Top Peta 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.

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.

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.

The Microsoft MCP Gateway functions as a versatile open-source reverse proxy and management interface specifically designed for Model Context Protocol (MCP) servers, enabling scalable and session-aware routing while also providing lifecycle management and centralized control over MCP services, especially in Kubernetes environments. Serving as a control plane, it effectively channels requests from AI agents (MCP clients) to their respective backend MCP servers, ensuring session affinity and managing a variety of tools and endpoints through a unified gateway that emphasizes authorization and observability. Furthermore, it allows teams to deploy, update, and decommission MCP servers and tools using RESTful APIs, which facilitate the registration of tool definitions and resource management, all reinforced by security protocols such as bearer tokens and role-based access control (RBAC). The architecture distinctly differentiates the management of the control plane—which encompasses CRUD operations on adapters, tools, and metadata—from the routing capabilities of the data plane, which accommodates streamable HTTP connections and dynamic tool routing, thereby delivering sophisticated functionalities like session-aware stateful routing. This thoughtful design not only boosts operational efficiency but also cultivates a more secure and robust environment for overseeing AI services, ultimately paving the way for streamlined management and enhanced performance in complex deployments.

MCPTotal stands out as a comprehensive, enterprise-grade solution designed to streamline the management, hosting, and governance of MCP (Model Context Protocol) servers and AI-tool integrations within a secure and audit-compliant environment, eliminating the risks associated with running these systems on developers' personal machines. Central to this platform is the “Hub,” which provides a controlled, sandboxed runtime environment where MCP servers are securely containerized, reinforced, and meticulously examined for vulnerabilities. Complementing this, the integrated “MCP Gateway” acts as an AI-centric firewall that conducts real-time analysis of MCP traffic, implements security protocols, monitors all interactions and data flows, and addresses common threats such as data breaches, prompt-injection attacks, and unauthorized credential usage. To further bolster security, all API keys, environment variables, and credentials are stored in an encrypted vault, effectively curbing credential sprawl and minimizing the risks linked with storing sensitive data in plaintext on individual devices. In addition, MCPTotal equips organizations with powerful discovery and governance tools, enabling security teams to scan both desktop and cloud environments to pinpoint the active usage of MCP servers, thereby ensuring thorough oversight and control. With its extensive features, this platform not only enhances security but also significantly improves the efficiency of managing AI resources across enterprises, ultimately fostering a more secure operational landscape for 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.

MintMCP acts as a comprehensive Model Context Protocol (MCP) gateway and governance solution tailored for enterprises, presenting a unified strategy for security, observability, authentication, and compliance related to AI tools and agents that interact with internal information, systems, and services. This innovative platform enables organizations to deploy, supervise, and manage their MCP infrastructure on a vast scale, delivering real-time insights into every interaction with MCP tools while incorporating role-based access control and enterprise-level authentication, all while ensuring thorough audit trails that comply with regulatory requirements. Serving as a proxy gateway, MintMCP efficiently consolidates connections from multiple AI assistants, such as ChatGPT, Claude, and Cursor, thereby simplifying monitoring tasks, reducing risky behaviors, securely managing credentials, and enforcing specific policy measures without the need for separate security setups for each individual tool. By centralizing these essential functions, MintMCP not only boosts operational efficiency but also strengthens the security framework of organizations utilizing AI technologies. This integrated approach ultimately allows businesses to focus on their core objectives, knowing their AI interactions are managed securely and effectively.

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.

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.

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.

PetaSAN is a sophisticated scale-out storage solution that functions in an active/active configuration, offering remarkable scalability and performance. By utilizing modern cloud technologies, PetaSAN allows for the effortless expansion of the storage cluster by adding nodes at any point without interrupting existing operations. While it operates on complex technologies, PetaSAN presents a unified solution that is easy to install and manage. Its intuitive graphical interfaces are designed to be user-friendly for those who may not have Linux administration experience, yet still provide comprehensive control for advanced Linux users. PetaSAN effectively integrates established technologies that support some of the most significant cloud infrastructures available, employing simple point-and-click interfaces for ease of use. At its foundation, PetaSAN utilizes the Ceph storage engine, a cutting-edge open-source software-defined storage solution that underpins many private and public cloud environments. This combination of usability and high performance positions PetaSAN as an attractive option for organizations aiming to improve their data storage capabilities. Additionally, the flexibility and scalability of PetaSAN make it suitable for a wide range of applications, ensuring that it can adapt to the evolving needs of businesses.

