Top JetStream Security Alternatives

Gemini Enterprise Agent Platform is an advanced AI infrastructure from Google Cloud that enables organizations to build and manage intelligent agents at scale. As the evolution of Vertex AI, it consolidates model development, agent creation, and deployment into a unified platform. The system provides access to a diverse library of over 200 AI models, including cutting-edge Gemini models and leading third-party solutions. It supports both low-code and full-code development, giving teams flexibility in how they design and deploy agents. With capabilities like Agent Runtime, organizations can run high-performance agents that handle long-duration tasks and complex workflows. The Memory Bank feature allows agents to retain long-term context, improving personalization and decision-making. Security is a core focus, with tools like Agent Identity, Registry, and Gateway ensuring compliance, traceability, and controlled access. The platform also integrates seamlessly with enterprise systems, enabling agents to connect with data sources, applications, and operational tools. Real-time monitoring and observability features provide visibility into agent reasoning and execution. Simulation and evaluation tools allow teams to test and refine agents before and after deployment. Automated optimization further enhances agent performance by identifying issues and suggesting improvements. The platform supports multi-agent orchestration, enabling agents to collaborate and complete complex tasks efficiently. Overall, it transforms AI from a productivity tool into a fully autonomous operational capability for modern enterprises.

BAND develops comprehensive interaction frameworks tailored for large-scale applications of distributed AI agents. This platform enables real-time, collaborative communication between agents and humans while integrating a runtime control plane that maintains policy adherence, establishes authority boundaries, and guarantees transparency across varied systems. Moreover, BAND supports developers, engineering teams, and leaders overseeing enterprise platforms that manage multi-agent ecosystems across internal frameworks, SaaS offerings, and collaborative environments with partners. This robust support not only improves operational efficiency but also stimulates innovation within intricate organizational frameworks, ultimately driving progress and adaptability in a rapidly evolving technological landscape.

Maetra acts as a specialized governance control plane designed for teams overseeing AI agents that utilize various tools. It identifies these agents along with their corresponding repositories, evaluates risks through predefined frameworks, and checks possible actions against versioned governance policies before they are carried out. Furthermore, it streamlines the process for human approvals, scrutinizes prompts and tool interactions for vulnerabilities during runtime, guarantees that ongoing tasks stay in line with authorized goals, and preserves immutable records of decisions for auditing. The system consists of multiple modules, including Govern, Secure, Task Guard, Interaction Guard, Discover, Comply, Audit, and Decision Intelligence, which can operate autonomously or collaboratively as a unified control plane, thus improving operational effectiveness and regulatory compliance. This multifaceted approach ultimately fosters a robust framework for managing and overseeing the actions of AI agents within organizations, ensuring that they function within the established guidelines. By promoting accountability and transparency, Maetra strengthens the governance of AI technologies in a rapidly evolving landscape.

MuleSoft is an enterprise platform built to make AI agents, APIs, applications, data, and systems easier to connect, govern, secure, and orchestrate from one centralized control plane. It helps organizations move into the agentic era by giving IT teams the tools to manage AI-driven interactions without losing visibility or control. MuleSoft Agent Fabric enables companies to govern and coordinate AI agents across different platforms, supporting compliance, performance improvement, and stronger business value. MuleSoft Omni Gateway helps teams oversee every interaction between APIs, agents, models, and enterprise systems across multiple environments. The platform also includes Trusted Agent Identity, which helps agents securely act on behalf of users when interacting with downstream services. With MuleSoft Agent Scanners, organizations can discover AI agents across platforms such as Amazon Bedrock and Google Vertex AI, then register them in a governed system to reduce shadow AI. MuleSoft Agent Registry centralizes agents, tools, and digital assets, while Agent Broker supports complex process orchestration through defined rules and dynamic task routing. The platform also supports multi-agent collaboration, API governance, monitoring, partner management, intelligent document processing, and hundreds of prebuilt connectors. Development teams can build APIs, integrations, and automations using natural language, clicks, or code through tools such as MuleSoft Vibes, MuleSoft Your Way, and Anypoint Code Builder. MuleSoft also supports customer success through professional services, training, partners, documentation, tutorials, demos, and community resources. MuleSoft is built for organizations that want to accelerate AI adoption, modernize integration, improve governance, and confidently scale agentic workflows across the enterprise.

