Alternatives to systemprompt.io

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.

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.

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.

Unify your AI governance initiatives amongst various stakeholders, guarantee that your governance procedures are primed for regulatory compliance, and effectively assess and control your AI-related risks and adherence to regulations. Transition from disjointed teams and processes to a consolidated source of reliable governance that simplifies the effective management of all your AI and machine learning projects. Keep informed on the latest regulations and standards with AI Policy Packs designed to comply with both current and emerging rules. Credo AI functions as an intelligence layer that integrates with your AI systems, converting technical documentation into practical insights regarding risk and compliance for product managers, data scientists, and governance professionals. By enhancing your technical and business infrastructure, Credo AI also provides risk and compliance metrics that can guide decision-making across your organization. This comprehensive approach not only streamlines governance but also fosters a culture of accountability and transparency in AI development.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Klique is an enterprise AI infrastructure management platform designed to help organizations deploy, govern, and optimize artificial intelligence workloads across multiple environments. The software provides a unified control plane for managing large language models, autonomous AI agents, GPU resources, and machine learning applications. Its intelligent routing engine automatically directs requests to suitable models based on organizational policies, performance requirements, response latency, and operating costs. Klique supports internally hosted models, open-source models, and external AI services from providers such as OpenAI and Anthropic. Its governance engine provides centralized authentication, role-based access controls, token budgets, usage quotas, audit trails, and detailed cost attribution. GPU orchestration capabilities enable resource pooling, workload prioritization, fractional GPU allocation, and automated scheduling across Kubernetes clusters and cloud infrastructure. The platform also provides managed development environments, model deployment tools, experiment tracking, and reusable workflows for AI development teams. Integrations with Claude Code, Codex, ChatGPT, and other agentic applications allow organizations to provide governed access to AI tools and computing resources. Klique supports on-premises, public cloud, hybrid, and air-gapped deployments, enabling enterprises to manage AI infrastructure while maintaining centralized security policies and operational visibility.

ModelLane serves as an intelligent inference gateway and routing control plane designed for developers and organizations that utilize various language model providers. It features an API compatible with OpenAI, enabling users to send requests to models that are either hosted, private, or self-hosted. Teams have the flexibility to create routing policies, referred to as “Lanes,” based on factors like cost, latency, availability, data retention, and geographical region, while also incorporating failover mechanisms, retry options, credential isolation, and detailed visibility into usage and expenses at the route level. The platform supports a variety of documented connectors, including those for OpenAI, Anthropic, Google, Mistral, Groq, and DeepSeek, along with local serving tools such as Ollama and vLLM. Furthermore, it provides an MCP interface that facilitates operations at the model layer. This system has multiple use cases, such as streamlining provider APIs, selecting optimal routes for diverse workloads, ensuring service continuity if a provider becomes unavailable, and overseeing inference activities effectively. Deployment choices are versatile, including options for hosted services, dedicated deployments, or integration within a customer’s VPC, allowing for tailored solutions to fit organizational needs. Ultimately, ModelLane enhances the efficiency and effectiveness of using multiple AI language models across various applications.

VerifyWise offers a comprehensive solution for AI governance, ensuring that businesses can deploy AI models securely, ethically, and in compliance with regulatory requirements. The platform provides key features such as AI framework implementation, real-time monitoring of model performance, audit trails for full transparency, and centralized inventory management for AI models. VerifyWise is built to support regulations like the EU AI Act and is designed to simplify the complex processes of compliance and risk management. With its user-friendly dashboards and open-source, transparent codebase, VerifyWise allows businesses to easily track and manage their AI models, mitigate risks, and ensure accountability throughout their lifecycle.

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.

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.

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

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.

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.

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.

NVIDIA OpenShell serves as an open and secure runtime environment specifically designed for autonomous AI agents, regulating their execution, access rights, and the pathways for inference traffic. Instead of embedding security within the model or application, it maintains safety measures in the surrounding environment, meaning that nothing is allowed by default; permissions are assigned through established policies, and enforcement mechanisms operate outside the agent process to prevent any circumvention via prompts. Each autonomous agent operates within a confined sandbox, which restricts direct network connectivity, limits file access, and implements kernel-level monitoring of system calls to ensure rigorous oversight. Acting as the control plane, a gateway is responsible for user authentication, lifecycle management of sandboxes, and the provision of policies, settings, credentials, and inference configurations to the agents. Additionally, a supervisor operates externally to each sandbox, scrutinizing network requests according to policies at various levels—including binary, destination, method, and path—and only grants access to credentials when explicitly permitted, thus enhancing the overall security framework. This layered architecture ensures that the agents function effectively while maintaining robust security protocols throughout their operations.

