Alternatives to Agent Control

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

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

The Teradata Enterprise AgentStack is a comprehensive platform designed for the development, deployment, and management of enterprise-level autonomous AI agents that seamlessly connect to reliable data and analytics, aiding businesses in transitioning from experimentation phases to fully operational agentic AI with robust enterprise control. This platform consolidates diverse functionalities to facilitate the entire agent lifecycle; AgentBuilder streamlines the process of creating intelligent agents through both no-code and pro-code tools that are compatible with Teradata Vantage and various open-source frameworks. Furthermore, the Enterprise MCP provides secure, context-rich access to well-governed enterprise data along with tailored prompts that enhance agent intelligence. Meanwhile, AgentEngine ensures scalable agent execution while maintaining consistent memory and reliability across various hybrid environments. Additionally, AgentOps plays a crucial role in centralizing the monitoring, governance, compliance, auditability, and policy enforcement, ensuring that the agents operate within established parameters, which ultimately leads to increased efficiency and adherence to organizational standards. Collectively, these features empower organizations to harness the full potential of autonomous AI in a controlled and efficient manner.

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

Fluq serves as an observability and orchestration platform for AI agents, providing teams with comprehensive real-time visibility and control over their operations. It functions as an integrated “single pane of glass” that meticulously tracks and visualizes every action performed by agents, including LLM calls, tool usage, file handling, token expenditure, and related costs through intricate waterfall traces. By utilizing a lightweight proxy to manage all agent requests, Fluq ensures minimal setup requirements and is compatible with any LLM provider or agent framework, facilitating seamless integration into existing systems without the need for code modifications. This platform empowers teams to analyze every decision made by an agent, investigate execution steps, and gain a clear understanding of how outcomes are derived, thereby enhancing transparency and ease of debugging. Furthermore, it incorporates governance capabilities such as policy enforcement, spending limits, approval gates, and access controls, which help mitigate risks like excessive costs, misuse of tools, and generation of incorrect outputs. Through these robust features, Fluq not only improves operational oversight but also fosters trust in AI systems by ensuring responsible usage and accountability.

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.

The HelpNow Agentic AI Platform by Bespin Global is a robust automation and orchestration solution designed for enterprises, enabling them to swiftly develop, implement, and oversee autonomous AI agents that are specifically aligned with their business processes, all without the need for extensive coding skills. This is achieved through a visual interface known as Agentic Studio and a centralized management portal, which allows for the creation of both single and multi-agent workflows, seamless integration with current systems using APIs and connectors, and real-time performance monitoring through an Agent Control Tower that ensures governance, enforces policies, and maintains quality standards. Furthermore, the platform facilitates LLM orchestration, accommodates various input formats (including text, voice, and STT/TTS), and offers flexible deployment options across multiple cloud environments such as AWS, GCP, Azure, and on-premises solutions, while ensuring connectivity to internal data and documents. By tapping into context-rich enterprise information, these agents are empowered to perform effectively. Additionally, the platform encompasses features for managing the entire lifecycle of agents, providing real-time observability, and integrating with both voice and document processing systems, all while adhering to enterprise governance protocols. Thus, organizations can harness advanced AI capabilities without compromising on control or oversight.

Strands Agents SDK is an open-source development framework that allows developers to build and manage AI agents with precision and control. It supports both Python and TypeScript, making it accessible to a wide range of developers and use cases. Instead of relying on rigid workflows or orchestration layers, the SDK lets developers define tools as functions and rely on the model’s reasoning capabilities to drive execution. The platform works across any AI model or cloud environment, offering flexibility for deployment and scaling. One of its standout features is the use of steering hooks, which act as middleware to guide, validate, and correct agent actions in real time. It also includes support for multi-agent systems, enabling complex workflows through agent collaboration. Built-in memory management ensures context is maintained across long interactions without manual intervention. Developers can monitor performance through observability tools that provide detailed traces and metrics. The SDK also includes an evaluation framework for testing agent accuracy and behavior before deployment. Overall, Strands Agents SDK empowers developers to create reliable, scalable, and intelligent AI agents with minimal complexity.