Webrix MCP Gateway acts as a holistic platform for businesses looking to securely incorporate AI solutions, facilitating smooth connections between multiple AI agents (including Claude, ChatGPT, Cursor, and n8n) and internal enterprise systems on a grand scale. By leveraging the Model Context Protocol standard, Webrix offers a consolidated secure gateway that addresses a significant barrier to AI implementation: the security concerns tied to tool access. Notable features encompass: - Centralized Single Sign-On (SSO) and Role-Based Access Control (RBAC) – This feature enables employees to log into authorized tools instantly, eliminating the need for IT ticket submissions. - Universal agent compatibility – The system accommodates any AI agent that adheres to the MCP standard. - Strong enterprise security – Includes comprehensive audit logs, effective credential management, and rigorous policy enforcement. - Self-service capability – Employees can conveniently access internal resources (such as Jira, GitHub, databases, and APIs) through their preferred AI agents without the need for manual configurations. By tackling the crucial issue of AI integration, Webrix equips your team with essential AI functionalities while ensuring stringent security, oversight, and compliance. Furthermore, whether you opt for an on-premise setup, a deployment within your cloud infrastructure, or our managed services, Webrix is designed to adapt seamlessly to the specific requirements of your organization, fostering innovation and efficiency.

Gate22 functions as a comprehensive platform for AI governance and Model Context Protocol (MCP) control that is tailored for enterprises, providing centralized management of the security and oversight of AI tools and agents interacting with MCP servers. It enables administrators to onboard, configure, and manage both internal and external MCP servers, offering granular permissions at the functional level, team-oriented access controls, and role-specific policies to guarantee that only approved tools and capabilities are accessible to the appropriate teams or individuals. By delivering a unified MCP endpoint, Gate22 consolidates multiple MCP servers into an easily navigable interface with just two main functions, which helps to lessen token consumption for developers and AI clients while effectively reducing context overload and maintaining both accuracy and security. The platform features an administrative interface with a governance dashboard that tracks usage patterns, ensures compliance, and applies least-privilege access, while the member interface streamlines and secures access to authorized MCP bundles. This dual perspective not only enhances operational productivity but also fortifies the overall security infrastructure within the organization. Additionally, the integration of these functionalities fosters a collaborative environment where teams can work more effectively while adhering to compliance standards.

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.

The Docker MCP Gateway serves as a crucial open source component within the Docker MCP Catalog and Toolkit, specifically crafted to operate Model Context Protocol (MCP) servers inside isolated Docker containers that maintain limited privileges, restricted network access, and specific resource constraints, thus ensuring secure and reliable environments for AI applications. This component manages the entire lifecycle of MCP servers by initiating containers whenever an AI application demands a particular tool, injecting required credentials, implementing security protocols, and routing requests so that servers can efficiently handle them and provide results through a single, integrated gateway interface. By consolidating all operational MCP containers behind a single access point, the Gateway simplifies the process for AI clients to find and utilize various MCP services, reducing redundancy, enhancing performance, and centralizing configuration and authentication aspects. Ultimately, it simplifies the interactions between AI applications and a variety of services, promoting a more streamlined development process while significantly improving overall system security. Additionally, this integrated approach allows developers to focus on innovation rather than managing complex service interactions, further enhancing productivity and effectiveness in AI deployment.

Arcade.dev is an innovative platform tailored for the execution of AI tool calls, enabling AI agents to perform real-world tasks like sending emails, messaging, updating systems, or triggering workflows via user-authorized integrations. Acting as a secure authenticated proxy that adheres to the OpenAI API specifications, Arcade.dev facilitates models' access to a variety of external services such as Gmail, Slack, GitHub, Salesforce, and Notion, utilizing both ready-made connectors and customizable tool SDKs while proficiently managing authentication, token handling, and security protocols. Developers benefit from a user-friendly client interface—arcadepy for Python or arcadejs for JavaScript—that streamlines the processes of executing tools and granting authorizations, effectively removing the burden of managing credentials or API intricacies from application logic. The platform boasts impressive versatility, enabling secure deployments across cloud environments, private VPCs, or local setups, and includes a comprehensive control plane for managing tools, users, permissions, and observability. This extensive management framework guarantees that developers can maintain oversight and control, harnessing AI's capabilities to automate a wide range of tasks efficiently while ensuring user safety and compliance throughout the process. Additionally, the focus on user authorization helps foster trust, making it easier to adopt and integrate AI solutions into existing workflows.