Lunar.dev functions as an all-encompassing platform for AI gateway and API consumption management, specifically crafted to empower engineering teams with a unified interface for monitoring, regulating, securing, and optimizing all interactions with outbound APIs and AI agents. This encompasses the ability to track communications with large language models, employ Model Context Protocol tools, and connect with external services across a variety of distributed applications and workflows. The platform provides immediate visibility into usage trends, latency problems, errors, and associated costs, enabling teams to oversee every interaction involving models, APIs, and agents in real-time. Moreover, it facilitates the implementation of policies such as role-based access control, rate limiting, quotas, and cost management strategies to maintain security and compliance, while preventing excessive use or unexpected charges. By centralizing the oversight of outbound API traffic through features like identity-aware routing, traffic inspection, data redaction, and governance, Lunar.dev significantly enhances operational efficiency for its users. Its MCPX gateway further simplifies the administration of numerous Model Context Protocol servers by integrating them into a single secure endpoint, thereby providing comprehensive observability and permission management for AI tools. In addition, this platform not only alleviates the challenges associated with API management but also substantially increases the capacity of teams to effectively leverage AI technologies, ultimately driving innovation and productivity within organizations.

Preloop is an open-source control plane tailored for AI agents that can execute real-world tasks, featuring a robust multi-layered security system. This includes an MCP firewall for tool access management, an AI model gateway that promotes cost efficiency, safety, and accountability, along with policy-as-code that emphasizes human oversight, all while ensuring runtime session visibility and maintaining audit trails in a self-hosted environment. As AI agents rapidly gain the ability to deploy code, alter infrastructure, manage financial transactions, access production data, and generate model costs nearly instantaneously, Preloop equips teams with the tools to oversee agent activities, track spending, and identify which actions require human approval. It supports an array of tools such as OpenClaw, Hermes, Claude Code, Codex CLI, Cursor, Gemini CLI, Windsurf, Cline, OpenCode, and any agents compliant with MCP standards. Moreover, access rules can assess not just tool names but also their arguments and context, utilizing CEL expressions to set specific conditions. Teams are also given the option to start with observability features and gradually implement approval and denial processes without needing SDKs or significant changes to current applications, facilitating a more efficient rollout. This comprehensive strategy not only ensures that organizations retain control over the functionalities of their AI agents but also allows them to adapt to evolving needs and challenges in the AI landscape. Such flexibility is crucial in a rapidly changing technological environment where the implications of AI actions can be profound.

Barndoor acts as a comprehensive management layer for data and access, guaranteeing that artificial intelligence systems operate securely alongside enterprise data and infrastructure. It functions as a centralized control hub, managing AI agents and applications, and enabling organizations to establish policies, enforce access controls automatically, and maintain thorough oversight of AI tool operations within their business structures. In contrast to conventional identity-based permissions, Barndoor utilizes context-aware governance, which empowers administrators to control the actions of an AI agent based on specific factors, such as the user supervising the agent, the system being accessed, the type of data involved, and the specific task at hand. This innovative system evaluates each AI request in real time, implementing policies prior to any actions being executed, thus preventing unsafe or unauthorized activities from impacting internal systems or compromising sensitive information. Moreover, this sophisticated approach to governance not only bolsters security and compliance but also cultivates a more reliable AI ecosystem, ultimately benefiting organizations as they navigate the complexities of modern technology. By prioritizing both safety and functionality, Barndoor positions itself as an essential tool for organizations that depend on AI-driven solutions.

