Alternatives to elsai Foundry

Gemini Enterprise Agent Platform is Google Cloud’s next-generation system for designing and managing advanced AI agents across the enterprise. Built as the successor to Vertex AI, it unifies model selection, development, and deployment into a single scalable environment. The platform supports a vast ecosystem of over 200 AI models, including Google’s latest Gemini innovations and popular third-party models. It offers flexible development tools like Agent Studio for visual workflows and the Agent Development Kit for deeper customization. Businesses can deploy agents that operate continuously, maintain long-term memory, and handle multi-step processes with high efficiency. Security and governance are central, with features such as agent identity verification, centralized registries, and controlled access through gateways. The platform also enables seamless integration with enterprise systems, allowing agents to interact with data, applications, and workflows securely. Advanced monitoring tools provide real-time insights into agent behavior and performance. Optimization features help refine agent logic and improve accuracy over time. By combining automation, intelligence, and governance, the platform helps organizations transition to autonomous, AI-driven operations. It ultimately supports faster innovation while maintaining enterprise-grade reliability and control.

Elsai is an enterprise AI platform that prioritizes governance, converting intricate workflows into operations that are manageable, transparent, and ready for production. Designed specifically for regulated and enterprise settings, elsai integrates elements such as AI orchestration, observability, safety measures, workflow automation, and compliance governance within a single execution framework. This comprehensive approach empowers organizations to expand their AI capabilities while ensuring that visibility, security, auditability, and cost management are inherently included. As a result, businesses can confidently navigate the complexities of AI implementation while adhering to governance standards.

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

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

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

Velatir serves as a platform for AI governance, aimed at connecting sophisticated AI technologies with necessary compliance and human oversight. Our approach incorporates human-in-the-loop governance that transforms regulatory challenges into opportunities for enhancement. By leveraging a smart policy engine, intelligent routing mechanisms, and streamlined approval workflows through platforms like Slack, Teams, email, or the web, we guarantee that AI integration is secure, transparent, and capable of scaling effectively. Constructed on a fully EU-based infrastructure, Velatir empowers operations, IT, and compliance teams to effectively handle risks, ensure adherence to regulations, and boost efficiency across their processes. This comprehensive solution not only supports regulatory compliance but also fosters a culture of innovation and trust within organizations.

Vivgrid serves as a comprehensive development platform tailored for AI agents, focusing on critical aspects such as observability, debugging, safety, and a robust global deployment framework. It provides complete transparency into agent activities by logging prompts, memory retrievals, tool interactions, and reasoning processes, allowing developers to identify and address any points of failure or unexpected behavior. Furthermore, it enables the testing and enforcement of safety protocols, including refusal rules and filters, while facilitating human-in-the-loop oversight prior to deployment. Vivgrid also manages the orchestration of multi-agent systems equipped with stateful memory, dynamically assigning tasks across various agent workflows. On the deployment front, it utilizes a globally distributed inference network to guarantee low-latency execution, achieving response times under 50 milliseconds, and offers real-time metrics on latency, costs, and usage. By integrating debugging, evaluation, safety, and deployment into a single coherent framework, Vivgrid aims to streamline the process of delivering resilient AI systems without the need for disparate components in observability, infrastructure, and orchestration, ultimately enhancing efficiency for developers. This holistic approach empowers teams to focus on innovation rather than the complexities of system integration.

JetStream Security serves as a governance platform focused on security, enabling enterprises to gain comprehensive visibility, control, and responsibility over their AI systems by transforming them from unclear, disjointed applications into managed and traceable infrastructures. Functioning as a unified control center, it integrates identity management, operational governance, monitoring, and financial management into one cohesive system, empowering organizations to “monitor every AI action, associate actions with accountable individuals, and ensure workflows stay within authorized limits” while applying policies during runtime. Furthermore, it incorporates agentic identity, linking human, agentic, and non-human identities to specific actions and access rights, thereby ensuring that each invocation, tool usage, or workflow can be tracked and governed according to least-privilege access standards. By maintaining ongoing runtime governance, JetStream continuously evaluates actual AI behavior against pre-approved frameworks, utilizing immutable logging and real-time monitoring to identify deviations, thereby reinforcing security and compliance. This robust approach not only enhances accountability but also supports organizations in navigating the complexities of AI governance effectively.

