Alternatives to Skovos

Gemini Enterprise Agent Platform is Google Cloud’s next-generation system for designing and managing advanced AI agents across the enterprise. Built as the successor to Vertex AI, it unifies model selection, development, and deployment into a single scalable environment. The platform supports a vast ecosystem of over 200 AI models, including Google’s latest Gemini innovations and popular third-party models. It offers flexible development tools like Agent Studio for visual workflows and the Agent Development Kit for deeper customization. Businesses can deploy agents that operate continuously, maintain long-term memory, and handle multi-step processes with high efficiency. Security and governance are central, with features such as agent identity verification, centralized registries, and controlled access through gateways. The platform also enables seamless integration with enterprise systems, allowing agents to interact with data, applications, and workflows securely. Advanced monitoring tools provide real-time insights into agent behavior and performance. Optimization features help refine agent logic and improve accuracy over time. By combining automation, intelligence, and governance, the platform helps organizations transition to autonomous, AI-driven operations. It ultimately supports faster innovation while maintaining enterprise-grade reliability and control.

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.

Drata is an agentic trust management platform for automating governance, risk, compliance, security assurance, and third-party risk management processes. Its Enterprise GRC capabilities bring controls, risks, policies, and evidence into a centralized system while allowing organizations to map controls across multiple frameworks and reuse compliance work. Continuous compliance automation collects evidence, monitors controls, identifies issues, and provides guided remediation to help teams remain audit-ready as their environments change. Drata's Trust Center provides a secure location where prospects, customers, and other stakeholders can review an organization's security posture, request documents, and obtain answers to trust-related questions. AI-powered questionnaire automation supports the questionnaire lifecycle from intake and triage through processing and response generation, using an evolving knowledge base to draft consistent answers. Third-party risk management uses AI agents to create assessment criteria from existing questionnaires, collect documents from vendor Trust Centers, perform risk assessments, and conduct vendor follow-ups. Drata also provides AI Agent Governance capabilities designed to discover AI agents within an enterprise, enforce organizational policies before agent actions execute, and produce records of agent decisions for auditing. The platform supports frameworks and regulations including SOC 2, ISO 27001, ISO 42001, GDPR, HIPAA, PCI DSS, DORA, FedRAMP, CMMC, and custom frameworks. Drata is designed to support organizations ranging from startups establishing their first compliance programs to enterprises managing governance, risk, compliance, and trust requirements across multiple business units and regions.

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.

Runlayer serves as an AI control plane tailored for organizations that are integrating AI agents and associated tools within their engineering, security, IT, and business sectors. This platform features a governed catalog that includes sanctioned MCP servers, connectors, skills, and agents, ensuring that all agent tool calls are channeled through a gateway that enforces compliance with established policies. Administrators have the capability to uncover AI client activities and MCP operations, examine session traces and audit logs, and implement configurable policies, approvals, and security scans to oversee or prevent potentially hazardous actions. Employees are empowered to develop agents via supported AI clients while utilizing authorized tools and defined permissions, with teams overseeing the adoption and management of these resources. Furthermore, Runlayer seamlessly integrates AI clients with identity providers, device management systems, and MCP servers, offering both hosted and self-hosted deployment options. This solution is specifically crafted for organizations aiming to achieve unified visibility, governance, and security as they implement AI agents and related workflows throughout their operations, fostering a more efficient and controlled environment for innovation.

Assurio serves as a comprehensive platform dedicated to AI governance, risk management, and assurance for organizations managing AI systems, models, and agents. It features an inventory system that allows users to document ownership, intended applications, components, and suppliers, while effectively linking risk assessments with policies, controls, exceptions, and lifecycle approvals. Additionally, it incorporates evaluation workflows that associate requirements with testing scenarios, performance metrics, findings, and the necessary supporting evidence. Teams benefit from the ability to preserve decision-making records and evidence histories, track modifications, and pinpoint records that require reassessment. Assurio also aligns its work with various frameworks such as NIST AI RMF, ISO/IEC 42001, ISO/IEC 23894, and the EU AI Act, although it is important to note that framework mapping does not equate to compliance verification. Designed for seamless integration, the platform connects with external requirements, model management, testing, observability, governance, risk, and compliance (GRC) systems, as well as enterprise resource planning (ERP), customer relationship management (CRM), and workflow systems. For enterprise applications, it outlines options for customer-hosted and dedicated deployment architectures, ensuring versatility and scalability for its users. This multifaceted approach allows organizations to navigate the complexities of AI governance effectively.