Token Security introduces a groundbreaking strategy designed specifically for the rapidly growing domain of Non-Human Identities (NHI), advocating for a machine-centric method to identity protection. In this digital age, identities are everywhere and frequently remain unmonitored; they emerge from machines, applications, services, and workloads that are created by diverse sources throughout each day. The complex and sluggish process of overseeing these identities has expanded the attack surface, making it challenging for organizations to manage effectively. Instead of focusing exclusively on human identities, Token emphasizes the significance of the resources being accessed, promptly illuminating who interacts with which resources, pinpointing vulnerabilities, and ensuring robust security without hampering operations. Additionally, Token proficiently maps all identities within cloud ecosystems, seamlessly incorporating complex elements such as Kubernetes, databases, servers, and containers, which leads to a unified view of critical identity data. This all-encompassing methodology not only bolsters security but also streamlines identity management amidst increasingly intricate infrastructures, ultimately fostering a more resilient digital environment. As organizations increasingly rely on automation and interconnected systems, the need for such innovative identity solutions becomes even more crucial, showcasing Token's relevance in today's technological landscape.

Defakto Security presents a powerful platform that authenticates all automated interactions by issuing temporary, verifiable identities to non-human entities such as services, pipelines, AI agents, and machines, effectively eliminating the reliance on static credentials, API keys, and persistent privileges. Their extensive non-human identity and access management solution supports the detection of unmanaged identities across various environments, including cloud, on-premises, and hybrid configurations, allowing for the real-time issuance of dynamic identities in accordance with policy requirements, the enforcement of least-privilege access principles, and the creation of comprehensive audit-ready logs. The solution consists of multiple modules: Ledger, which guarantees continuous discovery and governance of non-human identities; Mint, which streamlines the generation of targeted, temporary identities; Ship, which supports secretless CI/CD workflows by removing hard-coded credentials; Trim, which refines access rights and removes excessive privileges for service accounts; and Mind, which protects AI agents and large language models using the same identity framework utilized for workloads. Each module is essential in bolstering security and optimizing identity management across a variety of operational landscapes. Together, these components not only enhance security but also promote efficiency in managing identities for non-human entities.

Peta acts as a sophisticated control plane for the Model Context Protocol (MCP), facilitating, securing, regulating, and supervising the interactions between AI clients and agents with external resources, data, and APIs. The platform incorporates a zero-trust MCP gateway, a secure vault, a managed runtime environment, a policy engine, human-in-the-loop approvals, and extensive audit logging into a unified solution, allowing organizations to enforce detailed access controls, protect sensitive credentials, and track all interactions performed by AI systems. Central to Peta is Peta Core, which serves as both a secure vault and gateway, responsible for encrypting credentials, generating ephemeral service tokens, ensuring identity verification and policy compliance for each request, managing the lifecycle of the MCP server through lazy loading and auto-recovery, and injecting credentials at runtime without exposing them to agents. Furthermore, the Peta Console enables teams to determine which users or agents can access specific MCP tools within defined environments, set up approval processes, manage tokens, and analyze usage data along with associated costs. This comprehensive strategy not only bolsters security but also promotes effective resource management and accountability across AI operations, ultimately leading to improved operational efficiency and enhanced oversight. By integrating these functionalities, Peta establishes a robust foundation for organizations seeking to optimize their AI-driven initiatives.

Notenic operates as a governance and orchestration platform designed to oversee and safeguard autonomous AI agents, often referred to as "digital labor," especially in high-stakes environments where failures could result in severe regulatory, legal, or operational consequences. As an integral infrastructure layer, it seamlessly integrates into the execution pathways of AI systems to implement stringent governance measures before any interaction occurs with systems of record, thereby circumventing the challenges posed by post-output filters or controls that are applied during prompting. The platform is built on a zero-trust runtime architecture, which is defined by core principles like zero-persistence that guarantees no data retention after each session and execution-path control that enforces policies at the moment actions are performed. This architecture prioritizes independence from the model's context, effectively shielding against adversarial inputs that could undermine governed behavior. Additionally, Notenic provides a holistic control plane for the administration of AI agents, treating them as operational entities with specific roles and necessary oversight, which boosts organizational efficiency and accountability. Ultimately, this comprehensive framework ensures that all AI operations are executed in a secure, compliant, and well-regulated manner, reinforcing trust in automated processes. In a landscape where AI technology continues to evolve rapidly, Notenic stands out as a vital solution for maintaining the integrity and reliability of digital labor.

