Top Barndoor.ai Alternatives

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.

JetStream Security operates as a governance platform that prioritizes security, enabling businesses to attain thorough visibility, control, and accountability over their AI systems by transforming them from vague, fragmented applications into well-managed and traceable infrastructures. Acting as a centralized control hub, it merges identity management, operational governance, monitoring, and financial oversight into a single, integrated system, which allows enterprises to “track every AI action, link actions to responsible individuals, and ensure that processes remain within authorized boundaries” while enforcing policies in real-time. Additionally, it features agentic identity, which connects human, agentic, and non-human identities to particular actions and access permissions, guaranteeing that every invocation, tool utilization, or workflow can be monitored and regulated in accordance with least-privilege access principles. By ensuring continuous runtime governance, JetStream consistently assesses real AI behavior against established frameworks and employs immutable logging along with real-time monitoring to detect inconsistencies, thereby strengthening security and compliance measures. This comprehensive strategy not only improves accountability but also aids organizations in effectively managing the intricacies associated with AI governance, ultimately fostering a more secure and compliant operational environment. As a result, businesses can confidently optimize their AI usage while adhering to the necessary regulations and best practices.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Microsoft Agent 365 provides a comprehensive management layer for organizations adopting AI agents, giving IT teams the ability to oversee and secure agents with the same tools used for traditional user management. Acting as a centralized registry, it identifies every agent—whether authenticated with Entra agent ID, manually registered, or detected as a shadow agent operating within the system. By leveraging Microsoft Defender, the platform brings enterprise-grade threat protection and security posture management to agentic workflows. Identity access for agents is governed through Microsoft Entra, ensuring every automated system interacts with corporate resources securely and responsibly. Purview adds another layer of governance, enabling teams to track, classify, protect, and audit the data that agents access or generate. Through integrations with Microsoft 365 and Power Platform, agents gain the ability to work inside Word, Excel, Power Apps, Power BI, and automated workflows. Work IQ connects agents to each organization’s unique knowledge graph, unlocking rich contextual reasoning for better task execution. IT administrators can join Microsoft’s Frontier early access program to try Agent 365 and enable it for selected users or the entire tenant. Microsoft’s broader ecosystem also supports deploying agents through Copilot, building them in Copilot Studio, and designing advanced systems in Foundry. Agent 365 is designed to help enterprises scale agent adoption confidently, securely, and efficiently as AI becomes a core part of daily operations.

Klique is a vendor-agnostic enterprise AI control plane that enables organizations to manage AI infrastructure, model access, computing resources, and agentic applications through a centralized platform. The software combines three core capabilities covering intelligent AI request routing, service governance, and GPU workload orchestration. Its smart routing engine directs requests to internally hosted models, open-source models, or external AI providers based on cost, latency, availability, data sensitivity, and organizational policies. Automatic fallback mechanisms allow applications to switch between compatible model providers when preferred services become unavailable or fail to meet defined requirements. The governance engine provides centralized controls for token budgets, spending limits, usage quotas, virtual API keys, single sign-on, and role-based access permissions. Administrators can monitor AI consumption across users, departments, projects, models, and agents while maintaining audit trails and detailed infrastructure cost attribution. GPU orchestration capabilities support resource pooling, fractional GPU sharing, workload prioritization, cloud autoscaling, and allocation of computing resources across multiple clusters. The platform integrates with Kubernetes, Slurm, PBS, AWS, Google Cloud, Azure, and existing GPU infrastructure to support both AI inference and machine learning training workloads. AI development capabilities include experiment tracking, dataset management, model registries, automated pipelines, remote development environments, and deployment of managed inference endpoints. Klique also supports governed agentic development environments for tools such as Claude Code and Codex, alongside Model Context Protocol integrations and self-service application catalogs.

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.

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.

