Alternatives to Kosmoy

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.

agentgateway is an AI-native gateway built to manage, secure, and observe modern AI and agentic systems. It acts as a centralized control plane for LLMs, AI agents, and tool servers using protocols like MCP and A2A. Designed specifically for AI workloads, agentgateway supports connectivity patterns that legacy gateways cannot. The platform provides secure LLM access, preventing data leaks, malicious prompts, and uncontrolled usage. Enterprises gain full visibility into how models, agents, and tools interact across the ecosystem. agentgateway simplifies governance with centralized policy enforcement and access control. It also enables consistent observability using standards like OpenTelemetry. As an open-source project hosted by the Linux Foundation, it promotes vendor-neutral interoperability. agentgateway helps organizations scale AI responsibly and securely. It delivers a future-ready foundation for agentic connectivity.

Dataiku is a comprehensive enterprise AI platform built to transform how organizations develop, deploy, and manage artificial intelligence at scale. It unifies data, analytics, and machine learning into a centralized environment where both technical and non-technical users can collaborate effectively. The platform enables teams to design and operationalize AI workflows, from data preparation to model deployment and monitoring. With its orchestration capabilities, Dataiku connects various data systems, applications, and processes to streamline operations across the enterprise. It also offers robust governance features that ensure transparency, compliance, and cost control throughout the AI lifecycle. Organizations can build intelligent agents, automate decision-making, and enhance analytics without disrupting existing workflows. Dataiku supports the transition from siloed models to production-ready machine learning systems that can be reused and scaled. Its flexibility allows businesses to modernize legacy analytics while preserving institutional knowledge. Companies across industries leverage the platform to accelerate innovation, improve efficiency, and unlock new revenue opportunities. By combining scalability, governance, and usability, Dataiku empowers enterprises to turn AI into a strategic advantage.

Liminal gives regulated organizations a single governed environment for AI. Rather than securing models an organization has already deployed, Liminal supplies the access itself, so protection is applied before anything reaches a provider. Employees work with leading models from Anthropic, OpenAI, Google and others through one interface, with policy-based routing and no per-provider contracts. Adding a new model becomes a policy decision rather than an integration project, and teams are never stuck waiting for procurement to catch up with what the market released. Sensitive terms are identified within each prompt and masked, redacted, flagged or blocked according to rules defined by data category rather than by department. Masked values are restored in the response, which keeps output usable while regulated information stays inside the organization. Employees never have to sanitize inputs by hand, which is what makes the governed path the one they actually choose. Administrators see who used which model, what rules were applied and where violations occurred. That record is generated at the time of the interaction, so audit requests are answered from existing evidence instead of reconstruction after the fact. Activity can be fed into existing security tooling and reviewed alongside other events rather than in isolation. The platform connects to internal systems through MCP, so employees bring organizational context into their work without moving data into tools nobody is watching. Access follows permissions that already exist. Deployments run on single-tenant infrastructure with SSO and role-based permissions, serving banking and credit unions, insurance, healthcare, education, state and local government, and life sciences.

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.

Solo Enterprise offers a comprehensive cloud-native application networking and connectivity solution that enables businesses to securely connect, scale, manage, and monitor APIs, microservices, and advanced AI workloads within distributed infrastructures, particularly in Kubernetes-based and multi-cluster environments. The platform's foundational features leverage open-source technologies such as Envoy and Istio, including Gloo Gateway, which facilitates omnidirectional API management by effectively handling external, internal, and third-party traffic while ensuring security, authentication, traffic routing, observability, and analytics. Additionally, Gloo Mesh provides a centralized control mechanism for multi-cluster service mesh, streamlining service-to-service connectivity and security across different clusters. Moreover, the Agentgateway and Gloo AI Gateway enable secure and governed traffic for LLM/AI agents, incorporating essential guardrails and integration capabilities to enhance functionality and security. This multifaceted approach ensures that enterprises can operate efficiently in a rapidly evolving technological landscape.

Unity AI Gateway offers a unified framework for governance, monitoring, and expenditure management across various AI systems within an enterprise, enabling organizations to oversee agents, tools, models, MCPs, and AI frameworks from a single, regulated interface. It ensures consistent governance across AI services such as Databricks-hosted AI, external models, coding agents, and agent harnesses, while avoiding vendor lock-in for teams. Policies that are aware of user identities regulate agent access, permissible actions, and tool usage, while integrated, custom, and third-party safeguards maintain safety and compliance throughout prompts, responses, and interactions. This system records prompts, traces, tool interactions, payload logs, audit trails, token usage, and policy decisions to facilitate behavior monitoring, incident investigations, and compliance assistance. Furthermore, centralized financial controls enable tracking of consumption across various users, teams, applications, agents, and providers, incorporating budgets, rate limits, and strict spending caps to optimize resource allocation. By streamlining these processes, Unity AI Gateway empowers organizations to harness AI technologies effectively while adhering to their governance and budgetary frameworks.