WrangleAI stands out as a powerful platform tailored for enterprises, delivering crucial oversight, management, and governance of their AI implementations and associated costs. Acting as a "control plane" for generative AI technologies like GPT-4, Claude, and Gemini, it provides businesses with the ability to monitor usage in real-time, analyze expenses, oversee infrastructure, and set spending thresholds to avoid overspending. Furthermore, WrangleAI improves AI observability, allowing teams to identify which models are being used, by whom, and for what purposes, while facilitating intelligent workload distribution to more cost-effective models without sacrificing quality. The platform also features governance tools, such as role-based access control and compliance support with standards like SOC 2 and ISO 27001, promoting collaboration between finance, engineering, and leadership teams to implement policies and gain actionable insights for refining AI investments. This holistic approach not only enhances the management of AI initiatives but also equips organizations with the knowledge needed to make strategic decisions regarding their AI endeavors, ensuring that they effectively leverage their resources for long-term success. Ultimately, WrangleAI positions itself as an essential ally for enterprises looking to optimize their AI landscapes and drive innovation responsibly.

Singulr serves as a holistic platform tailored for enterprise AI governance and security, offering a unified control structure that supports organizations in discovering, securing, and optimizing their extensive AI deployments. By addressing the growing disparity between the swift adoption of AI technologies and the limitations of governance, it provides unmatched insight into all AI systems employed within the organization, encompassing bespoke applications, integrated AI solutions, publicly available tools, and shadow AI, which frequently bypass security detection. The platform meticulously identifies and inventories AI resources across the enterprise, establishing a dynamic record of agents, models, and services, while assessing their respective risks through comprehensive evaluations of data management, model lineage, vulnerabilities, and compliance standards. Furthermore, Singulr Pulse, the platform’s intelligence layer, analyzes millions of AI systems, assigns risk classifications, and streamlines automated onboarding processes, dramatically reducing approval timelines from weeks to just hours, all while maintaining stringent security protocols. This forward-thinking methodology not only improves the efficiency of AI adoption but also enables organizations to uphold a robust governance structure as they navigate the intricate landscape of AI integration. In doing so, it positions organizations to better respond to the challenges and opportunities presented by the evolving AI landscape.

Onyx operates as a comprehensive AI management platform focused on discovering, safeguarding, governing, optimizing, and assessing AI agents and models utilized within a company. It offers vital insights for security, governance, and AI teams regarding both sanctioned and unsanctioned AI operations across diverse environments such as SaaS applications, cloud services, endpoints, and coding practices, covering elements like prompts, responses, and agent conduct. The inclusion of the AI Security feature strengthens the organization’s defense by identifying vulnerabilities and enforcing proactive protections against possible threats and misuse. In parallel, AI Governance guarantees adherence to security protocols and regulatory requirements by providing opt-in coverage and enabling policy regulations to be expressed in natural language. Additionally, AI Orchestration simplifies the deployment of agents and Multi-Cloud Platforms (MCPs), focusing on enhancing cost-effectiveness, precision, and speed. The AI ROI feature aids in quantifying usage, setting targets, and monitoring outcomes across various organizational sectors. Moreover, the Onyx Guardian Agent acts as a supervising AI, consistently detecting risks and addressing challenges throughout the platform, which allows organizations to manage a vast array of agents efficiently. Ultimately, Onyx equips businesses to leverage AI’s full capabilities while ensuring control and diligent oversight, fostering a secure and compliant AI ecosystem. This not only enhances operational efficiency but also encourages innovation within the organization.

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.

Bevel functions as a vendor-agnostic control plane integrated with Git, specifically designed for enterprise AI agents, enabling organizations to establish their agents, context, skills, tools, permissions, and identities as proprietary files within their systems, accessible by any agent runtime through the Managed Control Plane (MCP). The context is structured as categorized knowledge nodes, complete with documented provenance that outlines the source, last modification, and verification timestamps, all of which is synthesized into a navigable graph that can be continuously updated for dashboard creation. Skills are defined in clear Markdown formats, allowing process owners to effortlessly read and review modifications, as well as transfer them between various runtimes. Tool manifests detail the available functionalities, while sensitive data is securely encrypted in a vault, managed by access protocols that specify which agents have permission to read particular files or execute certain endpoints. Each agent is allocated a distinctive identity and set of credentials, ensuring traceability of all actions to their origin. This extensive framework not only fortifies security and structure but also fosters transparency and accountability within AI operations, creating a more robust ecosystem for enterprise-level management of AI agents. Furthermore, the system promotes collaborative development, allowing teams to innovate while maintaining control over their AI resources.

