Alternatives to Preloop

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.

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.

MuleSoft provides a unified platform for enterprises that need to connect, manage, govern, and orchestrate AI agents, APIs, models, applications, and data at scale. It serves as an agentic control plane that helps organizations bring structure and visibility to fast-growing AI environments. Through MuleSoft Agent Fabric, companies can govern and coordinate agents regardless of where they were built, helping improve performance, compliance, and return on investment. MuleSoft Omni Gateway extends control across APIs, agents, and models, allowing teams to manage development, deployment, security, and policy enforcement from a single place. The platform also includes tools such as Agent Registry and Agent Scanners to identify, catalog, and monitor agents across major AI platforms. With Agent Broker and A2A support, MuleSoft helps agents collaborate across systems while giving businesses more control over how tasks are routed and completed. Organizations can also use MuleSoft MCP Support and Anypoint Connectors to transform existing applications, APIs, and systems into resources that AI agents can use. For developers, MuleSoft offers options ranging from natural language building with MuleSoft Vibes to pro-code development with Anypoint Code Builder. MuleSoft is designed for enterprises that want to scale agentic AI securely while maintaining governance, integration, observability, and operational consistency.

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.

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.

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.

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.

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

Humatron serves as a comprehensive AI workforce platform, transforming AI agents into secure and trusted digital workers that seamlessly integrate with various teams, tools, and business processes. Organizations have the ability to construct, recruit, tailor, train, oversee, and regulate these AI workers from a unified control dashboard, treating them more like digital personnel rather than mere assistants. Each AI worker can leverage advanced core agents, such as Claude, OpenAI, Manus, OpenClaw, Hermes, Cursor, or bespoke agent systems, which grants businesses the flexibility to interchange or update underlying models without altering the workforce layer. These AI workers are capable of operating independently, initiating and completing tasks, collaborating with team members, acquiring new skills, and communicating through established platforms like email, Slack, Teams, Zoom, and phone. The platform allows for the creation of builds that define reusable tools, rules, behaviors, and agent integrations, while each individual worker operates as a distinct instance tailored to meet the specific needs of a company, team, and role. This level of customization ensures that businesses can optimize their AI workforce to align perfectly with their operational goals.

ClawTab oversees the management of Claude Code, Codex, OpenCode, and shell tasks within persistent tmux sessions. An autonomous daemon efficiently manages schedules, monitors agent statuses, assigns task titles, detects questions, sends notifications, and maintains remote connections, all while the desktop application remains inactive. Users can utilize terminal tools, the tmux plugin, or the macOS desktop application to control agents seamlessly. It is possible to access the same live sessions from an iPhone, iPad, or web browser, allowing for real-time output tracking, question responses, and work initiation on a Mac or connected Linux system. All applications and local tools are freely available and licensed under the MIT license. You can self-host the relay without any cost or opt for the hosted Remote service for a subscription fee of $4.99 per month. Additionally, the flexibility of using multiple devices enhances productivity by ensuring you can always stay connected to your work.

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.

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

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

Dograh is a self-hostable voice agent platform that is open source and features a no-code workflow builder designed for developing production-ready voice agents. Teams have the flexibility to select their preferred inbound channels, speech-to-text services, language models, text-to-speech options, and telephony providers, or they can opt for innovative speech-to-speech models that facilitate direct audio interactions with seamless turn-taking, interruption management, and minimal latency. The platform caters to both inbound and outbound calling, offering widgets, telephony integrations, observability, tracing capabilities, real-time analytics, and a hybrid approach that combines pre-recorded voice with TTS, all while supporting over 70 languages. Additionally, the MCP server enables various agent runtimes, including Claude Code, Cursor, OpenClaw, and Codex, to create, modify, and deploy voice agents directly from development environments. Dograh can be operated on personal servers, within a private cloud or virtual private cloud, or in a managed setting, ensuring that models can be hosted entirely within the user's infrastructure. With its extensive features and adaptability, Dograh stands out as a versatile solution for teams looking to innovate in voice technology.

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.

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.

SuperBased serves as a local-first control hub for AI coding agents, enabling developers to monitor, manage, and optimize agent performance from a single binary installed on their personal computers. It seamlessly integrates with 40 coding tools by directly reading native session data, eliminating the need for proxies, SDK modifications, or complicated setups, and supports various agents including Claude Code, Codex, Cursor, GitHub Copilot, OpenCode, Gemini CLI, Kilo Code, Qwen Code, Aider, Devin, and others. The intuitive dashboard provides insights into token usage reported by providers, cache operations, expenses, session tracking, and forecasts for future messaging costs across tools that typically maintain isolated data. Developers can initiate over 20 CLI agents as terminal sessions, manage multiple repositories from a single interface, connect to an active agent, take control of the keyboard, and relinquish control when necessary. Additionally, model routing capabilities enable teams to effectively align tasks with the most suitable models, while egress gates allow for pre-execution command holds, giving users the power to halt or redirect actions that may be costly or pose risks. This comprehensive solution empowers developers to enhance their workflow and maintain better oversight over their coding agents.