Openlayer is an AI governance, evaluation, and observability platform designed for teams building traditional machine learning, generative AI, RAG, and agentic systems. The platform helps organizations test, monitor, and improve AI applications from early experimentation through production deployment. Openlayer provides more than 100 automated tests that evaluate data quality, model performance, safety, reliability, fairness, and behavior across AI workflows. Its observability capabilities give teams traceability across prompts, retrieval steps, agents, tool calls, responses, and complex multi-step execution paths. Real-time guardrails help block or reduce risks such as prompt injections, PII leakage, bias, toxicity, hallucinations, and unsafe outputs. Openlayer also supports automated model evaluations so teams can continuously assess AI systems instead of relying only on manual review. For governance teams, the platform helps operationalize responsible AI requirements and align internal processes with frameworks such as NIST and the EU AI Act. Enterprises can use Openlayer to create safer AI development practices, maintain oversight, and document how models perform over time. By combining evaluation, observability, guardrails, governance automation, and workflow traceability, Openlayer helps companies deploy AI systems with more confidence and control.

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.

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.

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.

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.

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.

Prisma AIRS AI Runtime Security is a specialized solution aimed at safeguarding applications, agents, models, and data that utilize LLM technology during their operational phases, providing real-time oversight, assurance, and governance throughout the AI lifecycle. This system continuously observes AI behavior, implementing protective measures that identify and mitigate threats which conventional security tools often overlook, such as prompt injection, harmful code, toxic outputs, data leakage, and unauthorized or unsafe actions. It empowers organizations to uncover all AI assets in operation, including shadow AI, while gaining insights into the interactions among agents, applications, and models across various environments. By consistently evaluating risk through the testing of AI systems, managing permissions, and monitoring the security posture in real-time, it incorporates controls that prevent manipulation and exposure during runtime engagements. With its adaptive defense mechanism, it protects against both evolving threats and zero-day vulnerabilities, leveraging real-time analysis of inputs, outputs, and execution processes. Ultimately, this innovative solution enhances an organization's ability to maintain a secure AI framework while promoting trust and compliance in AI deployments.

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.

iDox.ai Guardrail serves as an immediate security measure for AI applications, designed to safeguard sensitive information from being exposed during generative AI tasks. This innovative solution functions at the endpoint, intercepting user prompts, uploaded files, and any AI interactions prior to data transmission from the device. Guardrail employs policy-driven mechanisms to identify and prevent the leakage of sensitive information, including personally identifiable information (PII), protected health information (PHI), payment card information (PCI), intellectual property, and other confidential business data. In contrast to conventional data loss prevention (DLP) systems, Guardrail is tailored specifically for AI applications. It continuously observes user engagement with AI platforms like ChatGPT, Microsoft Copilot, and Claude, applying protective measures in real-time to ensure security. Among its key features are: - Continuous monitoring of prompts and file submissions - Detection of sensitive data with AI awareness - Real-time anonymization and sanitization processes - Defense against risks associated with AI agents, such as unauthorized file access incidents (e.g., OpenClaw) - Implementation of website whitelisting and strict policy enforcement. Additionally, Guardrail enhances user confidence in utilizing AI technologies while ensuring compliance with data privacy regulations.

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.

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.

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.

The Apigene MCP Gateway serves as the essential runtime layer that links AI agents to APIs and MCP servers via the Model Context Protocol. By presenting agent tools, context, skills, and instructions as a unified remote MCP endpoint that is fully managed and regulated, it transforms MCP into a fully-fledged native solution rather than a mere experimental tool. Apigene offers a comprehensive agent foundation layer encapsulated within a single MCP Gateway, enabling agents to connect securely with APIs and MCP servers without the need for bespoke glue code or framework-specific adaptations. Teams can effortlessly construct AI agents using conversational interfaces, specifying which APIs and MCP servers the agents can access, outlining their reasoning processes, and dictating their actions—all without writing code. Additionally, it features intelligent tool selection that effectively pairs the appropriate API or MCP tool with each request, while also allowing for multi-platform deployment across numerous environments, including ChatGPT, Claude, Cursor, Gemini, VS Code, internal copilots, enterprise AI systems, and custom applications. This powerful integration streamlines the development process, making it easier for teams to leverage AI in their projects.