AICtrlNet goes beyond simple monitoring of AI governance by actively engaging in its implementation. Unlike other platforms that merely evaluate or supervise AI risks, AICtrlNet takes the lead in orchestrating AI agents, involving human participants as essential contributors rather than just approval checkpoints, and integrating enterprise systems into a unified governance framework. The platform is versatile, accommodating various models such as OpenAI, Claude, Gemini, and local runtimes like Ollama and vLLM. It employs a 6-phase Control Spectrum that delineates autonomy levels for diverse workflows and agents. Additionally, it boasts a library of 43 agent templates designed for specific roles alongside over 177 workflow templates that cover 41 different industry sectors. Rather than replacing existing automation solutions, it collaborates with tools like n8n, Zapier, and Make as integral nodes within its system. AICtrlNet emphasizes compliance by supporting regulatory standards such as HIPAA, GDPR, SOC2, and the EU AI Act, thanks to its built-in governance and accountability features. The software is offered in open-core editions: the Community edition, which is MIT-licensed, free, and self-hostable; the Business edition, which enhances governance and risk evaluation through machine learning capabilities; and the Enterprise edition, which adds multi-tenancy and federation functionalities. Users can easily engage with the platform via the HitLai visual no-code interface, REST API, or MCP, providing flexibility and user-friendliness. With its comprehensive features, AICtrlNet is set to transform the AI governance landscape by fostering a proactive approach while ensuring that all elements work in harmony to achieve compliance and effectiveness.

Permiso is an enterprise identity security platform built to protect every identity operating across cloud, SaaS, on-premises, hybrid, and AI-driven environments. The platform combines identity discovery, runtime identity attribution, identity security posture management, identity threat detection and response, and AI identity security into a unified security architecture. Its Universal Identity Graph creates continuous relationships between users, service accounts, non-human identities, AI agents, credentials, workloads, machines, permissions, infrastructure resources, and runtime actions to provide complete identity lineage. Unlike traditional identity providers that primarily monitor authentication, Permiso extends visibility into runtime activity, allowing security teams to observe tool calls, MCP invocations, serverless functions, workload creation, sub-agent execution, API interactions, and privilege inheritance throughout an identity's lifecycle. The platform inventories identities across cloud providers, SaaS applications, CI/CD pipelines, and enterprise infrastructure while identifying overprivileged accounts, stale credentials, toxic permission combinations, and identities most likely to be compromised. Permiso continuously monitors runtime behavior to detect anomalous activity, lateral movement, credential theft, insider threats, account takeover, and attacks targeting AI agents or machine identities. Security teams can investigate incidents using correlated runtime and control plane activity while leveraging more than 1,500 threat detection signals developed by Permiso's P0 Labs research team. The platform includes dedicated capabilities for identity visibility, identity intelligence, identity posture management, identity threat detection and response, non-human identity security, and AI agent runtime security.

OpenBox is a powerful AI governance solution designed specifically for enterprises, with the goal of maintaining the transparency, auditability, and secure deployment of AI systems at scale through the real-time monitoring of all agent actions and interactions within the platform. By offering a unified governance framework, it consolidates identity management, policy enforcement, risk management, and compliance into a single operational environment, effectively addressing the prevalent challenge of fragmentation that often arises from relying on multiple disparate tools, and enabling organizations to uphold consistent oversight over their AI operations. With its seamless integration into existing AI workflows through an easy-to-use SDK, it requires no alterations to current infrastructures while providing instant visibility into the operational behaviors, decision-making mechanisms, and communications among AI agents. Additionally, OpenBox takes a proactive approach by supervising and evaluating each action before it is executed, ensuring that policy enforcement and compliance assessments happen in real-time to prevent any risky or non-compliant actions, thus prioritizing a preventative strategy over responding to issues after they occur. This forward-thinking approach not only bolsters compliance but also cultivates a culture of responsibility and accountability within AI operations, ultimately promoting a safer and more trustworthy AI ecosystem. As organizations increasingly rely on AI technology, tools like OpenBox become essential for navigating the complexities of governance in an evolving digital landscape.