Kosmoy helps enterprise teams answer practical questions about production AI: which systems are running, who owns them, what they cost and which controls apply. Its inventory records AI systems, models, agents and MCP servers with ownership and risk assessments. Monitoring tracks usage, costs and behaviour across applications. The AI Gateway applies access controls, guardrails, routing and logging to LLM, MCP and agent-to-agent traffic. Action Capsule provides runtime isolation and a kill switch for autonomous agent actions. Kosmoy runs in the customer Kubernetes environment, in the cloud or on premises. AI platform, security, risk and compliance teams can use the same inventory and operational evidence when reviewing AI use cases.

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.

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.

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.

Nightworks AI serves as a regulated agent platform tailored for ongoing finance and operational tasks, such as preparing for closings and managing back-office functions. This platform is specifically crafted for financial controllers, CFOs, owner-operators, holding-company managers, and teams within regulated back-office environments. The system enables agents to handle work and compile necessary documentation while allowing personnel to examine decisions and maintain oversight over actions that cannot be reversed. Its offerings encompass workflow exploration, a supervised workflow trial, and an operational assessment. Agents operate within the client's ecosystem, providing a workspace for operators to analyze evidence, decisions made, and documented activities. Each engagement involves a mutual agreement on the workflow's scope, permissions, source systems, and implementation details, ensuring a tailored approach to meet the specific needs of the organization. This flexibility in deployment helps streamline operations efficiently while maintaining compliance and control.

Modulos helps compliance, risk and AI teams govern the AI their organization builds, buys and uses. Teams use it to prepare for ISO/IEC 42001 certification or an EU AI Act conformity assessment, find and govern shadow AI, test that AI agents behave as intended and put a monetary figure on AI risk for board decisions. Scout, the built-in AI agent, scans cloud accounts, code and connected tools for unregistered AI systems and adds them to the AI registry for review. The Evidence Agent, the Control Assessment Agent and the Risk Agent propose; people approve. Evidence stays attached to the control it supports, with review workflows, an audit log and PDF audit exports. The platform also includes a Policy Center, vendor records for third-party AI and integrations with GitHub, AWS, Azure, Jira, Confluence, MLflow and Microsoft Copilot Studio. Modulos is based in Zurich and received an Honorable Mention in the inaugural Gartner® Magic Quadrant™ for AI Governance Platforms (2026).

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.

Myra AI Workspace integrates an AI gateway with a controlled environment designed for organizations that handle sensitive information while utilizing AI technologies. Users can engage with chat functions, manage projects, access knowledge repositories, import files, and utilize document generation tools, whereas administrators oversee access protocols, model configurations, and safety measures. This gateway interfaces with over 20 model providers, such as OpenAI, Anthropic, Gemini, Azure OpenAI, AWS Bedrock, Mistral, Groq, DeepSeek, and xAI, all through a single OpenAI-compatible endpoint. Organizations benefit from BYOK (Bring Your Own Key) capabilities, allowing them to maintain their provider contracts securely. A color-coded privacy indicator informs users about the status of their data, whether it remains on the Myra infrastructure with open-weight models, is PII-masked prior to reaching external models, or necessitates administrator consent. Additional features include customizable guardrails, PII masking, secure audit logs that are tamper-evident, budget controls with three tiers, and support for MCP connectors, SCIM, and SIEM forwarding, all of which contribute to a robust and secure AI environment. The platform operates on Myra's infrastructure located in the EU, ensuring compliance with regional data protection regulations.

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.