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.

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.

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.

Enkrypt AI is a specialized platform designed for enterprise-level security, compliance, and governance in the realm of artificial intelligence, focusing particularly on safeguarding large language models, AI agents, multimodal systems, and machine-critical processes. Catering to industries such as finance, healthcare, insurance, and government, Enkrypt AI empowers organizations to innovate quickly while ensuring safety and maintaining a competitive edge. The platform addresses the entire spectrum of AI security through several key features: Guardrails: With ultra-low latency (under 50 milliseconds), policy-driven guardrails effectively mitigate risks associated with prompt injections, unauthorized data exposure, hazardous outputs, and non-compliant behavior of agents in real-time. Red Teaming: The system implements policy-driven multimodal attack simulations for LLMs and AI agents prior to their deployment in order to identify vulnerabilities. MCP Security: The MCP Scan Hub and Secure MCP Gateway offer comprehensive protection for MCP servers, tools, and agent toolchains throughout the entire process. Compliance: Ongoing monitoring ensures adherence to standards such as NIST AI RMF, OWASP LLM Top 10, the EU AI Act, HIPAA, and FINRA, with certifications including ISO 27001 and SOC 2 Type II. Recognized as a Gartner Cool Vendor for 2025, Enkrypt AI sets itself apart in the industry.

LMOps is a stack that allows you to launch production-ready applications for monitoring, model management and more. Portkey is a replacement for OpenAI or any other provider APIs. Portkey allows you to manage engines, parameters and versions. Switch, upgrade, and test models with confidence. View aggregate metrics for your app and users to optimize usage and API costs Protect your user data from malicious attacks and accidental exposure. Receive proactive alerts if things go wrong. Test your models in real-world conditions and deploy the best performers. We have been building apps on top of LLM's APIs for over 2 1/2 years. While building a PoC only took a weekend, bringing it to production and managing it was a hassle! We built Portkey to help you successfully deploy large language models APIs into your applications. We're happy to help you, regardless of whether or not you try Portkey!

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.

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.

DueDel is a next-generation AI risk intelligence platform designed to streamline due diligence by automating research and surfacing early warning signals across financial, legal, and reputational domains. Powered by advanced NLP and sentiment analysis, the system identifies subtle risk patterns that traditional manual research often misses. Users can run comprehensive scans by entering their target entity and keywords, after which DueDel generates consolidated reports featuring red flags, stakeholder mapping, litigation traces, and tone analytics. Executive summaries turn complex findings into actionable insights, allowing leadership teams to make confident decisions more quickly. DueDel reduces manual research time by up to 80%, enabling analysts to focus on strategy rather than data gathering. It integrates easily with existing workflows, making it suitable for investment firms, compliance departments, and risk management teams. The platform is backed by founders with deep expertise in AI safety, LLM research, and financial risk governance. Award recognition and partnerships with major financial institutions highlight its credibility in transforming modern risk intelligence.

OneTrust AI Governance is a comprehensive tool designed to safeguard the return on investment in artificial intelligence by converting AI-related risks into actionable controls, thereby enabling teams to effectively govern while maintaining agility. It bridges the gap between enterprise governance and technical realities, allowing organizations to accelerate AI implementation, mitigate risks, and uphold trust as AI technologies advance in real-world applications. The platform assists teams in organizing their AI systems and evaluating risks through a central inventory that tracks models, datasets, agents, and vendors, while also designating ownership, lifecycle status, and understanding interdependencies of components. By utilizing global frameworks such as the EU AI Act, NIST, and ISO 42001, it standardizes the process of identifying AI risks and features automated workflows for risk categorization based on use cases, systems, or components, along with mapped risk and control frameworks for continuous compliance. Additionally, OneTrust enhances the efficiency of approvals, attestations, scoping, evidence collection, and reporting that is ready for audits through customizable intake and approval workflows. This ensures that organizations can maintain a robust governance structure while swiftly adapting to the fast-evolving landscape of AI technologies.