Klique is an enterprise AI infrastructure control plane that connects applications, agents, developers, models, cloud APIs, and compute resources through a unified governance layer. The platform is designed to sit between AI consumers and the infrastructure that serves them, allowing organizations to control both model requests and underlying workloads from one system. Its Smart Routing capabilities select models based on factors such as cost, latency, organizational policy, and data sensitivity while providing fallback across providers when necessary. Workload routing can also direct training, data processing, and inference jobs to appropriate clusters according to capacity, locality, and price. Klique’s AI Service Management layer converts internal models, open-source endpoints, and third-party APIs into centrally managed services with budgets, quotas, virtual keys, single sign-on, and audit logging. Organizations can apply the same policies to employees, AI agents, teams, projects, and tools instead of configuring controls separately across each provider. GPU Orchestration pools accelerators and CPUs across on-premises and cloud environments and supports fractional GPU sharing, scheduling priorities, compute quotas, and multi-GPU workloads. The platform can run on existing Kubernetes environments and GPU clusters while also connecting to cloud infrastructure and hosted AI model APIs. Klique supports fully on-premises and air-gapped deployments for sensitive workloads as well as hybrid configurations that can route work according to data locality and operational requirements. It also provides usage and cost visibility across models, users, projects, agents, token consumption, and compute resources so organizations can attribute AI spending more precisely.

Dapple provides an Enterprise OS Cloud tailored for organizations in regulated industries and those leveraging AI, offering a solid AI infrastructure that adheres to stringent requirements for isolation, data residency, governance, and performance. This cutting-edge solution occupies the niche between public cloud offerings and private data centers, combining dedicated, single-tenant GPU infrastructure with an integrated control plane that manages orchestration, compliance, connectivity, observability, and operational tasks. Featuring advanced functionalities such as topology-aware placement, multi-GPU scheduling, fault-domain isolation, and reserved clusters, Dapple guarantees reliable performance without interference from other users. Moreover, private connectivity effectively merges current cloud environments with dedicated computing resources, while crucial aspects like identity management, container orchestration, threat protection, and governance policies remain robust throughout the deployment lifecycle. On an architectural level, compliance is stringently upheld before any workload is executed, ensuring adherence to in-country data residency mandates, audit responsibilities, and various regulatory standards, thus cultivating a secure environment for sensitive operations. Furthermore, Dapple not only empowers enterprises to innovate without constraints but also reinforces their commitment to upholding stringent compliance measures, all while protecting vital data assets. This balance of innovation and security positions Dapple as a leader in the AI infrastructure landscape.

Ensure compliance with corporate guidelines when implementing AI through our intuitive AI governance control plane. By streamlining the experience, you can improve oversight and securely promote the adoption of AI with SurePath AI. This platform integrates effortlessly with your existing security frameworks, proprietary models, and enterprise data sources. It features essential components such as SSO, SCIM, and SIEM. You can monitor AI usage at the network level while controlling access and examining requests to safeguard against potential data breaches. Moreover, it offers the capability to redact sensitive details from requests aimed at public models. The real-time modification of requests enhances operational efficiency while reducing risks. Additionally, you can redirect traffic to your private AI models, leveraging SurePath AI's access controls to craft a custom-branded AI portal for your enterprise. With controls driven by policies, user requests are enhanced with only the data they have permission to access, yielding responses that are particularly relevant to your organizational demands. User prompts are also automatically refined to guarantee that outputs are in line with your strategic goals and ensure adherence to compliance standards. This comprehensive approach not only fortifies security but also fosters a culture of responsible AI use across the organization.