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

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.

AI Gateway HQ serves as a centralized AI gateway and management platform that helps organizations link their applications, coding agents, and automation tools to various model providers. It offers API endpoints that are compatible with OpenAI and Anthropic, efficiently routing requests through a system that manages provider credentials, model aliases, workload keys, and fallback mechanisms. Administrators have the ability to enforce identity and access policies, track request metadata, manage organizational and workload budgets, establish rate and concurrency limits, and analyze routing, usage, costs, and compliance with policies. Additionally, the service allows users to integrate their own provider API credentials or opt for a managed Amazon Bedrock solution that utilizes prepaid credits. Users can configure and govern their requests through a browser-based console and API, with established client setups that feature Codex CLI, Claude Code, and OpenCode. Teams leverage this platform to streamline AI access, manage model utilization and financial outlay, and continuously monitor operational metrics across different applications and environments, ensuring efficiency and accountability in their AI initiatives. Overall, the platform empowers organizations to optimize their AI strategies while maintaining control over resource allocation and compliance.

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.

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

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

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.

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.

ZGI is an open-source AI platform designed for enterprises to create business-oriented agents that leverage their specific data, tools, workflows, models, and expertise. With its Agent Runtime feature, agents can efficiently load Skills, access real-time company insights, utilize various tools, and quickly deliver valuable results. The Model Gateway integrates multiple global and domestic model providers, such as OpenAI, Anthropic, Google, DeepSeek, and Qwen, enabling teams to select the most suitable model for each agent based on criteria like quality, availability, cost, or geographic location while maintaining centralized control over access, quotas, routing policies, and fallback options. The comprehensive product workspace encompasses the entire agent development lifecycle: Agent Studio merges Skills, knowledge, tools, and models; Workflows facilitate complex, multi-step processes and allow users to monitor each execution closely; the Database enables natural-language queries over real-time business information while adhering to access governance; Model Management oversees provider connections and enterprise-level routing; and Knowledge Assets transform company documents into searchable, context-aware knowledge repositories. By integrating these features, ZGI aims to streamline the deployment and management of AI agents within enterprises.

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.

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.

FirstHelm serves as a centralized control plane for managing AI agents, acting as an intermediary between your collection of agents—such as n8n, OpenAI, Anthropic, CrewAI, LangChain, Microsoft Copilot Studio, or any custom agent through REST API—and the broader ecosystem. It not only regulates the permissions of each agent but also ensures accountability by logging every action and verifying it against established rules, including budget limits, prohibited actions, and visibility into costs and tokens per mission. Actions that are deemed costly, hazardous, or irreversible require human consent before proceeding, with any unattended approvals set to expire as a safeguard against inaction. Additionally, FirstHelm features live dashboards that allow users to guide agents in real time during missions, while also producing comprehensive audit trails and compliance documentation aligned with standards such as the EU AI Act, ISO 42001, SOC 2, UK GDPR, NIST AI RMF, and FCA requirements—encompassing 38 controls that are evaluated in real-time based on your own data. This innovative solution is available under a freemium model, is adaptable to various frameworks, and originates from the UK, underscoring its commitment to regulatory compliance and user empowerment. With its user-friendly interface and robust functionality, FirstHelm aims to enhance the management and oversight of AI-driven operations.

PromptUnit serves as an AI inference intermediary that automatically minimizes AI expenses by acting as a bridge between an application and its AI service providers, requiring no modifications to existing code. Teams simply replace the base URL while maintaining the same SDK, endpoints, response parsing, and error management, allowing PromptUnit to take care of routing, failover, cost monitoring, and quality assessment. It meticulously logs every API interaction, detailing aspects such as model, feature, user segment, token count, latency, and cost, thereby providing immediate insights into AI expenditures before any routing adjustments are implemented. In its observation mode, PromptUnit meticulously monitors traffic, shadow-classifies incoming requests, predicts potential savings, and clarifies routing choices, enabling teams to visualize exact savings prior to activating live routing. After activation, Smart Routing intelligently classifies tasks to direct each request to the most cost-effective model that meets the established quality standards. Additionally, PromptUnit incorporates features like prompt compression, token inflation protection, efficiency scoring for prompts, semantic request caching, and multi-model consensus for enhanced performance. Its comprehensive approach ensures that organizations can optimize their AI usage and manage budgets effectively.