Obot functions as an open-source AI infrastructure platform and Model Context Protocol (MCP) gateway, providing organizations with a centralized control system to discover, onboard, manage, secure, and scale MCP servers, which facilitate the connection of large language models and AI agents to various enterprise systems, tools, and data sources. It incorporates an MCP gateway, a catalog, an administrative console, and an optional integrated chat interface, all within a modern design that works seamlessly with identity providers like Okta, Google, and GitHub to implement access control, authentication, and governance policies across MCP endpoints, thus ensuring that AI interactions remain secure and compliant. Moreover, Obot empowers IT teams to host both local and remote MCP servers, manage access through a secure gateway, establish detailed user permissions, log and audit usage effectively, and create connection URLs for LLM clients, including tools like Claude Desktop, Cursor, VS Code, or custom agents, enhancing operational flexibility and security. Additionally, this platform streamlines the integration of AI services, making it easier for organizations to leverage advanced technologies while maintaining robust governance and compliance standards.

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.

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.

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.

GraphBit is a robust AI framework tailored for enterprises, intended to manage essential AI systems while ensuring security, governance, and reliable production performance. By leveraging a high-performance Rust execution core along with a Python wrapper, it offers developers an optimal blend of orchestration efficiency and Python's user-friendly nature, enabling the creation of dependable multi-agent workflows that consume minimal CPU and memory resources. The architecture of GraphBit is meticulously structured to mitigate risks, incorporating various layers such as interfaces, configuration, models, tools, actions, memory, orchestration, and observability. This framework seamlessly integrates with existing applications, facilitates the development of bespoke AI interfaces, and allows users to engage through intuitive workflows while maintaining controlled actions. Teams are empowered to set policies, rules, and guardrails from a central location, with GraphBit ensuring compliance without necessitating modifications to application code. Additionally, it accommodates LLMs and multimodal models sourced from diverse providers, providing teams with the flexibility to interchange models effortlessly while preserving workflows and governance. With its comprehensive design, GraphBit not only enhances operational efficiency but also fosters innovation by enabling teams to focus on developing advanced AI solutions.

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

Sapiom serves as a financial and access infrastructure platform that allows AI agents and API-driven applications to securely access, provision, and pay for various third-party services, APIs, tools, and compute resources in real-time, eliminating the need for manual onboarding, individual management of API keys, and the necessity of pre-purchased credits. It features a centralized dashboard that enables organizations to keep track of overall spending, agent activities, service utilization, and real-time analytics, while also allowing the establishment of rule-based spending and usage limits, alongside the enforcement of governance policies to ensure that autonomous agents operate securely within set financial boundaries. Additionally, Sapiom offers SDKs and APIs that empower developers to link agents to a selective network of services, including verification processes, web searching, AI models through OpenRouter, and automation of image/audio generation and browser tasks, facilitating automated authentication and micro-payments for each use. This system meticulously tracks every API invocation, associated costs, and execution traces, ensuring comprehensive visibility and control over operations, which ultimately enhances the operational efficiency of organizations leveraging its capabilities.

Develop your own customized policies that extend beyond typical abuse classifications and implement them swiftly. Intrinsic serves as a platform designed to create AI agents focused on fostering user trust by integrating seamlessly into your current workflows, gradually improving human oversight through safe automation. Streamline the moderation process for text, images, videos, and reports with a system that continuously enhances its performance with each moderation attempt. Efficiently handle review queues and escalation processes using detailed Role-Based Access Control (RBAC) permissions. Utilize insights from performance reports and comprehensive health monitoring across the platform to make informed, data-driven decisions. Benefit from cutting-edge security features, AI-enhanced analytics, and extensive information governance to ensure your operations remain robust and compliant. With these tools, organizations can maintain high standards of user engagement and safety.