Maxim is a enterprise-grade stack that enables AI teams to build applications with speed, reliability, and quality. Bring the best practices from traditional software development to your non-deterministic AI work flows. Playground for your rapid engineering needs. Iterate quickly and systematically with your team. Organise and version prompts away from the codebase. Test, iterate and deploy prompts with no code changes. Connect to your data, RAG Pipelines, and prompt tools. Chain prompts, other components and workflows together to create and test workflows. Unified framework for machine- and human-evaluation. Quantify improvements and regressions to deploy with confidence. Visualize the evaluation of large test suites and multiple versions. Simplify and scale human assessment pipelines. Integrate seamlessly into your CI/CD workflows. Monitor AI system usage in real-time and optimize it with speed.

asqav is a cutting-edge platform focused on AI governance and security, aimed at ensuring that AI agents are always prepared for audits by offering real-time oversight, enforcement, and a reliable record of each action performed by the agents. It features a streamlined SDK that empowers developers to embed governance functionalities directly into their AI agents with minimal code, facilitating comprehensive monitoring throughout the entire lifecycle of AI activities. Additionally, the platform incorporates behavioral analysis to identify potential problems like drift, rate limits, and scope breaches, as well as sophisticated threat detection mechanisms that can recognize issues such as prompt injections, leaks of sensitive information, harmful outputs, and other dangers. Policy enforcement is achieved through customizable “policy gates,” which implement specific rules for each agent, conduct preflight assessments, and provide dynamic approvals before any actions are taken, thereby guaranteeing that agents function within established parameters. Furthermore, asqav enhances security with automated incident response features, allowing for the suspension, isolation, or escalation of agents deemed risky, all of which contribute to a robust framework for maintaining AI accountability and safety. In this way, asqav not only safeguards AI operations but also promotes trust in their deployment across various sectors.

Warestack is an AI-driven platform designed to enhance release protection by integrating directly into your GitHub organization and implementing tailored, context-sensitive guardrails throughout every phase of the development process. Users can articulate protection guidelines in straightforward language, such as mandating approvals for any pull requests that are not hotfixes or prohibiting deployments on Fridays, and Warestack will automatically identify or prevent high-risk actions, while simultaneously tracking activities such as pull requests, issues, deployments, and workflow executions in real-time, all presented in a consolidated dashboard. The platform also works smoothly with popular tools like GitHub, Slack, and Linear, providing intelligent alerts and notifications, in addition to offering one-click audit logs and reports that cater to SOC-2 and compliance requirements. Furthermore, Warestack adapts effortlessly to various teams and repositories through the application of scoped rules, role-based enforcement, and a transparent open-source rule engine called Watchflow, which facilitates the creation of policies. This ensures that organizations can maintain a high standard of security and compliance in their development environments, all while enjoying the flexibility to customize their protection strategies as needed.

Tuning Engines serves as a comprehensive AI control and governance framework designed for teams engaged in building production intelligence that spans various models, agents, tools, and specialized systems. This platform consolidates the entire AI lifecycle into a single, regulated environment, encompassing aspects like inference, model routing, fallback strategies, fine-tuning tasks, datasets, evaluations, model imports and exports, custom models, agents, MCP servers, reusable skills, guardrails, AGT YAML policies, data capture, runtime tracing, usage analytics, API management, billing, team roles, and numerous integrations. Developers benefit from APIs compatible with OpenAI, routes aligned with Anthropic, CLI workflows, MCP access, and seamless coding-agent integrations, along with a comprehensive resource catalog for models, agents, tools, and skills. Moreover, teams have the ability to link various AI workflows, including Claude Code, OpenCode, Aider, Cline, Roo, Continue.dev, Cursor, VS Code, Windsurf, and more, all through a singular, governed platform that enhances collaboration and efficiency.

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

The Oracle AI Agent Platform is a comprehensive service designed for the development, implementation, and oversight of sophisticated virtual agents that utilize large language models along with integrated AI technologies. Setting up these agents involves a straightforward multi-step process, allowing them to utilize various tools such as converting natural language into SQL queries, enhancing responses with information from enterprise knowledge repositories, invoking custom functions or APIs, and managing interactions with sub-agents. These agents are capable of engaging in multi-turn conversations while maintaining context, which allows them to address follow-up inquiries and provide personalized, coherent exchanges. To ensure quality and safety, the platform includes built-in guardrails for content moderation, prevention of prompt injection attacks, and safeguarding of personally identifiable information (PII). Additionally, the system offers optional human-in-the-loop mechanisms that enable real-time oversight and the ability to escalate issues when necessary, ensuring a balance between automation and human control. This combination of features positions the Oracle AI Agent Platform as a robust solution for businesses looking to enhance customer interactions through intelligent automation.