Willow is an all-encompassing enterprise platform crafted for the management of AI agents, tools, MCP servers, skills, and plugins. It enables seamless integration of a multitude of agents, including Claude, ChatGPT, Cursor, Codex, Gemini, n8n, and tailored agents into both internal systems and SaaS solutions like Jira, GitHub, Slack, and various databases through an MCP gateway. Each agent is equipped with a unique human-linked identity, designated permissions, and a detailed audit trail to ensure accountability. Security teams are responsible for developing policies, while employees can independently access approved connectors, skills, and plugins as required. Among its many features are shadow AI discovery, redaction of PII, prompt-injection inspection, permissions at both app and action levels, alongside integrations for SSO, SCIM, and RBAC with platforms such as Okta, Entra ID, and JumpCloud. Furthermore, Willow provides functionalities for SIEM export, tracking of tokens and costs, and operates background agents to boost overall performance. The platform is offered in various deployment options, including SaaS, dedicated cloud, or on-premises deployment within a customer’s VPC. With a SOC 2 Type II attestation and adherence to GDPR regulations, Willow has achieved significant adoption and is currently in active use by leading companies like Wix, Innovid, and Riskified, ensuring it aligns with stringent industry benchmarks. This combination of versatility and a strong focus on security positions Willow as an excellent option for organizations aiming to responsibly leverage AI technologies. Ultimately, its comprehensive features and commitment to compliance empower businesses to navigate the complexities of AI integration with confidence.

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.

Kastra acts as a vital authorization framework for AI systems, establishing the permissions of agents, models, and tools before they are executed. Situated along the execution path of numerous interactions, including prompts, tool calls, shell commands, database transactions, and API requests, it assesses each action through deterministic, attribute-based policies, making decisions to allow, deny, redact, or escalate in less than a millisecond. Unlike monitoring solutions that merely observe AI activities after they occur, Kastra takes a preemptive stance, blocking unauthorized actions before they can affect any tools, APIs, databases, or production systems. Its extensive control plane encompasses a policy engine, edge decision-making features, multiple integrations, and a tamper-proof evidence vault that securely records each decision for future auditing and replay. Additionally, with the introduction of Kastra Edge, local enforcement capabilities are broadened to developer environments, protecting coding agents like Claude Code, Cursor, and Codex CLI from malicious commands, unauthorized data access, unsafe file changes, and incorrect tool usage. This forward-thinking approach to authorization not only bolsters security but also guarantees compliance and accountability in AI-driven operations, fostering a more trustworthy environment for users. By ensuring that all actions are rigorously vetted, Kastra significantly mitigates potential risks associated with AI technologies.

FirstHelm acts as a unified control center for overseeing AI agents, functioning as a bridge between your array of agents—such as n8n, OpenAI, Anthropic, CrewAI, LangChain, Microsoft Copilot Studio, or any bespoke agent accessible via REST API—and the larger operational environment. It not only manages the permissions for each agent but also promotes accountability by meticulously logging all actions and validating them against predefined guidelines, including budget constraints, forbidden activities, and transparency regarding costs and tokens allocated per task. Actions considered expensive, risky, or irreversible necessitate human approval prior to execution, with any unattended authorizations designed to expire to prevent delays in decision-making. Furthermore, FirstHelm includes interactive dashboards that enable users to steer agents in real time throughout missions while generating detailed audit trails and compliance records in accordance with regulations such as the EU AI Act, ISO 42001, SOC 2, UK GDPR, NIST AI RMF, and FCA guidelines—covering a total of 38 controls that are assessed continuously based on your individual data. This cutting-edge solution is offered under a freemium pricing structure, is versatile enough to integrate with various frameworks, and hails from the UK, highlighting its focus on adherence to regulations and empowering users. In addition to its intuitive interface and powerful capabilities, FirstHelm is designed to significantly improve the oversight and management of AI-enhanced operations, ultimately streamlining the user experience and enhancing operational efficiency.

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.

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.