Kosmoy brings AI inventory, monitoring, gateway policies and agent runtime controls into one enterprise platform. Teams register models, applications, agents and MCP servers, assign owners and assess risks. They can monitor usage, costs and behaviour, then apply access controls, guardrails, routing and logging through the AI Gateway. Action Capsule adds runtime isolation and a kill switch for autonomous agents. The platform is deployed in the customer Kubernetes environment, on premises or in the cloud. It is designed for AI platform, security, risk and compliance teams that need to connect governance decisions to the AI systems they operate. Enterprise licensing is quoted for the deployment scope and capabilities required.

NewCore is an innovative identity provider that caters to both individuals and AI agents through a centralized identity core, which guarantees that every identity remains visible, secure, and continuously monitored from access initiation to auditing completion. It identifies a variety of primary identities, including employees, contractors, partners, machines, delegated agents, and autonomous workloads, all within a cohesive framework. The Identity Security feature reinforces trust in access management with capabilities like single sign-on, passkeys, phishing-resistant multi-factor authentication, secure token signing, strength assessments for authenticators, and security-aware policies. By implementing a Secure Split Key mechanism, it separates signing authority between NewCore’s cloud services and the client's environment, ensuring that neither party can independently validate a token. Additionally, the Identity Discovery feature generates a detailed real-time graph that includes humans, agents, accounts, applications, authenticators, sessions, and access routes, effectively highlighting shadow accounts, orphaned credentials, and unmanaged agents that may introduce security vulnerabilities. This comprehensive approach not only boosts security measures but also simplifies the tracking and management of a wide array of identities within an organization, ultimately fostering a safer digital environment. By integrating advanced technology with robust security protocols, NewCore positions itself as a leader in identity management solutions.

Agent Control is an innovative open-source framework that revolutionizes the management of AI agent behavior on a grand scale, establishing a new standard for governance in the field. It tackles the challenges posed by fragmented and hardcoded checks by equipping teams with a cohesive governance layer that applies regulations at every stage, all managed from a single control interface that can be dynamically updated without needing modifications to the agent's core code. Developers can easily identify any function for governance by using the control() decorator, turning critical decision points within an agent into separately regulated control points, each with tailored governance policies. When a function marked with this decorator is executed, Agent Control evaluates the input or output based on the relevant policy, generating responses that can include denying, steering, warning, logging, or allowing the action. Should a denial occur, the SDK raises a ControlViolationError, effectively blocking any potentially harmful actions from being carried out. This clear demarcation of policies from the actual code empowers developers to strategically position control hooks, while governance teams can focus on the specifics of enforcement, promoting a collaborative governance model. The adaptability and strength of Agent Control render it an essential resource for organizations aiming for effective standardization in AI agent governance, and its user-friendly interface further enhances accessibility for developers across various levels of expertise.

Trase is a highly regulated AI platform tailored for industries such as healthcare, government, and enterprise, where elements like trust, security, sovereignty, and predictability are critical. It provides a strong framework for integrating AI agents into real-world workflows, featuring a wide array of specialized agents that can be immediately deployed, as well as systems designed for thorough oversight of every workflow, decision-making process, and escalation. The core of these agents operates on Trase Origin, an operating system meticulously crafted to oversee, secure, and govern agents across various environments—be it cloud, on-premises, VPC, or edge—while ensuring that data stays in its original location. Within a consolidated control plane, both Trase and third-party agents gain advantages from shared policy enforcement, extensive monitoring capabilities, cost oversight, clear escalation processes, and a complete, unchangeable audit trail. Furthermore, it facilitates deployments that meet HIPAA and SOC2 compliance standards, while safeguarding data residency, privacy, model flexibility, and the prevention of vendor lock-in. This comprehensive strategy empowers organizations to harness the potential of AI effectively while remaining compliant with rigorous regulatory mandates, ultimately enhancing operational efficiency and innovation.