WSO2 Bijira is an advanced SaaS platform designed for managing the complete lifecycle of APIs with a focus on AI and cloud-native capabilities, handling aspects such as design, security, governance, deployment, and monitoring for both internal and external APIs, as well as those driven by AI, across hybrid and multi-cloud settings. It features a centralized control panel that ensures uniform API policy, security measures, and analytics, while also offering tools for visual API proxy mapping, intuitive drag-and-drop policy management, and a customizable developer portal aimed at enhancing API adoption and reuse. By harnessing AI technologies, Bijira facilitates the generation of OpenAPI specifications, performs API testing through natural language inputs, ensures compliance with governance standards, and integrates valuable insights back into the API development workflow. Additionally, it incorporates robust security features, such as OAuth2, OIDC, and fine-grained access control, while promoting governance-as-code through AI-driven policy validation to ensure comprehensive oversight and reliability. This innovative approach empowers organizations to optimize their API strategies and streamline their integration processes effectively.

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.

Zapper Edge is a cloud-native, enterprise-grade Managed File Transfer (MFT) solution crafted to facilitate secure, compliant, and efficient file transfers among partners, vendors, and applications. Functioning as the command center for file management, it upholds zero-trust security principles, implements role-based access control (RBAC) with a defense-in-depth strategy, and incorporates single sign-on (SSO), PGP encryption, customer-managed keys (CMK), and governance based on policies. The platform is equipped to handle Data Lifecycle Management and Data Loss Protection, allowing users to upload, download, preview, delete files, and perform bulk operations while ensuring detailed access control and immutable audit trails. Additionally, it features SIEM-enabled incident reporting and real-time monitoring capabilities, which provide essential visibility for swift detection, investigation, and compliance documentation. Designed with Azure in mind, Zapper Edge boasts rapid performance, the ability to scale horizontally, effortless deployment, and integrated data residency controls. Moreover, it includes an AI Agent Orchestration layer that supports governed API-based data access and features a RAG Foundry, facilitating the creation of micro-level, sanctioned data subsets for secure and efficient retrieval. This comprehensive suite of tools makes Zapper Edge a robust choice for organizations seeking to enhance their file transfer security and operational efficiency.

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.

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.

Agent 365 is Microsoft’s new enterprise framework for managing AI agents with the same rigor and structure used for human users. It centralizes oversight by providing a registry that surfaces every agent operating within your organization, including identity-secured agents, internally registered agents, and automatically detected shadow agents. The platform enhances security by extending Microsoft Defender protections, Entra identity access controls, and Purview governance policies to all agents. Agent 365 integrates with Microsoft 365, Power Apps, Power Automate, and Power BI, enabling agents to participate in workflows, analytics, and productivity tasks just like any other digital worker. Using Work IQ, organizations can equip agents with deep contextual understanding sourced from company data, relationships, and internal systems. This unified approach simplifies deployment, strengthens compliance, and improves operational insight for IT teams. Through Microsoft’s Frontier early access program, IT admins can explore and activate Agent 365 directly in the Admin Center. Microsoft built Agent 365 to support the rapidly growing role of AI agents across enterprise environments, ensuring they remain secure, governed, and aligned with organizational standards.

VoltusWave is an advanced platform for enterprise AI agent workforces that transcends the limitations of standalone automation tools by integrating intelligent agents within a comprehensive execution framework capable of managing end-to-end business processes. This platform offers a cohesive environment where AI agents can interpret documents, make informed decisions, carry out workflows, and address exceptions, all while ensuring full audit trails and human intervention capabilities are in place. It operates through six interconnected engines, which include process orchestration, rules enforcement, document generation, integration infrastructure, no-code application development, and a regulated AI agent workforce, empowering organizations to efficiently manage intricate operations like procure-to-pay or enterprise-to-cash cycles with minimal human input. These AI agents function across all operational layers, dealing with tasks related to documents, approvals, reconciliations, compliance verification, and customer communications, while a robust rules engine guarantees that every action adheres to established guidelines with complete version control and traceability. This holistic approach not only streamlines processes but also enhances overall efficiency and accountability within the organization.