Preloop serves as an open-source control plane designed for AI agents that perform tangible actions. It integrates a multi-layered security approach featuring an MCP firewall for managing tool access, an AI model gateway that ensures cost-effectiveness, safety, and accountability, along with policy-as-code that incorporates human oversight, all while providing runtime session visibility and audit trails—all within a self-hosted environment. Given the rapid capabilities of AI agents to deploy code, modify infrastructure, manage financial transactions, access production data, and incur model costs almost instantaneously, Preloop empowers teams to regulate agent activities, monitor expenditures, and determine which actions necessitate human consent. It is compatible with a variety of tools such as OpenClaw, Hermes, Claude Code, Codex CLI, Cursor, Gemini CLI, Windsurf, Cline, OpenCode, and any agents that adhere to MCP standards. Additionally, access rules can evaluate not only the tool names but also arguments and context, utilizing CEL expressions to establish detailed conditions. Furthermore, teams have the flexibility to initiate with observability features and progressively introduce approval and denial protocols without the need for SDKs or extensive modifications to existing applications, thus streamlining the implementation process. This comprehensive approach ensures that organizations remain in control of their AI agents' functionalities and impacts.

Microsoft Foundry Agent Service provides a unified environment for building intelligent agents that automate high-value tasks across an organization. It supports multi-agent workflows, hosted custom-code agents, and seamless integration with Azure Logic Apps and other enterprise systems. Developers can extend agent capabilities using built-in memory, ready-to-use tools, and secure connectivity powered by the Model Context Protocol. The platform includes deep observability features—such as tracing, dashboards, and guardrails—to ensure safe, reliable, and cost-efficient operations at scale. Built-in governance via Entra Agent ID gives each agent a managed identity with full lifecycle, access, and policy controls. Organizations can deploy agents directly into Teams and Microsoft 365 Copilot to bring automation into everyday employee workflows instantly. With more than 100 compliance certifications and enterprise-grade security, Foundry Agent Service supports even the most regulated industries. Its combination of extensibility, security, and operational readiness makes it a powerful foundation for enterprise-wide AI adoption.

GolfMCP serves as an open-source framework aimed at simplifying the development and deployment of production-ready Model Context Protocol (MCP) servers, which empowers organizations to construct a secure and scalable infrastructure for AI agents without the hassle of boilerplate code. Developers can effortlessly define tools, prompts, and resources using straightforward Python files, while Golf takes care of essential tasks like routing, authentication, telemetry, and observability, allowing you to concentrate on the core logic rather than underlying plumbing. The platform incorporates enterprise-level authentication methods such as JWT, OAuth Server, and API keys, along with automatic telemetry and a file-based organization that removes the need for decorators or manual schema configurations. It also features built-in utilities that facilitate interactions with large language models (LLMs), comprehensive error logging, OpenTelemetry integration, and deployment tools like a command-line interface with commands for initializing, building, and running projects. Furthermore, Golf includes the Golf Firewall, a robust security layer tailored for MCP servers that enforces strict token validation to enhance the overall security framework. This extensive functionality ensures that developers are equipped with everything they need to create efficient AI-driven applications.

Tenable AI Exposure is a robust, agentless solution integrated into the Tenable One exposure management platform, designed to enhance visibility, context, and control over the utilization of generative AI tools such as ChatGPT Enterprise and Microsoft Copilot. This tool empowers organizations to track user engagement with AI technologies, providing insights into who is accessing them, the nature of the data involved, and the execution of workflows, while identifying and addressing potential risks like misconfigurations, insecure integrations, and the leakage of sensitive information, including personally identifiable information (PII), payment card information (PCI), and proprietary business data. Furthermore, it protects against threats like prompt injections, jailbreak attempts, and policy breaches by implementing security measures that do not interfere with daily operations. Compatible with leading AI platforms and ready for deployment in just minutes with zero downtime, Tenable AI Exposure facilitates the governance of AI use, making it an essential component of an organization's overall cyber risk management strategy, ultimately ensuring safer and more compliant AI operations. By integrating these security protocols, organizations can foster a culture of responsible AI usage while mitigating potential vulnerabilities.

LangProtect serves as a cutting-edge security and governance platform specifically designed for AI, offering robust protection against issues such as prompt injections, jailbreaks, data leaks, and the generation of unsafe or non-compliant outputs in LLM and Generative AI applications. Tailored for production-grade GenAI environments, this platform implements real-time controls at the execution level of AI, meticulously examining prompts, model outputs, and function calls as they occur, enabling teams to intercept high-risk actions before they can affect end users or compromise sensitive information. By doing so, LangProtect ensures that potential threats are neutralized promptly, preserving the integrity of data and user interactions. Furthermore, LangProtect seamlessly integrates with existing LLM infrastructures through an API-first design that maintains low latency, accommodating various deployment models including cloud, hybrid, and on-premise solutions to meet the security and data residency requirements of enterprises. It is also equipped to safeguard contemporary architectures like RAG pipelines and agentic workflows, providing policy-driven enforcement, continuous monitoring, and governance that is ready for audits. This comprehensive approach ensures that organizations can confidently leverage AI technologies while minimizing risks associated with their deployment.