TrueFoundry is an Enterprise Platform as a service that enables companies to build, ship and govern Agentic AI applications securely, at scale and with reliability through its AI Gateway and Agentic Deployment platform. Its AI Gateway encompasses a combination of - LLM Gateway, MCP Gateway and Agent Gateway - enabling enterprises to manage, observe, and govern access to all components of a Gen AI Application from a single control plane while ensuring proper FinOps controls. Its Agentic Deployment platform enables organizations to deploy models on GPUs using best practices, run and scale AI agents, and host MCP servers - all within the same Kubernetes-native platform. It supports on-premise, multi-cloud or Hybrid installation for both the AI Gateway and deployment environments, offers data residency and ensures enterprise-grade compliance with SOC 2, HIPAA, EU AI Act and ITAR standards. Leading Fortune 1000 companies like Resmed, Siemens Healthineers, Automation Anywhere, Zscaler, Nvidia and others trust TrueFoundry to accelerate innovation and deliver AI at scale, with 10Bn + requests per month processed via its AI Gateway and more than 1000+ clusters managed by its Agentic deployment platform. TrueFoundry’s vision is to become the Central control plane for running Agentic AI at scale within enterprises and empowering it with intelligence so that the multi-agent systems become a self-sustaining ecosystem driving unparalleled speed and innovation for businesses. To learn more about TrueFoundry, visit truefoundry.com.

The AI Governance platform efficiently identifies and catalogs AI assets, streamlines compliance processes, mitigates AI-related risks, and provides ongoing assessments of model performance, ensuring the reliability, safety, and audit readiness of deployed AI systems. This advanced platform leverages AI technology to map over thirty international regulations, assess AI-specific risks, analyze model performance instantaneously, and create compliance documentation that meets audit standards, among other features. The Adeptiv AI Governance Dashboard serves as a comprehensive intelligence hub tailored for superior oversight of AI initiatives across enterprises. By aggregating all essential governance indicators into a unified, real-time dashboard, it offers insights into the total number of AI applications, compliance advancements, success and failure rates, submission rates of evidence, and trends in adoption across different business units. Additionally, the platform enhances risk management by providing in-depth perspectives on risk levels, distribution of severity, and trends in resolution, allowing teams to swiftly focus on areas that have the most significant impact on the organization’s AI strategy. Overall, this platform is crucial for organizations aiming to maintain a high standard of accountability and performance in their AI operations.

Kastra serves as the crucial authorization framework for AI systems, determining the permissions of agents, models, and tools prior to their execution. Positioned along the execution path of all interactions such as prompts, tool calls, shell commands, database operations, and API requests, it evaluates each action based on deterministic, attribute-driven policies, rendering decisions to allow, deny, redact, or escalate in less than a millisecond. In contrast to monitoring solutions that only track AI actions post-execution, Kastra proactively prevents unauthorized activities before they can impact any tool, API, database, or production environment. Its comprehensive control plane integrates a policy engine, edge decision-making capabilities, various integrations, and a tamper-proof evidence vault that securely signs each decision for auditing and replay purposes. Furthermore, with Kastra Edge, local enforcement is extended to developer environments, safeguarding coding agents such as Claude Code, Cursor, and Codex CLI from harmful commands, unauthorized data extraction, unsafe file modifications, and improper tool usage. This proactive approach to authorization not only enhances security but also ensures compliance and accountability in AI-driven processes.

AIsa serves as the comprehensive infrastructure solution tailored for engineers, enterprise architects, and Web3 developers engaged in the deployment of autonomous agents. By enabling developers to consolidate over 100 individual API accounts into a single, simplified payment wallet, we facilitate the accessibility of advanced AI-driven commerce and resource routing. Notable advantages include the ability to conduct high-frequency micropayments, cross-platform functionality, and a fully autonomous ecosystem available around the clock. The Developer Dashboard provides a cohesive and efficient interface for tracking API usage and funding agent wallets. The Multi-Modal Gateway allows for the seamless integration of standard LLM reasoning with real-time web searches and live data extraction. Through the Skills Marketplace, users can access a curated selection of pre-built, plug-and-play tools that significantly enhance agent functionalities. In addition to this, the Autonomous Foundry empowers users to deploy and scale hosted agent ecosystems without the burden of backend infrastructure management. By allowing AIsa to manage complex billing and API oversight, developers can concentrate on refining agent logic and improving performance. This holistic approach not only simplifies the deployment process but also accelerates innovation within the domain of autonomous agents.

Axway Amplify is a modular API and integration platform designed to help enterprises connect systems, govern APIs, and enable secure AI-ready digital experiences. It supports federated API management, giving organizations visibility and control across APIs that live in different clouds, on-premises systems, gateways, repositories, and vendor environments. Amplify API Management helps teams design, implement, secure, publish, and manage APIs throughout the full lifecycle. Amplify Fusion provides low-code and no-code integration tools that allow business and IT users to build event-based workflows, connect applications, and automate recurring processes. Amplify Engage creates a marketplace for curated API products and digital assets, helping developers discover, subscribe to, and reuse approved APIs. Amplify AI Gateway helps organizations scale AI responsibly by protecting prompts, orchestrating LLM usage, authenticating access to AI services, and controlling compliance requirements. The platform also includes centralized monitoring, governance, and management capabilities for APIs across AWS, Azure, Istio, Axway, and other gateway environments. Amplify is modular, so companies can begin with API management, integration, AI governance, or API marketplace capabilities and expand over time. By combining API security, discovery, governance, integration, and AI enablement, Axway Amplify helps enterprises modernize without abandoning systems that already work.