Forest is an operational infrastructure platform built for regulated companies that need a secure way to run humans, AI agents, BPOs, LLMs, suppliers, and workflows together. The platform acts as an operational backend between a company’s data, compliance suppliers, human teams, AI agents, and tools connected through MCP. Forest keeps data inside the customer’s infrastructure while giving teams and agents a shared control plane for business logic, smart actions, workflows, permissions, RBAC, and audit trails. It is designed for regulated environments where agentic operations must remain compliant, auditable, and under control. Forest supports onboarding workflows on top of KYC and KYB providers such as Sumsub, Onfido, Veriff, Persona, and Trulioo. These workflows can combine identity verification, business registry checks, beneficial-owner discovery, document reviews, screening checks, risk scores, jurisdiction logic, and segment-based routing. Routine cases can be triaged by agents, while edge cases can be routed to human reviewers. Every provider call, AI agent step, workflow event, and reviewer decision is recorded at the record level so audit evidence is created as work happens. Forest also helps teams control agents from different sources, including vertical vendors, internal engineering teams, automation tools, and big-tech runtimes. Its implementation approach maps existing databases, providers, and undocumented processes before configuring workflows, then moves selected processes into production with compliance checks and performance audits. By combining operational workflows, MCP access, agent governance, live data connections, permissions, RBAC, audit trails, KYC and KYB orchestration, implementation support, and regulated-process controls, Forest helps companies modernize operations without losing oversight.

OpenWeave functions as a governance framework for AI agents and autonomous systems, operating as a server-enforced state machine that dictates the actions and their timing for these agents. Users can design workflows that include various states, transitions, and authorized triggers; the backend rigorously enforces transitions using a strict 403 error, and crucial states necessitate human approval, thus ensuring that bots cannot proceed without human intervention. Additionally, the monitoring capability offers visibility into agent activities, preventing inappropriate actions from taking place before they can occur. Rather than having transitions hardcoded, agents acquire knowledge about acceptable transitions through the API, guaranteeing that each bot maintains a verifiable identity, with all changes recorded in an immutable audit trail. The system provides integration options via a REST API and a remote MCP server, making it an essential tool for AI-agent developers, AgentOps/MLOps, and platform teams. This robust framework not only fortifies security measures but also simplifies the oversight of AI workflows, ultimately leading to more reliable and efficient autonomous systems. Furthermore, by facilitating seamless collaboration among various stakeholders, OpenWeave enhances the overall development process within the AI landscape.

asqav stands out as an innovative platform dedicated to the governance and security of artificial intelligence, ensuring that AI agents are consistently prepared for audits through real-time monitoring, enforcement, and a dependable log of every action taken. It boasts an efficient SDK that allows developers to seamlessly integrate governance capabilities into their AI agents with minimal code, enabling thorough oversight throughout the entire AI activity lifecycle. The platform also employs behavioral analysis to detect potential issues such as drift, exceeded rate limits, and scope violations, along with advanced threat detection systems that identify risks like prompt injections, leaks of sensitive data, and harmful outputs. Policy enforcement is facilitated by customizable “policy gates,” which establish specific rules for each agent, perform preflight evaluations, and offer dynamic approvals prior to any actions, ensuring that agents operate within defined boundaries. Moreover, asqav strengthens security with automated incident response functionalities that permit the suspension, isolation, or escalation of agents assessed as high-risk, thereby creating a comprehensive framework for maintaining accountability and safety in AI applications. Through these features, asqav not only protects AI operations but also fosters confidence in their use across a multitude of industries, thereby enhancing the overall efficacy and reliability of AI technologies. Ultimately, asqav serves as a crucial ally in the responsible deployment of AI, championing best practices in governance and security.

Jet-Stream Cloud is a premier streaming service in Europe, boasting over three decades of expertise, designed specifically for broadcasters, publishers, government entities, and businesses. This platform enables users to effectively host, process, and oversee their video, podcast, and music content, in addition to live radio, television, and webcasts. Committed to compliance with GDPR regulations, Jet-Stream Cloud prioritizes sustainability by being eco-friendly and carbon-neutral while providing outstanding streaming quality. Moreover, it presents the potential for substantial savings of up to 40% and features global capabilities with eight Content Delivery Networks (CDNs) to enhance user experience. With its innovative solutions, Jet-Stream Cloud positions itself as a leader in the streaming industry.