios. DataAI Agent Commander helps organizations discover AI agents, copilots, and models, monitor risky activity, control how AI systems access data, and undo AI mistakes with precision. Identity and Access Governance helps reduce risk from misconfigured or compromised access by showing who can access sensitive data and where permission drift exists. DataAI Privacy and Compliance maps data to regulatory requirements, automates controls, and generates audit-ready reports. DataAI Resilience helps teams understand what data is protected, where backups exist, what is recoverable, and how to recover from ransomware, accidental changes, or outages. Operational intelligence allows teams to ask questions and have AI agents find answers across the environment. By unifying backup, security, AI governance, privacy, compliance, identity, and resilience, Veeam DataAI Command Platform helps organizations manage data and AI trust with greater visibility and control.

CloudEagle.ai is an AI-powered SaaS Management, AI Governance, and Identity Governance platform that helps organizations discover, govern, and optimize every SaaS and AI application across the enterprise, including applications outside traditional SSO or IT visibility.

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.

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.

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.

Kane CLI is an innovative AI testing tool designed for terminal use, developed by TestMu AI, previously known as LambdaTest. This versatile tool can be operated from various environments including any terminal, IDE, or CI pipeline, and it seamlessly integrates with AI coding agents such as Claude Code, Codex CLI, and Gemini CLI. The process you would want to execute in simple terms is: log into the system, add a laptop to your shopping cart, apply the SAVE10 discount code, and check the final total. Powered by Kane CLI, a real Chrome browser is utilized to conduct these actions step by step, providing a clear pass or fail result along with a link for shareable evidence. This tool eliminates the need for selectors or boilerplate code, meaning there’s no requirement for a test framework to be established beforehand. It is tailored to serve two key groups simultaneously: developers, QA engineers, product managers, and casual coders can validate a feature prior to a pull request, before the QA process, and just before deployment. On the other hand, AI coding agents leverage Kane CLI as an essential verification tool; they can create a feature based on a prompt but lack the capability to confirm its functionality in an actual browser environment. Thus, Kane CLI effectively completes that verification process and can be installed with a single command, making it both user-friendly and efficient. This dual utility enhances collaboration and streamlines the testing workflow across teams.

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.

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.