Spawn serves as an innovative tool within OpenRouter for effortlessly deploying AI coding agents on your infrastructure using just a single command. You can select your desired agent, pick a cloud provider, and Spawn will take care of provisioning a virtual machine, installing the chosen agent along with its necessary dependencies, authenticating to both OpenRouter and the cloud via a CLI OAuth process, configuring all required endpoints and model routing, and finally initiating an SSH session so you can begin your tasks immediately. Each combination of agent and cloud is encapsulated in a standalone script, thus eliminating the need for Terraform or YAML and ensuring that deployments remain portable. The agents supported include Claude Code, OpenClaw, Codex CLI, OpenCode, Kilo Code, Hermes Agent, Junie, Pi, Cursor CLI, and T3 Code, which simplifies the exploration of various coding-agent workflows or allows for seamless switching between them with a single command. In addition to cloud platforms such as DigitalOcean, Sprite, Hetzner Cloud, AWS Lightsail, GCP Compute Engine, and Daytona, Spawn also accommodates local setups or ephemeral local Docker environments. This versatility ensures that developers can choose the best environment suited to their needs.

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.

Agentcard provides a secure method for AI agents to conduct online transactions by generating disposable virtual Visa cards tailored for agent operations. This innovative solution eliminates the need to share actual card information in conversations or require human intervention for checkout, as users can issue single-use cards that come with predetermined spending limits and automatically deactivate after a single authorized transaction. The system is built around user control, ensuring that every card and charge requires human approval, that real card information is never disclosed to agents, and that users receive alerts whenever an agent attempts to create a card or execute a payment. Furthermore, it seamlessly integrates with various platforms, including ChatGPT, Claude Desktop, Claude Code, OpenClaw, Cursor, and MCP-compatible agents through one-click setups, an MCP server, CLI tools, REST API, a Chrome Extension, and administrative tools for organizations. Users have the ability to create cards, monitor balances, review transaction histories, deactivate cards, and utilize these cards for online purchases while maintaining oversight and control throughout the process. This user-centric design ensures that the integrity and security of financial transactions remain uncompromised, allowing for a smooth and efficient interaction between agents and payment systems.

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

Bevel serves as a vendor-neutral, Git-integrated control plane tailored for enterprise AI agents, allowing organizations to define their agents, context, skills, tools, permissions, and identities as owned files within their infrastructure, which can then be accessed by any agent runtime through MCP. The context is organized as typed knowledge nodes, each with documented provenance detailing its source, the last modification, and verification timestamps, and this information is compiled into a navigable graph that can be updated and utilized for creating dashboards. Skills are articulated as straightforward Markdown procedures, enabling process owners to easily read, review changes, and transfer them across different runtimes. Additionally, tool manifests outline the capabilities available, while sensitive information is stored securely in a vault, governed by access rules that dictate which agents can read certain files or invoke specific endpoints. Each agent is assigned a unique identity and credentials, ensuring that all actions can be traced back to their source. This comprehensive framework not only enhances security and organization but also promotes transparency and accountability in AI operations.

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

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

SEAOTTER serves as a managed control plane specifically designed for the Hermes Agent on Google Cloud, providing isolated and consistently active agents without the need for VPS or SSH access. Users can easily create an agent via the dashboard, and within minutes, SEAOTTER sets up a dedicated namespace for each agent using a gVisor sandbox. The system allows for actions such as pausing, restarting, restoring, and reprovisioning through both API and user interface, all while offering integrated logs and metrics without the necessity of SSH access. Sensitive information is securely managed in a write-only section and stored within Google Secret Manager, with Hermes loading the secrets at startup, ensuring that users should refrain from sharing keys in chat. Upon signing up, users can connect using an organization-scoped so_ MCP key from Cursor, Claude, or Codex, while Hermes acts as the operational hub featuring various tools, memory management, and cron capabilities, all hosted in the us-central1 region. A trial period of seven days is available without requiring a credit card, allowing users to utilize one agent with limited resources (1 CPU / 4Gi / 8Gi). Following the trial, the cost for each always-on agent is $99 per month, with additional agents available for an extra $99 each, and custom solutions can be arranged through a consultation. This streamlined approach makes SEAOTTER an efficient choice for deploying agents in a managed cloud environment.