LangProtect is an innovative security and governance solution crafted specifically for AI, providing strong defenses against challenges such as prompt injections, jailbreaks, data breaches, and the creation of unsafe or non-compliant outputs in LLM and Generative AI systems. Designed for advanced GenAI production environments, the platform applies real-time controls at the execution level, carefully analyzing prompts, model responses, and function calls as they happen, which allows teams to block high-risk actions before they can impact users or jeopardize sensitive data. In doing so, LangProtect promptly neutralizes potential threats, thereby safeguarding the integrity of both data and user interactions. Moreover, LangProtect's API-first architecture allows for effortless integration with existing LLM systems while ensuring low latency, and it supports a variety of deployment models, including cloud, hybrid, and on-premise configurations to satisfy the security and data residency needs of organizations. The platform is also adept at protecting modern architectures like RAG pipelines and agentic workflows, offering policy-driven enforcement, ongoing monitoring, and governance that are prepared for audits. This all-encompassing strategy empowers organizations to harness AI technologies confidently while significantly reducing the risks tied to their implementation. Ultimately, LangProtect stands out as a vital resource for businesses aiming to navigate the complexities of AI security effectively.

Obot serves as an open-source AI infrastructure platform and Model Context Protocol (MCP) gateway, allowing organizations to have a centralized system for discovering, onboarding, managing, securing, and scaling MCP servers that connect large language models and AI agents with various enterprise systems, tools, and data sources. Its features include an MCP gateway, a catalog, an administrative console, and a chat interface that integrates seamlessly with identity providers like Okta, Google, and GitHub, facilitating the implementation of access control, authentication, and governance policies across MCP endpoints to ensure secure and compliant AI interactions. Furthermore, Obot enables IT teams to host both local and remote MCP servers, manage access through a secure gateway, set detailed user permissions, effectively log and audit usage, and generate connection URLs for LLM clients such as Claude Desktop, Cursor, VS Code, or custom agents, thereby enhancing both operational flexibility and security. Additionally, this platform simplifies the integration of AI services, empowering organizations to utilize cutting-edge technologies while upholding strong governance and compliance standards. By streamlining these processes, Obot fosters an environment where innovation can thrive without compromising security or regulatory requirements.

Dymium is a real-time enforcement architecture—known as the Ghost Layer—that governs how AI agents, applications, and analysts interact with sensitive data. Instead of relying on static roles, pre-approved datasets, or post-access checks, Dymium evaluates every request dynamically based on identity, role, context, and policy. This just-in-time control model prevents over-permissioning and ensures that sensitive fields are masked or withheld during AI inference. GhostDB, GhostAPI, and GhostMCP act directly at the data source, removing the need for ETL pipelines, shadow datasets, or duplicated environments. Because governance happens before any data is returned, teams gain fast, safe access without latency or compliance risk. Dymium provides detailed logging for every interaction, keeping organizations audit-ready for GDPR, HIPAA, and the AI Act without manual effort. Data and AI teams can move faster with fewer blockers, while security and privacy teams maintain granular control. Product teams can embed governed access into AI-powered features from day one. Dymium delivers row-, field-, and role-level access controls without requiring a replatform or redesign of existing systems. Built for modern AI workloads, Dymium is the last—and most important—layer before any data request.

The Aditya Protocol acts as a regulatory framework for operations that have undergone careful examination, specifically tailored for teams working with AI agents, scripts, CI/CD workflows, internal applications, and automation processes that are nearing production stages. This cutting-edge system allows technical teams to systematically request, review, approve, implement, and document essential operational tasks while ensuring human oversight, featuring components such as validated command sequences, rationale prompts, approval tracking, execution histories, artifacts, guidance on access tokens, node tokens, configuration controls, and workflows designed to provide documentation. At present, the Aditya Protocol is accessible through a limited supervised pilot initiative that includes a select group of trusted technical reviewers and service-provider partners; it is important to note that this protocol is not meant for extensive public deployment, certification, legal advice, or to replace human judgment in operational tasks. Consequently, the emphasis of the protocol lies in maintaining human supervision throughout all operational activities it governs, ensuring accountability and reliability in execution. The focus on human involvement underscores the protocol's commitment to enhancing safety and integrity in critical processes.

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.