SystemPrompt is a platform designed for organizations that enables self-hostable AI governance and runtime capabilities, facilitating connections between AI clients, model providers, and various tools. It offers a unified control plane and gateway for overseeing user and agent access, managing model routing, and ensuring appropriate permissions, credentials, and compliance checks. Additionally, the platform allows for the documentation of requests and tool actions within the organization for auditing and review purposes. With compatibility for connections to providers such as Anthropic, OpenAI, Google Gemini, and Groq, SystemPrompt employs the Model Context Protocol (MCP) to ensure that only authorized tools are accessible to suitable clients. The platform also empowers teams to enhance the runtime by incorporating agents, workflows, skills, and tailored business services, all deployable via binaries, containers, or managed cloud environments. Specifically designed for technical and security teams tasked with overseeing AI workloads, SystemPrompt not only offers local evaluation at no cost but also stipulates that production use and cloud hosting must adhere to commercial agreements. Furthermore, its flexible architecture allows organizations to adapt the platform to meet their specific operational needs.

KYDE serves as a behavioral firewall designed specifically for AI agents, ensuring they can be entrusted with significant responsibilities. By delineating prohibited actions, documenting completed tasks, and safeguarding your proprietary knowledge, KYDE enhances the reliability of AI agents. Positioned externally, KYDE operates in the request pathway between your agents and all LLM providers, systematically intercepting, scoping, and signing each action prior to execution. This external placement ensures it cannot be overridden by the agent itself, maintaining strict control. With no need for code alterations and only one environment variable required, KYDE is both provider-agnostic and ready for multi-cloud platforms, targeting a latency of under 100 milliseconds. It encompasses three essential functions within a single layer. The first is PROVE, which creates an audit trail that remains independent of any LLM provider; actions are signed using Ed25519, hash-linked, and recorded at the boundary, making them irretrievable by the agent. In this scenario, the perpetrator cannot fabricate their own account. The second function is RATE, which evaluates agent behavior across different providers on a unified scale known as the KYDE Trust Score™. While vendors assess their own performance, KYDE focuses on objectively grading agent behavior, creating a more transparent evaluation system. Finally, this comprehensive framework not only enhances accountability but also fosters an environment of trust in AI interactions.

MemClaw serves as a durable memory service tailored for LLM-driven agents and functions as a regulated shared memory layer among fleets of agents. Its core purpose is to facilitate collaborative learning among AI agents by transforming their isolated contexts into a collective Company Brain, complete with integrated memory features, governance, provenance tracking, contradiction detection, and predefined visibility scopes from the outset. The architecture of MemClaw effectively distinguishes an organization’s agents—including tenants, fleets, nodes, and individual agents—from the managed memory layer via components such as the MCP Server, REST API, OpenClaw plugin, MemClaw Core, and persistent storage solutions. Agents can access and contribute to the Company Brain using MCP-compatible tools, direct HTTPS requests, or integrations through OpenClaw, while the MemClaw Core processes enhancements like entity extraction, contradiction identification, PII screening, and lifecycle management prior to any data being saved. Each memory entry can be labeled with a specific visibility scope and categorized automatically into various types including fact, episode, decision, preference, rule, plan, commitment, action, and outcome. Additionally, this structured approach not only enhances the organization of information but also improves the overall efficiency and effectiveness of AI agent interactions within the network.

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.

Rithmo serves as a fact-checking tool specifically designed for AI agents, ensuring that organizations avoid the pitfalls of relying on outdated, conflicting, or obsolete business information. By continuously aligning decisions made across various meetings, communications, and operational frameworks, Rithmo enables agents to operate based on the most accurate and current business truths rather than merely leveraging the information they gather. In instances where the context shifts, Rithmo is capable of detecting inconsistencies, supplying the resolved response along with its source, and halting an agent's action if the conflict cannot be resolved safely. As an integral component of the governance and reliability framework for AI agents, Rithmo offers a comprehensive decision history, established provenance, supersession details, and an audit trail that elucidates what changes occurred and the reasons behind them. Furthermore, Rithmo enhances the functionalities of AI agent memory, orchestration, observability, security, and enterprise search by tackling a distinct challenge: confirming whether the business context that informs an agent’s actions remains valid. This capability ensures that organizations can trust the actions of their AI agents are grounded in the most reliable and relevant information.

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.

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.

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.