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.

AgentSky is a comprehensive platform that offers agent-as-a-service solutions for deploying persistent, always-active AI agents in the cloud, eliminating the need for Mac minis, extensive setups, or any infrastructure management. Users are able to select an agent harness, such as Claude Code, Codex, Hermes, or OpenClaw, pair it with an appropriate model, enhance its capabilities, and initiate it effortlessly with a single click. These agents are accessible through various platforms including WhatsApp, iMessage, Telegram, Slack, Discord, web chat, the A2A protocol, and the CLI, ensuring consistent history, tools, and state across different communication channels. Additionally, local setups of Claude Code, Codex, or OpenClaw can be seamlessly transferred to the cloud, maintaining all instructions, model configurations, and MCP servers while avoiding the transfer of sensitive information like secrets, API keys, or session history. Every agent operates as a managed worker featuring a durable state, ongoing history tracking, snapshots, backups, restoration capabilities, and an isolated sandbox environment that starts up with only the tools that are attached, ensuring both security and efficiency. This innovative approach allows for greater flexibility and scalability in deploying AI solutions tailored to user needs.

The Aditya Protocol serves as a control plane for operations that have been reviewed, specifically designed for teams engaging with AI agents, scripts, CI/CD processes, internal tools, and automation that are close to production environments. This innovative solution enables technical teams to request, review, approve, execute, and document crucial operational activities under human supervision, incorporating features such as reviewed command flows, rationale prompts, approval statuses, run histories, artifacts, access-token guidance, node-token guidance, settings controls, and workflows focused on providing evidence. Currently, the Aditya Protocol is available for a limited supervised pilot program involving select trusted technical reviewers and service-provider partners, and it is explicitly not intended as a wide-scale public release, certification tool, legal advisory resource, or a substitute for human operational judgment. As such, the protocol emphasizes the importance of human oversight in all operational processes it facilitates.

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

Zooid is a collaborative chat application that operates on the Matrix protocol and is available as open-source software, providing features like channels, threads, direct messaging, and spaces for team communication. The app allows for self-hosting, ensuring that all conversation records and user data are maintained within the infrastructure managed by the operator. One notable aspect of Zooid is its capacity to integrate AI agents directly into the same chat rooms as human participants, enhancing collaboration. Agents that are compatible with the Agent Client Protocol (ACP), including Claude Code, Codex, and opencode, can seamlessly join conversations, where their interactions are displayed as structured interface components instead of simple text; for instance, permission requests are visualized as approval cards, tool interactions are shown as structured data, task outlines appear as checklists, and sub-agent hierarchies are represented as expandable trees. Each AI agent operates within its own secure sandbox environment. Zooid is distributed under the MIT license, allowing for complete end-to-end self-hosting capabilities, providing users with the flexibility and control they need over their communication tools. This combination of features makes Zooid an appealing choice for teams looking to leverage both human and AI collaboration effectively.

AgentKey seamlessly integrates your AI agents with external data sources using a single key, enabling them to perform real tasks effectively. While your agent may possess the knowledge to undertake specific actions, it requires access to the appropriate APIs and services to execute them successfully. AgentKey streamlines this process, allowing the agent to conduct extensive searches, extract information from web pages, gather social insights, and incorporate context from various sectors like finance, ecommerce, business, crypto, and on-chain data in one comprehensive operation. Designed to work with platforms such as Claude Code, Codex, Cursor, Windsurf, Gemini CLI, OpenClaw, Hermes, Antigravity, and Warp, as well as any system that is compatible with MCP or Skills files, AgentKey equips agents with the ability to access a wealth of information without the hassle of managing multiple provider dashboards. The search capabilities encompass services like Brave Search, Tavily, Serper, Perplexity, Parallel, and Exa, while scraping functionalities leverage tools like Firecrawl, Jina, and Bright Data to convert web content into actionable insights. This innovative solution not only enhances efficiency but also empowers agents to deliver more informed and context-rich outcomes in their operations.

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.

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.

claude-mem serves as an offline-first cloud memory solution for AI agents, centered around an open source engine along with a cloud synchronization layer that connects agent memories universally through a single private MCP link. Its design ensures that coding agents and AI assistants do not begin from scratch in each session, regardless of the machine or editor in use. As agents work, claude-mem efficiently records notes that encapsulate decisions, solutions, obstacles, environmental insights, architectural choices, and a variety of structured observations within a temporal database. The CMEM Cloud then replicates this local memory through a private Model Context Protocol endpoint, enabling any compatible agent or integrated development environment to access and modify the same memory across various platforms such as Claude Code, Cursor, Windsurf, OpenCode, Codex CLI, Gemini CLI, and VS Code. Operating primarily in a local setting, it maintains functionality whether or not a network connection is available, and ensures that memory is kept in sync whenever cloud access is present. This innovative approach enhances the continuity of AI interactions, facilitating a smoother experience for developers and users alike.