Openlayer is an AI governance and observability platform that helps enterprises evaluate, monitor, and control both traditional ML and generative AI systems. The platform is designed for modern AI environments that include LLM applications, RAG pipelines, agentic systems, and complex multi-step workflows. Openlayer provides more than 100 automated tests for evaluating model quality, safety, reliability, data quality, performance, and policy compliance. Teams can use these tests to automate comprehensive model evaluations and identify issues before AI systems affect users, customers, or business operations. The platform’s observability features provide full traceability across prompts, retrieved context, agents, tool usage, intermediate steps, model outputs, and workflow decisions. Real-time guardrails help prevent prompt injections, PII leakage, biased outputs, toxicity, hallucinations, and other AI safety risks. Openlayer supports teams across the full AI lifecycle, from early experimentation and validation to production monitoring and governance reporting. Its governance automation capabilities help organizations align AI development and deployment processes with responsible AI frameworks such as NIST and the EU AI Act. The platform is built for enterprises that need to innovate with AI while maintaining security, compliance, explainability, and operational oversight. Openlayer also helps teams manage risk across both classic machine learning models and newer GenAI systems, giving organizations a unified approach to AI quality and trust. By combining automated testing, observability, real-time protection, traceability, and governance workflows, Openlayer enables safer, more reliable, and more responsible AI operations at scale.

Enkrypt AI is an agentic AI security and compliance platform that helps enterprises identify, mitigate, monitor, and govern risks associated with AI models, applications, agents, and supporting infrastructure. The platform is designed to cover AI security threats and compliance requirements across different models and modalities while allowing organizations to continuously evaluate AI systems as they evolve. Its dynamic red teaming capabilities generate use-case-specific attacks that adapt in real time to uncover security, safety, compliance, and brand risks beyond those identified through static testing. Enkrypt AI can test for threats including prompt injection, jailbreaking, data leakage, model inversion, adversarial attacks, drip attacks, unsafe actuation, policy violations, and misuse by end users. It also evaluates AI quality and safety risks such as hallucinations, model drift, bias and discrimination, toxic content, deceptive behavior, misleading outputs, lack of explainability, and brand misalignment. Real-time guardrails detect and stop risky interactions as they occur while adapting to new prompts, behaviors, and emerging threats. Continuous monitoring gives security and compliance teams visibility into AI risks, protection effectiveness, and areas requiring action as models and applications change. Enkrypt AI's compliance functionality converts internal policies and external regulatory requirements into automated guardrails and generates evidence that can support audits and compliance programs. The product portfolio includes Agent Red Teaming, Agent Guardrails, an Agent Policy Engine, AI Data Risk Audit, MCP Scanner, and MCP Gateway for protecting AI agents, their data, and their connections to tools and infrastructure. Enkrypt AI supports use cases including customer-facing AI agents, frontier models, AI compliance and auditing, third-party AI risk, secure AI development, data risk assessment, and MCP security.

Domino is a powerful enterprise AI platform built to help organizations develop, deploy, and manage AI systems at scale while delivering measurable business value. It provides a unified environment that supports the entire AI lifecycle, from data exploration and experimentation to deployment and monitoring. The platform enables self-service data science by giving users secure access to datasets, development tools, and scalable compute resources such as CPUs and GPUs. Domino supports a wide range of AI applications, including machine learning models, generative AI solutions, and agent-based systems. Its orchestration capabilities allow organizations to run workloads across hybrid, multi-cloud, and on-premises environments with flexibility and efficiency. The platform includes robust governance features, such as model registries, audit trails, and automated policy enforcement, ensuring transparency and compliance. It also tracks experiments and model lineage, providing a complete system of record for AI development. Domino enhances collaboration by enabling teams to share insights, tools, and workflows across the enterprise. Cost optimization tools help manage infrastructure spending through autoscaling and resource monitoring. The platform integrates seamlessly with existing enterprise systems and supports industry-standard tools and frameworks. With strong security certifications and compliance support, it meets the needs of regulated industries. Overall, Domino enables organizations to industrialize AI, reduce risk, and accelerate innovation while maintaining full control over their AI operations.

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.