Multifactor is a sophisticated platform tailored for managing account-sharing and access control, prioritizing a zero-trust methodology while employing post-quantum cryptography and complex permission settings. Users are empowered to securely store their digital accounts—ranging from passwords and passkeys to 2FA codes—in a protected vault, enabling them to dispatch controlled links that grant access to both individuals and AI agents. This feature of immediate access revocation ensures that all underlying credentials remain hidden, significantly boosting security. Users can define specific permissions, allowing for instance, the ability to "view transactions" without granting the power to "initiate transfers," all while maintaining detailed, non-repudiable audit trails for every action performed. Additionally, the platform integrates robust encryption alongside a post-quantum security architecture, affirming that only those with authorization can access sensitive data. It also serves as a comprehensive identity and access management system, supporting a variety of authentication methods such as biometrics and hardware tokens, while managing authorization, auditing access, enforcing device and network endpoint controls, and enabling secure resource sharing. This multifaceted strategy not only streamlines access management but also significantly bolsters overall cybersecurity defenses, positioning it as an essential tool for modern digital security needs. Its adaptability ensures that it can meet the evolving challenges of a dynamic security landscape.

DeployStack serves as a robust management platform designed for the enterprise context of the Model Context Protocol (MCP), with the goal of centralizing, securing, and improving the governance of MCP servers and AI tools across organizations. It boasts an all-in-one dashboard that facilitates the oversight of all MCP servers and integrates a centralized credential vault to eliminate the hassle of managing numerous API keys and configuration files. Furthermore, it employs role-based access control, OAuth2 authentication, and high-grade encryption to ensure that enterprise operations remain secure. The platform also delivers in-depth usage analytics and observability, providing real-time insights into MCP tool utilization, such as user access trends and frequency, while maintaining extensive audit logs for compliance and financial transparency. Moreover, DeployStack enhances token and context window management, allowing Large Language Model (LLM) clients to significantly reduce token usage through a hierarchical routing system that efficiently accesses multiple MCP servers, thereby preserving model performance without compromise. This forward-thinking solution not only streamlines operational processes but also equips organizations with the tools needed to effectively manage their AI resources, all while upholding stringent security and compliance standards. As a result, DeployStack positions itself as an indispensable asset for enterprises navigating the complexities of AI governance.

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.

Storm MCP acts as a sophisticated gateway focused on the Model Context Protocol (MCP), enabling effortless connections between AI applications and a variety of verified MCP servers with a simple one-click deployment option. It guarantees strong enterprise-grade security, improved observability, and straightforward tool integration without requiring extensive custom coding efforts. By standardizing connections for AI and selectively exposing specific tools from each MCP server, it aids in reducing token consumption while optimizing model tool selection. Users benefit from its Lightning deployment feature, granting access to over 30 secure MCP servers, while Storm efficiently handles OAuth-based access, detailed usage logs, rate limits, and monitoring. This cutting-edge solution is designed to securely link AI agents with external context sources, allowing developers to avoid the complexities involved in creating and maintaining their own MCP servers. Aimed at AI agent developers, workflow creators, and independent innovators, Storm MCP is distinguished as a versatile and customizable API gateway, alleviating infrastructure challenges while providing reliable context for a wide array of applications. Its distinctive features make it a vital resource for enhancing the AI integration experience, ultimately paving the way for more innovative and efficient solutions in the realm of artificial intelligence.

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.

InstaVM presents a powerful cloud and production sandbox solution tailored for AI agents, offering immediate access to essential computing resources such as runtime, storage, networking, policy management, and secrets. Distinguishing itself from conventional sandboxes, it employs hardware-isolated virtual machines rather than containers, thus providing secure environments equipped with complete Linux filesystems, networking capabilities, package management, RESTful API access, and the ability to sustain persistent states. The platform's snapshot feature allows users to create duplicates of any sandbox and revert to earlier configurations, while its persistent volumes guarantee that data remains intact across different executions. Furthermore, egress control empowers teams to dictate which external connections can be established, complemented by features like secrets injection and Vault to protect sensitive data from potential vulnerabilities. Additionally, the ability to deploy public URLs renders any port accessible on the public internet, augmenting its versatility. Designed with various agent patterns in mind, such as code interpreters, deployment agents, deep research agents, AI evaluations, reinforcement learning applications, and vibe coding applications, it serves as an all-encompassing tool for developers. With its groundbreaking architecture and wide-ranging features, InstaVM establishes itself as a premier solution for projects driven by artificial intelligence, enabling seamless integration and operation across diverse applications. As the landscape of AI development evolves, InstaVM positions itself as an essential resource for teams looking to leverage cutting-edge technology effectively.