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.

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

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.

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.

WitnessAI builds the guardrails to make AI productive, safe, and usable. Our platform allows enterprises the freedom to innovate, while enjoying the power of generative artificial intelligence, without compromising on privacy or security. With full visibility of applications and usage, you can monitor and audit AI activity. Enforce a consistent and acceptable use policy for data, topics, usage, etc. Protect your chatbots, employee activity, and data from misuse and attack. WitnessAI is building an international team of experts, engineers and problem solvers. Our goal is to build an industry-leading AI platform that maximizes AI's benefits while minimizing its risks. WitnessAI is a collection of security microservices which can be deployed in your environment on-premise, in a sandbox in the cloud, or within your VPC to ensure that data and activity telemetry remain separate from other customers. WitnessAI, unlike other AI governance solutions provides regulatory separation of your information.

Plano is a delivery infrastructure solution built specifically for AI agents and agentic applications that require reliability, scalability, and operational visibility. Acting as an AI-native proxy and data plane, the platform manages the underlying infrastructure needed to route requests, orchestrate agents, enforce policies, and monitor interactions. Developers can integrate multiple AI models and model versions through a unified interface without creating custom routing systems for each provider. The platform includes built-in capabilities for observability, guardrail enforcement, context engineering, and intelligent model selection to improve application performance. Teams can use Plano alongside their preferred frameworks, tools, and programming languages while maintaining a consistent infrastructure layer. Rich tracing features provide detailed visibility into agent workflows, helping product and engineering teams identify errors and optimize outcomes. Centralized security controls simplify governance and ensure consistent policy enforcement across AI applications. Support for on-premises deployments also makes the platform suitable for organizations with strict compliance and data residency requirements. Plano helps businesses accelerate the journey from prototype to production by reducing the operational burden of managing AI infrastructure.

Orq.ai stands out as the leading platform tailored for software teams to effectively manage agentic AI systems on a large scale. It allows you to refine prompts, implement various use cases, and track performance meticulously, ensuring no blind spots and eliminating the need for vibe checks. Users can test different prompts and LLM settings prior to launching them into production. Furthermore, it provides the capability to assess agentic AI systems within offline environments. The platform enables the deployment of GenAI features to designated user groups, all while maintaining robust guardrails, prioritizing data privacy, and utilizing advanced RAG pipelines. It also offers the ability to visualize all agent-triggered events, facilitating rapid debugging. Users gain detailed oversight of costs, latency, and overall performance. Additionally, you can connect with your preferred AI models or even integrate your own. Orq.ai accelerates workflow efficiency with readily available components specifically designed for agentic AI systems. It centralizes the management of essential phases in the LLM application lifecycle within a single platform. With options for self-hosted or hybrid deployment, it ensures compliance with SOC 2 and GDPR standards, thereby providing enterprise-level security. This comprehensive approach not only streamlines operations but also empowers teams to innovate and adapt swiftly in a dynamic technological landscape.

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.

Edgee operates as an AI intermediary that integrates seamlessly with your application and various large language model providers, functioning as an intelligence layer at the edge that minimizes prompt size before they are sent to the model, ultimately decreasing token consumption, lowering expenses, and enhancing response times without requiring alterations to your current codebase. Users can access Edgee via a single API that is compatible with OpenAI, allowing it to implement various edge policies, including smart token compression, routing, privacy measures, retries, caching, and financial oversight, before passing the requests to chosen providers like OpenAI, Anthropic, Gemini, xAI, and Mistral. The advanced token compression feature efficiently eliminates unnecessary input tokens while maintaining the meaning and context, which can lead to a substantial reduction of up to 50% in input tokens, making it particularly beneficial for extensive contexts, retrieval-augmented generation (RAG) workflows, and multi-turn conversations. Furthermore, Edgee allows users to label their requests with bespoke metadata, facilitating the monitoring of usage and expenses by different criteria such as features, teams, projects, or environments, and it sends notifications when there is an unexpected increase in spending. This comprehensive solution not only streamlines interactions with AI models but also empowers users to manage costs and optimize their application’s performance effectively.

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

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