AAES Govern is a self-hosted software solution that is currently in its pre-launch phase, designed to handle enterprise AI agent requests via pre-established credential pathways. It verifies user permissions, mandates necessary human approvals, and enforces spending limits by reserving evaluated amounts prior to final authorization, while also documenting signed decisions to ensure offline integrity. While an agent can utilize direct credentials or an alternate route to bypass these enforcement measures, integrations that only observe cannot halt ongoing activities. Customers have the option for evaluation through a paid design partnership costing USD 40,000 for a three-month period, which includes both AAES Govern and the distinct AAES Operate product; however, the rates for production are not publicly disclosed. Although managed hosting for Govern is planned, it is not currently available. Additionally, the separately released aaesverify CLI, which is licensed under Apache-2.0, is capable of verifying the integrity of exported records against a trusted public key, but it does not provide assurances regarding complete data capture, input accuracy, or downstream execution fidelity. Notably, AAES has yet to showcase any production customer results or obtain independent certification for its offerings, highlighting a gap in third-party validation. This absence of verified performance raises questions about the software's readiness for widespread implementation in enterprise environments.

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.

StackRails serves as a platform designed for software architecture and AI coding governance specifically tailored for engineering teams. It creates a dynamic knowledge graph that encompasses repositories, services, APIs, events, and cloud infrastructure, enabling coding agents to access architecture and policy insights via the Model Context Protocol (MCP). This platform is compatible with tools like Claude Code, GitHub Copilot, Cursor, and OpenAI Codex, ensuring that generated code adheres to rules set by the organization on developers’ local machines and during pull-request processes. Engineering teams can leverage its capabilities to trace cross-repository dependencies, evaluate the impact of changes, keep architecture documentation up to date, oversee engineering policies, and conduct AI-driven architectural assessments. StackRails offers flexibility in deployment; it can be utilized as a hosted service in the EU, within customer-managed cloud settings on platforms such as AWS, Microsoft Azure, or Google Cloud, and it also supports on-premises installations for added security and control. This versatility ensures that organizations can adopt StackRails in a manner that best suits their operational needs and compliance requirements.

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.

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.

Eyrane is an innovative AI security platform that is currently being developed for teams focused on security and engineering, specifically those managing agents and automated processes. Its primary function is to assist organizations in identifying various components such as agents, models, tools, MCP servers, identities, credentials, permissions, and interconnected systems while also mapping the access pathways between these elements. The platform is engineered to enforce runtime policies that dictate whether agent actions are permitted, require evaluation, or are prohibited based on factors like identity, permissions, tools, and the sensitivity of the data involved. Additionally, Eyrane evaluates agent performance in relation to potential threats, including prompt injection, misuse of tools, abuse of privileges, data exfiltration, and scenarios connected to MCP. Potential applications of Eyrane encompass agent inventory management, access audits, runtime monitoring, enhancing MCP security, and facilitating AI red teaming exercises. Ultimately, Eyrane aims to empower security and engineering teams as they deploy AI agents within business applications and workflows, ensuring comprehensive oversight and control. This dual focus on security and efficiency makes Eyrane a vital tool in the evolving landscape of AI governance.

Domino is a comprehensive enterprise AI platform that enables organizations to transform AI initiatives into scalable, production-ready systems. It supports the full AI lifecycle, including data access, model development, deployment, and ongoing management. The platform provides a self-service environment where data scientists can access tools, datasets, and compute resources with built-in governance and security controls. Domino allows teams to build machine learning models, generative AI applications, and intelligent agents using their preferred development environments. It also includes advanced orchestration capabilities to manage workloads across hybrid, multi-cloud, and on-premises infrastructures. Governance features such as model registries, audit trails, and policy enforcement ensure compliance and reproducibility. The platform enhances collaboration by providing a centralized system of record for all AI assets and experiments. Additionally, it helps organizations optimize costs through resource management and usage tracking. Domino is designed to meet enterprise standards for security and regulatory compliance. Ultimately, it empowers businesses to accelerate AI innovation while maintaining operational control and accountability.

OwlVigil serves as a cloud-centric AI gateway and governance solution tailored for developers, AI product teams, and organizations managing various model providers. It facilitates the routing of AI requests via a consolidated endpoint, enabling teams to link providers, create scoped gateway keys, oversee access, and implement routing and policy rules. Administrators have the capability to define budgets for workspaces, teams, members, or keys; limit access to specific models and providers; and keep track of requests, tokens, usage, latency, and expenditures. With features like role-based permissions, audit logs, alerts, and request analytics, teams can effectively assess AI operations across different workspaces and departments. The platform supports OpenAI-compatible requests, which permits teams to integrate existing applications through a common interface seamlessly. OwlVigil is available as a hosted service that includes an individual free plan, alongside paid plans for teams and businesses, as well as customized options for enterprises seeking tailored solutions. This flexibility ensures that users can select the plan that best fits their specific needs and scales appropriately with their operations.