Axway Amplify is an enterprise API management, integration, and AI governance platform built to help organizations connect complex digital ecosystems with more control and flexibility. The platform is federated by design, meaning it can publish, validate, govern, secure, and monitor APIs across multiple clouds, on-premises data centers, vendors, gateways, and repositories. Amplify API Management supports secure API lifecycle management from design through implementation, helping internal and external teams collaborate, reach new markets, and manage APIs across hybrid environments. Amplify Fusion gives IT and business users low-code and no-code tools for building integration flows, automating tasks, designing event-based processes, and reducing the burden on centralized IT teams. Amplify Engage helps enterprises turn APIs and digital assets into discoverable, governed, reusable products through curated marketplaces and developer access controls. Amplify AI Gateway provides a governance layer for production AI usage, including MCP server publishing, prompt guards, prompt templates, LLM orchestration, authentication, authorization, and threat protection. The Amplify Management Plane gives organizations a central place to govern and monitor APIs while allowing development teams to keep using preferred tools and gateways. Amplify Agents help capture API value by making APIs easier to discover, reuse, and govern across environments such as AWS, Azure, Istio, and other gateway systems. The platform supports a broader range of API patterns beyond SOAP and REST, including GraphQL, events, service mesh, gRPC, and AsyncAPI. Because Amplify is modular, organizations can start with federated API management, low-code integration, API adoption, or AI governance and scale the platform as their architecture matures.

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.

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.

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.

SocialPeta emerges as the leading platform dedicated to the analysis of advertising creatives, featuring a vast repository of more than 600 million creatives sourced from 68 networks, which encompass prominent entities like Facebook, Admob, Unity, and Chartboost. Currently, we proudly serve over 200 enterprise clients, including industry giants such as Google, Baidu, YOOZOO, NetEase, 37games, Cheetah Mobile, iGG, and Bigo Live, showcasing our significant presence in the market. The variety of partnerships we engage in emphasizes our dedication to delivering exceptional insights into the advertising ecosystem, which is crucial for businesses seeking to navigate this dynamic industry effectively. Such collaborations not only enhance our offerings but also reinforce our reputation as a trusted resource for advertising intelligence.

Prefect Horizon functions as a comprehensive managed AI infrastructure platform within the broader Prefect product suite, empowering teams to deploy, govern, and oversee Model Context Protocol (MCP) servers and AI agents at an enterprise scale, equipped with crucial production-ready features such as managed hosting, authentication, access control, observability, and governance tools. Utilizing the innovative FastMCP framework, it elevates MCP from a simple protocol to a robust platform composed of four interconnected core components: Deploy, which streamlines the quick hosting and scaling of MCP servers through continuous integration, continuous deployment (CI/CD), and monitoring; Registry, serving as a centralized hub for first-party, third-party, and curated MCP endpoints; Gateway, delivering role-based access control, authentication, and audit trails to ensure secure and regulated access to various tools; and Agents, which provide intuitive interfaces deployable in Horizon, Slack, or accessible via MCP, thereby enabling business users to interact with context-aware AI without needing in-depth technical knowledge of MCP. This comprehensive strategy not only allows organizations to fully leverage AI functionalities but also reinforces their governance and security measures, thus promoting a responsible use of advanced technologies. By integrating these elements, Prefect Horizon presents a solution that meets the intricate demands of modern enterprises in an increasingly data-driven world.

Nuphos is a specialized DevOps environment designed specifically for AI, allowing engineering teams and AI agents to work together in managing production systems while ensuring proper oversight and control. These intelligent agents are built to understand your infrastructure, effectively troubleshoot issues, and navigate various platforms such as AWS, GCP, Kubernetes, and Cloudflare, all while complying with rigorous IAM permissions and maintaining detailed audit trails. Each agent session is restricted to particular IAM roles and utilizes temporary, least-privilege credentials, guaranteeing that any changes proposed to the infrastructure receive prior approval. The agents possess the capability to review resources, access dashboards, analyze logs, formulate actionable plans, request necessary approvals, and execute safe actions, simultaneously enriching their knowledge about services, environments, workflows, runbooks, and operational history. Rather than switching between numerous terminals, cloud interfaces, dashboards, and documentation, engineers and agents work together within a cohesive DevOps workspace to enhance both efficiency and clarity. This collaborative framework not only streamlines workflows but also empowers both teams and AI to innovate and tackle challenges more adeptly, ultimately leading to improved productivity and responsiveness. By fostering a shared environment, Nuphos encourages open communication and knowledge sharing between human engineers and AI agents, further enhancing operational effectiveness.