Microsoft Copilot Studio is a powerful and flexible platform designed to help users create, customize, and manage AI-driven agents tailored to meet diverse business needs. Combining the simplicity of low-code development with the advanced capabilities of generative AI, the platform enables users to design intelligent agents that can access and utilize internal knowledge bases, perform complex actions through a wide range of data connectors, and operate autonomously to streamline processes and improve productivity. These AI agents can be seamlessly integrated into existing workflows and deployed across various channels, including Microsoft 365 applications, internal websites, and mobile apps, ensuring they adapt to the unique operational environments of any organization. Furthermore, Copilot Studio includes a robust suite of governance and management tools, allowing IT teams to maintain centralized control over agent usage, monitor performance with detailed analytics, and enforce security policies. This combination of ease of use, advanced functionality, and comprehensive governance makes Microsoft Copilot Studio an invaluable tool for organizations looking to leverage AI to transform their business operations.

Oz serves as a cloud-centered orchestration platform tailored for AI coding agents, empowering developers and teams to effortlessly execute, oversee, automate, and expand an unlimited number of parallel cloud coding agents without the need for custom infrastructure. This platform offers programmable, auditable workflows that streamline repetitive development tasks and intricate code modifications, ensuring full control over the process. Users can initiate agents through various interfaces including the CLI, web application, APIs, SDKs, Warp Terminal, or mobile devices. Additionally, Oz allows for the orchestration of numerous agents simultaneously, complete with integrated audit trails, session tracking, and comprehensive visibility, and provides the capability to monitor or engage with active agents within a shared control environment. The platform also accommodates flexible hosting options, whether on your own infrastructure or Warp's, while ensuring that each agent operates within secure, isolated environments. Oz produces tangible artifacts such as plans and pull requests, and is adept at managing multi-repo alterations, allowing agents to effectively synchronize extensive updates across vast codebases. With its robust features, Oz significantly enhances the efficiency of software development processes, making it an indispensable tool for modern development teams.

Token Security presents an innovative strategy tailored for the booming era of Non-Human Identities (NHI), emphasizing a machine-first approach to identity security. In today's digital landscape, identities are omnipresent and often unmanaged; they manifest as machines, applications, services, and workloads, continuously generated by various sources throughout the day. The intricate and sluggish nature of managing these identities has resulted in an attack surface that organizations find difficult to navigate. Rather than concentrating solely on human identities, Token prioritizes the resources being accessed, swiftly revealing who accesses which resources, identifying vulnerabilities, and ensuring security without disrupting operations. Furthermore, Token adeptly identifies all identities across cloud environments, seamlessly integrating intricate components such as Kubernetes, databases, servers, and containers, thereby consolidating relevant identity data into a cohesive perspective. This comprehensive approach not only enhances security but also simplifies the management of identities within increasingly complex infrastructures.

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

Agent Builder is a component of OpenAI’s suite designed for creating agentic applications, which are systems that leverage large language models to autonomously carry out multi-step tasks while incorporating governance, tool integration, memory, orchestration, and observability features. This platform provides a flexible collection of components—such as models, tools, memory/state, guardrails, and workflow orchestration—which developers can piece together to create agents that determine the appropriate moments to utilize a tool, take action, or pause and transfer control. Additionally, OpenAI has introduced a new Responses API that merges chat functions with integrated tool usage, alongside an Agents SDK available in Python and JS/TS that simplifies the control loop, enforces guardrails (validations on inputs and outputs), manages agent handoffs, oversees session management, and tracks agent activities. Furthermore, agents can be enhanced with various built-in tools, including web search, file search, or computer functionalities, as well as custom function-calling tools, allowing for a diverse range of operational capabilities. Overall, this comprehensive ecosystem empowers developers to craft sophisticated applications that can adapt and respond to user needs with remarkable efficiency.

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.

Shakudo represents the pioneering secure AI operating system designed specifically for enterprise data stacks, allowing organizations to effectively deploy, operate, and manage top-tier data and AI tools within their own infrastructures while maintaining full control, governance, and minimizing dependency on vendors. This platform can be seamlessly implemented within your Virtual Private Cloud (VPC) or on-premises, guaranteeing complete data sovereignty while streamlining DevOps workflows across all stages of the AI lifecycle, ranging from quick prototyping to comprehensive production. It includes a carefully curated selection of over 170 open-source and commercial stack components, such as orchestration tools, distributed computing frameworks, vector databases, and CI/CD pipelines, thus empowering teams to modify or change tools as their requirements change without the need for extensive infrastructure redevelopment. The integrated control plane of Shakudo offers a centralized interface for managing tools, monitoring expenses, enforcing policies, optimizing performance, and orchestrating models, jobs, and services, making it a versatile solution for modern enterprises. This holistic approach not only enhances operational efficiency but also supports continuous adaptation to the evolving technological landscape.