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

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.

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

Data Flow Manager is an Agentic AI Control Plane for Apache NiFi Operations, built for enterprises running NiFi at real scale. Run, manage, and fix NiFi challenges across all clusters, environments, and flows using simple natural-language prompts. One platform. One control plane. Zero firefighting. DFM replaces fragmented UIs, brittle scripts, and reactive operations with centralized, AI-driven control, enabling NiFi teams to transition from manual operations to governed, autonomous execution.

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.

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

EasyClaw is a user-friendly desktop application designed to streamline the installation and operation of the OpenClaw autonomous AI agent stack on your local machine, eliminating the need for DevOps skills, Python expertise, Docker usage, or complex configuration, and features a simple one-click setup along with an intuitive graphical dashboard for quick deployment across various popular messaging platforms. After installation, EasyClaw automatically handles the OpenClaw runtime and seamlessly connects your AI agents, like ClawdBot and MoltBot, to messaging applications including WhatsApp, Telegram, Signal, and iMessage, allowing for effortless interaction with your assistant using natural language through the platforms you already use. Operating natively on your computer ensures that all processes are executed locally, which safeguards your privacy and data security while enabling the agent to automate a wide array of tasks such as managing your inbox, summarizing documents, providing reminders, translating in real-time, comparing prices, and facilitating other personalized workflows without relying on cloud services. This comprehensive functionality allows users to enhance their productivity and streamline daily tasks in a secure and efficient manner.

Rapid Claw is a cloud-based hosting solution designed specifically for OpenClaw, allowing users to quickly set up and operate a fully autonomous AI agent within minutes, all without the need to deal with infrastructure, configuration, or DevOps responsibilities. This platform offers a dedicated and private instance of OpenClaw that runs perpetually in the cloud, enabling the AI agent to carry out essential tasks like managing emails, automating workflows, reviewing code, processing data, and engaging with various applications without any human involvement. By automating the setup, updates, security measures, and backups, it alleviates the challenges commonly associated with self-hosting, which usually entails server provisioning, dependency management, environment setup, and ongoing maintenance. Users can initiate their AI assistant without writing a single line of code, entering API keys, or executing terminal commands, and can start interacting with it immediately through an intuitive interface. This seamless experience makes it accessible for individuals and teams who want to leverage AI capabilities without the technical burden.

SimpleClaw enables users to launch a fully operational OpenClaw AI agent in less than a minute, eliminating the need for intricate infrastructure setups, server configurations, SSH keys, or any coding, which transforms a typically complicated installation into a seamless one-click deployment that swiftly activates your autonomous assistant. You have the option to select from various AI models, including Claude Opus 4.5, GPT-5.2, or Gemini 3 Flash, while SimpleClaw manages the hosting environment, provides a pre-configured OpenClaw runtime, and maintains the backend to ensure your assistant operates around the clock. Once your OpenClaw instance is up and running, it can perform a variety of real-world digital tasks, such as reading and summarizing emails and lengthy documents, drafting responses and follow-ups, offering real-time translations, organizing your inbox, addressing support tickets, scheduling meetings through chat, keeping you informed about deadlines, planning your week, tracking expenses, comparing prices, managing subscriptions, and much more. This level of automation not only saves time but also enhances productivity, allowing you to focus on other essential tasks in your daily routine.

Paperclip.inc is an AI company orchestration platform that helps businesses manage AI agents like a structured team. Instead of running many separate AI tools manually, users can manage every agent, task, approval, and routine from one organized workspace. The platform supports popular AI models and agents, including Claude, Codex, Gemini, Cursor, DeepSeek, Qwen, Kimi, GLM, MiniMax, OpenCode, Hermes, and more. Paperclip.inc gives each task business context by connecting goals from the company level down to teams, agents, and individual work items. Built-in budget controls prevent overspending by pausing agent work when a spending cap is reached. Permission settings allow users to decide which agent actions are automatic, approval-required, or blocked. The system also includes immutable audit logs and one-click rollback so teams can review decisions and recover from unwanted changes. Recurring routines can run on schedule in the cloud, allowing work such as reporting, monitoring, and operational digests to continue around the clock. With pre-built AI companies, EU hosting, managed updates, and open-source control plane technology, Paperclip.inc helps organizations scale agentic work without losing visibility or governance.