MudraID is a cloud-based platform designed for identity and trust management, specifically tailored for teams engaged in developing AI agents, APIs, and services that leverage agent capabilities. The platform provides agents with unique cryptographic identities, facilitates scoped and temporary delegation, and assesses requests based on policy, trust, and revocation status at the moment of action. Teams have the ability to issue, rotate, suspend, and revoke credentials for agents, enforce permissions on a per-action basis, and track delegation pathways efficiently. It is compatible with OAuth 2.0, OIDC, JWT/JWKS, MCP authorization, and signed A2A Agent Cards, ensuring a robust framework for secure interactions. For developers, it offers a Python agent SDK and middleware options for FastAPI/Starlette, while a hash-chained audit trail meticulously logs decisions and associated events. MudraID serves as an essential tool for product, platform, security, and IAM teams that require effective management of interactions between agents and services, thereby enhancing overall operational integrity and security. This comprehensive approach ensures that all interactions remain traceable and governed under established policies.

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.

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.

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.

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.

TokenTally serves as a self-hosted governance platform tailored for organizations aiming to oversee their employees' interactions with generative AI tools. It establishes a unified control framework for sanctioned AI services, offering functionalities that allow the creation of access policies, budget management, prompt enhancement, and usage and cost monitoring. Administrators have the capability to track the AI service usage across teams and implement overarching organizational guidelines, while employees utilize the designated tools within this regulated environment. This solution is designed for company leaders, operational executives, IT and security teams who are responsible for assessment and deployment, as well as IT service providers managing client infrastructures. TokenTally is deployed on the organization’s own systems, with subscription plans structured according to employee numbers, accommodating both small-scale and enterprise-level implementations. Moreover, it is particularly beneficial for businesses that desire a centralized overview and control over their AI adoption, spending, and the management of proprietary data. As organizations increasingly integrate AI into their workflows, solutions like TokenTally become essential for maintaining oversight and ensuring compliance.

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.

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.

AI Sigil is a comprehensive platform designed for governance, risk, and compliance in the realm of artificial intelligence. It features an up-to-date library containing 28 regulatory frameworks, which includes the EU AI Act and an array of national and state laws. Users are required to register each AI system along with its various components, such as use cases, models, data, interfaces, and actions. The platform then intelligently determines applicable regulations, categorizes the system according to its role and associated risk level, and outlines the requisite obligations, updating them whenever there are changes to the system. These obligations are transformed into actionable requirements and controls, distributed across the organization and the system level, each assigned to a responsible party with defined status, evidence, and review frequency, all while maintaining a comprehensive risk register that includes mitigations. Regular assessments and questionnaires are conducted on a set schedule, preserving a complete history of responses that can be shared with vendors or external evaluators without requiring them to have an account. The output is a regulator-ready report that is created solely from the recorded data and secured with a unique fingerprint, all supported by a thorough activity log. Additionally, the platform supports multi-entity, role-based access, features a REST API and MCP server, and offers support in six different languages, making it a versatile tool for organizations navigating the complexities of AI regulation.

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.

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.

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.

Elsai is an enterprise AI platform that prioritizes governance, converting intricate workflows into operations that are manageable, transparent, and ready for production. Designed specifically for regulated and enterprise settings, elsai integrates elements such as AI orchestration, observability, safety measures, workflow automation, and compliance governance within a single execution framework. This comprehensive approach empowers organizations to expand their AI capabilities while ensuring that visibility, security, auditability, and cost management are inherently included. As a result, businesses can confidently navigate the complexities of AI implementation while adhering to governance standards.

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.

Holiday is the control layer for business AI. It sits across your existing systems and makes every AI action accountable: software-enforced boundaries decide what each AI identity may do, and what each person may ask, on every single call. Nothing is trusted at the session level. What Holiday delivers: 1. AI Governance - one place to set permissions, budgets and reporting, with a full audit trail for every AI identity in the business. 2. Our Environment - your own single-tenant environment, hosted in the AWS region you choose, connecting your business systems and running Digital Employees. 3. AI Security - zero-trust verification of each AI tool call, checked against both the AI's and the user's permissions. 4. Business Chat - staff ask questions in chat and get permissioned answers drawn from email, CRM, documents and finance. 5. Shadow Agent Detection - surfaces unapproved AI tools and unregistered agents by watching identity and access activity.