DigitalAPI is a comprehensive API lifecycle management platform that unifies how organizations handle APIs, events, and integrations across multiple gateways and cloud environments. It provides a centralized control plane for API discovery, governance, deployment, and monetization, reducing complexity and improving efficiency. The platform features a lightweight API gateway that allows rapid deployment without heavy development effort. It also includes a developer portal that simplifies API access and onboarding for internal and external users. DigitalAPI offers an external API marketplace where businesses can monetize their APIs and create new revenue streams. Its multi-cloud and multi-gateway capabilities ensure seamless integration and governance across distributed systems. The platform incorporates AI-ready features, enabling automation and interaction with APIs using natural language. It also provides analytics and reporting tools for tracking API usage and performance. With strong governance and security controls, organizations can maintain compliance and reduce risks. Overall, DigitalAPI empowers businesses to modernize their API ecosystem and scale efficiently.

Native serves as a cloud security control plane aimed at assisting organizations in establishing, executing, and upholding security policies throughout various cloud environments, encompassing contemporary AI infrastructures. Its primary objective is to deliver governance that is inherently secure, allowing teams to manage the provisioning, access, and oversight of AI services and cloud resources within their systems. Users can articulate their desired security objectives, which Native then translates into the necessary technical controls tailored for each cloud provider, thereby removing the need for manual interpretation of best practices or individual policy configurations for multiple environments. Additionally, Native enhances risk management through comprehensive visibility and planning tools that facilitate asset discovery, change simulation, and control implementation to mitigate risks and limit potential damages across systems. Moreover, it incorporates sophisticated functionalities such as environment segmentation, protection of data perimeters, and strategies for managing blast radius containment, further strengthening an organization’s security posture. By integrating these features, Native ensures a robust framework for cloud security management.

MCP-Use is an open-source platform designed for developers that provides an array of SDKs, cloud infrastructure, and an intuitive control interface to facilitate the creation, management, and deployment of AI agents utilizing the Model Context Protocol (MCP). The platform allows connections to various MCP servers, each offering distinct tool functionalities such as web browsing, file handling, or specialized third-party integrations, all accessible through a single, unified MCPClient. Developers are empowered to build custom agents (using MCPAgent) that can intelligently choose the most suitable server for each specific task by leveraging configurable pipelines or a built-in server management system. By streamlining processes like authentication, managing access control, audit logging, observability, and creating sandboxed runtime environments, it ensures that both self-hosted and managed MCP developments are primed for production use. Moreover, MCP-Use enhances the development experience by integrating with well-known frameworks such as LangChain (Python) and LangChain.js (TypeScript), significantly speeding up the process of building AI agents equipped with diverse tools. In addition, its user-friendly architecture encourages developers to innovate and experiment with new AI functionalities more efficiently.

nono is a novel open-source sandbox that utilizes kernel enforcement to create a secure environment for AI coding agents and LLM tasks. In contrast to traditional policy-based guardrails that merely monitor and filter operations, nono leverages operating system security features—specifically Landlock on Linux and Seatbelt on macOS—to render unauthorized operations impossible at the syscall level. With just a single command, you can encapsulate any AI agent, including Claude Code, OpenCode, OpenClaw, or any command-line interface process. The system automatically enforces a default-deny policy for filesystem access, restricts harmful commands (such as rm, dd, chmod, and sudo), isolates sensitive credentials and API keys, and extends all imposed restrictions to any child processes, ensuring there's no avenue for escape once limitations are set. Built-in profiles allow for rapid deployment, and secrets can be injected from the system keystore in a secure manner, with automatic zeroization upon exit. Additionally, future enhancements such as audit logging, atomic rollbacks, and Sigstore-attested policy signing are planned, offering robust tracking and security features. It operates under the Apache 2.0 license and is developed by the same creator behind Sigstore, further emphasizing its credibility and reliability in securing AI workloads.