Coder offers self-hosted cloud development environments, provisioned as code and ready for developers from day one. Favored by enterprises, Coder is open source and can be deployed air-gapped on-premise or in your cloud, ensuring powerful infrastructure access without sacrificing governance. By shifting local development and source code to a centralized infrastructure, Coder allows developers to access their remote environments via their preferred desktop or web-based IDE. This approach enhances developer experience, productivity, and security. With Coder’s ephemeral development environments, provisioned as code from pre-defined templates, developers can instantly create new workspaces. This streamlines the process, eliminating the need to deal with local dependency versioning issues or lengthy security approvals. Coder enables developers to onboard or switch projects in a matter of minutes.

AgentShelf Platform provides a user-friendly no-code interface for the creation, implementation, and management of specialized AI agents tailored for business processes. Teams have the capability to equip each agent with authorized context, tools, model access, permissions, and a specific workspace, allowing them to launch experiences across websites, internal platforms, products, or external applications. The platform features reusable agent templates, interactive widgets, SDKs, and APIs, along with tools for monitoring usage and costs, budget management, activity logs, and access controls that can be set to public or private. It caters to a variety of applications, including visitor qualification on websites, customer support prioritization, follow-ups in CRM systems, research activities, knowledge retrieval, and the generation of recurring reports. With its comprehensive tools and flexible deployment options, the platform promotes efficiency and enhances workflow automation in diverse business environments.

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.

NewCore serves as a cutting-edge identity provider designed for both humans and AI agents, centered around a unified identity core that ensures every identity is visible, secure, and monitored from the point of access through to auditing. It recognizes employees, contractors, partners, machines, delegated agents, and autonomous workloads as primary identities within a singular framework. The Identity Security component fortifies trust associated with access using features such as single sign-on, passkeys, phishing-resistant multi-factor authentication, secure token signing, strength scoring for authenticators, and policies that are aware of security measures. Utilizing a Secure Split Key mechanism, it divides the signing authority between NewCore’s cloud infrastructure and the customer's own environment, ensuring that neither entity can independently sign a valid token. Furthermore, the Identity Discovery feature creates a comprehensive live graph that encompasses humans, agents, accounts, applications, authenticators, sessions, and access pathways, thereby illuminating shadow accounts, orphaned credentials, and unmanaged agents, which can pose security risks. This holistic approach to identity management not only enhances security but also streamlines the process of tracking and managing diverse identities within an organization.

Dymium delivers governed access to enterprise data in real time, giving AI, applications, and analytics just enough information to function—no more and no less. Its Ghost Layer architecture applies policies dynamically, evaluating each request at the moment it occurs rather than relying on static roles or delayed batch checks. This prevents over-permissioned access, blocks sensitive fields during AI inference, and ensures every query is compliant before data is returned. Teams gain live access to more datasets without waiting for pipelines, approvals, or shadow environments. Dymium eliminates the risks associated with data duplication by enforcing controls directly where data lives, regardless of structure or system. Security, privacy, and compliance teams benefit from full visibility and detailed audit trails for every interaction. AI and product teams can ship smarter, safer features with governance automatically built in. With support for row-, field-, and role-level access, Dymium modernizes governance for organizations operating at AI speed.

Modulo is a comprehensive self-hosted solution designed to construct and manage software development lifecycle pipelines utilizing AI agents. Teams can create visual workflows incorporating various components such as agents, connectors, approval gates, and human interventions, while also specifying typed inputs, outputs, permissions, and review checkpoints for every transition. The platform enables the orchestration of existing agents alongside tools for source control, ticketing, messaging, CI/CD, monitoring, and knowledge management, with schema validations and human approvals guiding the workflow progression. Additionally, Modulo meticulously logs inputs, outputs, model versions, prompt details, evaluations, and governance decisions, creating a detailed audit trail. Teams are empowered to establish token budgets for individual agents, impose spending caps on pipelines, and initiate organization-wide pauses as needed. Ultimately, Modulo caters to engineering and platform teams aiming to regulate agent-assisted software delivery, encompassing code modifications, pull requests, reviews, and other related development workflows on their managed infrastructure. This platform not only enhances operational efficiency but also ensures accountability throughout the software delivery process.

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.