Backslash Security is the governance and visibility platform built for organizations where AI coding tools are already part of how software gets built. GitHub Copilot, Cursor, Windsurf, Claude Code, and Gemini CLI have fundamentally changed the development lifecycle — and the security controls most organizations rely on were not designed for this environment. Backslash provides a comprehensive AI coding tool inventory and policy enforcement across the full AI coding spectrum, giving security teams visibility into every active tool and the risk introduced before it reaches production. This includes vibe coding security — risk detection purpose-built for vulnerability patterns in AI-generated code that traditional scanners are not equipped to catch. As AI coding agents grow more capable, they increasingly operate with access to external services, internal data, and organizational infrastructure through MCP servers. Over-permissioned agents and misconfigured MCP connections create data leakage pathways — exposing sensitive organizational data to AI models without security team awareness or enforcement controls. These are active exposure points, not theoretical risks. Backslash addresses this directly. The platform maps every MCP server connection, identifies over-permissioned AI agent configurations, and enforces least-privilege access before data leakage occurs. Security teams gain full visibility into what AI agents can access and where permissions exceed what the task requires. For security leaders governing an environment that moved faster than their controls, Backslash is the missing layer — built from the ground up for AI-native development, not retrofitted from a previous generation of tooling.

Gentoro is a comprehensive platform designed to enable enterprises to effectively harness agentic automation by seamlessly integrating AI agents with existing real-world systems in a secure and scalable manner. It operates on the Model Context Protocol (MCP), which empowers developers to effortlessly transform OpenAPI specifications or backend endpoints into production-ready MCP Tools, eliminating the need for manual integration coding. The platform efficiently addresses runtime challenges such as logging, retries, monitoring, and cost management, while simultaneously ensuring secure access, audit trails, and governance policies, including OAuth support and policy enforcement, regardless of whether it is deployed in a private cloud or an on-premises environment. Notably, Gentoro is model- and framework-agnostic, allowing for flexibility in integrating various large language models (LLMs) and agent architectures. This versatility aids in preventing vendor lock-in and streamlines the orchestration of tools within enterprise settings, as it manages tool generation, runtime operations, security measures, and ongoing maintenance all within a single integrated stack. By providing a unified solution, Gentoro enhances operational efficiency and simplifies the journey toward automation for businesses.

Ona, the evolution of Gitpod, is built to help teams move beyond traditional IDEs by serving as a central hub for modern software engineering. Its sandboxed environments run with full OS-level isolation, giving developers secure and consistent setups whether hosted in the cloud or on private infrastructure. With Ona Agents, teams can automate repetitive tasks, accelerate handoffs, parallelize work, and receive real-time support across scoping, coding, reviewing, and documentation. The platform ensures that developers can seamlessly switch between agent conversations, browser-based VS Code Web, or desktop IDEs without losing productivity. Enterprise-level guardrails reinforce compliance by offering detailed audit trails, network controls, and fine-grained organizational policies. Ona is already trusted by global enterprises in industries like banking and pharmaceuticals, highlighting its reliability at scale. Integrations with GitHub, GitLab, Redis, MongoDB, and AWS make it easy to connect existing workflows without disruption. With SOC 2 certification, GDPR compliance, and WCAGAA accessibility standards, Ona sets the standard for secure and inclusive developer productivity.

Microsoft Foundry Agent Service provides a unified environment for building intelligent agents that automate high-value tasks across an organization. It supports multi-agent workflows, hosted custom-code agents, and seamless integration with Azure Logic Apps and other enterprise systems. Developers can extend agent capabilities using built-in memory, ready-to-use tools, and secure connectivity powered by the Model Context Protocol. The platform includes deep observability features—such as tracing, dashboards, and guardrails—to ensure safe, reliable, and cost-efficient operations at scale. Built-in governance via Entra Agent ID gives each agent a managed identity with full lifecycle, access, and policy controls. Organizations can deploy agents directly into Teams and Microsoft 365 Copilot to bring automation into everyday employee workflows instantly. With more than 100 compliance certifications and enterprise-grade security, Foundry Agent Service supports even the most regulated industries. Its combination of extensibility, security, and operational readiness makes it a powerful foundation for enterprise-wide AI adoption.

UiPath Agentic Orchestration serves as the orchestration framework of the UiPath Platform, facilitating the integration and coordination of AI agents, robotic processes, APIs, workflows, and human involvement to carry out intricate, extended enterprise processes from start to finish with oversight, transparency, and ongoing enhancement. This platform transcends conventional automation by merging generative AI agents with RPA bots and human contributions, all within well-defined workflows, which fosters real-time collaboration, adaptive decision-making, and proactive solutions to challenges throughout both structured and unstructured data environments. Furthermore, it offers comprehensive orchestration, process modeling—including BPMN standards—along with seamless integration with external systems and robust monitoring capabilities, thereby allowing organizations to track operations, handle exceptions, and pursue continuous improvement through data-driven analytics. Enhanced by built-in governance, compliance mechanisms, and analytical tools, Agentic Orchestration streamlines the management of widespread automation while guaranteeing dependable performance. Its innovative approach not only boosts efficiency but also empowers organizations to adapt swiftly to changing market demands and operational challenges.

PaletteAI is a comprehensive platform for managing enterprise AI infrastructure that aims to enhance the speed of deploying, scaling, governing, and operationalizing AI workloads across various environments, including data centers, cloud, and edge computing. It offers a flexible, turnkey solution that empowers platform, DevOps, and AI/data science teams to create repeatable AI stacks that comply with governance requirements, integrating all necessary elements from storage to machine learning frameworks, thus eliminating the need for tedious manual configurations and enabling teams to swiftly establish new AI environments with just one click. Acting as a centralized control plane, it simplifies the entire lifecycle of AI infrastructure by allowing users to build, deploy, and oversee AI environments while maximizing hardware efficiency, maintaining security and policy protocols, and facilitating ongoing operations such as resource management and monitoring. By using PaletteAI, organizations can significantly reduce the time and effort needed to manage their AI infrastructure, allowing teams to focus more on innovation rather than maintenance.

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.

Gate22 serves as a robust AI governance and Model Context Protocol (MCP) control platform designed for enterprises, centralizing the security and oversight of how AI tools and agents interact with MCP servers within an organization. It empowers administrators to onboard, configure, and regulate both internal and external MCP servers, offering detailed permissions at the functional level, team-based access control, and role-specific policies to ensure that only sanctioned tools and functionalities are accessible to designated teams or users. By providing a cohesive MCP endpoint, Gate22 aggregates multiple MCP servers into an intuitive interface featuring just two primary functions, leading to reduced token consumption for developers and AI clients, while effectively minimizing context overload and ensuring both precision and security. The administrative interface includes a governance dashboard that allows for the monitoring of usage trends, compliance maintenance, and enforcement of least-privilege access, while the member interface facilitates streamlined and secure access to authorized MCP bundles. This dual-view approach not only enhances operational efficiency but also strengthens overall security within the organizational framework.

Defakto Security offers a robust platform that authenticates every automated interaction by providing temporary, verifiable identities to non-human entities like services, pipelines, AI agents, and machines, thereby removing the need for static credentials, API keys, and enduring privileges. Their comprehensive non-human identity and access management solution facilitates the identification of unmanaged identities across diverse environments such as cloud, on-premises, and hybrid settings, the issuance of dynamic identities in real time based on policy specifications, the enforcement of least-privilege access principles, and the generation of complete audit-ready logs. The solution comprises several modules: Ledger, which ensures ongoing discovery and governance of non-human identities; Mint, which automates the creation of purpose-specific, temporary identities; Ship, which enables secretless CI/CD workflows by eliminating hard-coded credentials; Trim, which optimizes access rights and eliminates excessive privileges for service accounts; and Mind, which safeguards AI agents and large language models using the same identity framework employed for workloads. Each module plays a critical role in enhancing security and streamlining identity management across various operational contexts.

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

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.