Agent Builder is a component of OpenAI’s suite designed for creating agentic applications, which are systems that leverage large language models to autonomously carry out multi-step tasks while incorporating governance, tool integration, memory, orchestration, and observability features. This platform provides a flexible collection of components—such as models, tools, memory/state, guardrails, and workflow orchestration—which developers can piece together to create agents that determine the appropriate moments to utilize a tool, take action, or pause and transfer control. Additionally, OpenAI has introduced a new Responses API that merges chat functions with integrated tool usage, alongside an Agents SDK available in Python and JS/TS that simplifies the control loop, enforces guardrails (validations on inputs and outputs), manages agent handoffs, oversees session management, and tracks agent activities. Furthermore, agents can be enhanced with various built-in tools, including web search, file search, or computer functionalities, as well as custom function-calling tools, allowing for a diverse range of operational capabilities. Overall, this comprehensive ecosystem empowers developers to craft sophisticated applications that can adapt and respond to user needs with remarkable efficiency.

Agentspan is an innovative open-source server and SDK that introduces robust execution capabilities for AI agents, redefining their operation in practical settings that go beyond mere demonstrations. It empowers developers to create agents using Python and convert them into reliable, persistent workflows that safeguard execution state on the server, which prevents any loss of progress during system failures or restarts. This unique setup allows agents to pause and resume their tasks exactly where they stopped, even if they reconnect from a different device. Furthermore, it facilitates human oversight by allowing agents to pause for user approval and then continue effortlessly via platforms like Slack, web interfaces, or code. Additionally, Agentspan supports complex multi-agent workflows, enabling multiple agents to be interconnected in a single sequence, ensuring that every step is meticulously logged, monitored, and recoverable throughout the entire process. This comprehensive approach enhances both the reliability and flexibility of AI applications in various operational contexts.

Enhance your observability framework to swiftly identify data and machine learning challenges, facilitate ongoing enhancements, and prevent expensive incidents. Begin with dependable data by consistently monitoring data-in-motion to catch any quality concerns. Accurately detect shifts in data and models while recognizing discrepancies between training and serving datasets, allowing for timely retraining. Continuously track essential performance metrics to uncover any decline in model accuracy. It's crucial to identify and mitigate risky behaviors in generative AI applications to prevent data leaks and protect these systems from malicious attacks. Foster improvements in AI applications through user feedback, diligent monitoring, and collaboration across teams. With purpose-built agents, you can integrate in just minutes, allowing for the analysis of raw data without the need for movement or duplication, thereby ensuring both privacy and security. Onboard the WhyLabs SaaS Platform for a variety of use cases, utilizing a proprietary privacy-preserving integration that is security-approved for both healthcare and banking sectors, making it a versatile solution for sensitive environments. Additionally, this approach not only streamlines workflows but also enhances overall operational efficiency.

MintMCP serves as a robust Model Context Protocol (MCP) gateway and governance solution designed for enterprises, offering a centralized approach to security, observability, authentication, and compliance for AI tools and agents that interface with internal data, systems, and services. This platform empowers organizations to deploy, oversee, and manage their MCP infrastructure on a large scale, providing real-time insights into each MCP tool interaction while implementing role-based access control and enterprise-level authentication, all while ensuring comprehensive audit trails that adhere to regulatory standards. Functioning as a proxy gateway, MintMCP effectively aggregates connections from various AI assistants, including ChatGPT, Claude, and Cursor, streamlining monitoring processes, mitigating risky behaviors, managing credentials securely, and enforcing detailed policy measures without necessitating individual security implementations for each tool. By centralizing these functions, MintMCP not only enhances operational efficiency but also fortifies the security posture of organizations leveraging AI technologies.

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

OpenBox serves as a robust AI governance platform tailored for enterprises, aiming to ensure that AI systems remain transparent, auditable, and securely deployable on a large scale by instituting real-time monitoring of every action taken by agents and interactions within the system. By offering a cohesive governance framework, it amalgamates identity, policy, risk management, and compliance into a singular runtime environment, thereby addressing the common issue of fragmentation associated with using multiple tools and allowing organizations to maintain standardized oversight over AI activities. Seamlessly integrating with current AI workflows via a streamlined SDK, it necessitates no modifications to existing architectures while providing immediate insights into the operational behavior, decision-making processes, and inter-system communications of AI agents. Furthermore, OpenBox proactively supervises and assesses each action prior to its execution, implementing policy enforcement and regulatory evaluations instantaneously to avert any non-compliant or high-risk activities, ensuring a more preventative approach rather than simply responding to issues post-factum. This proactive stance not only enhances compliance but also fosters a culture of accountability in AI operations.

GraphBit is a robust AI framework tailored for enterprises, intended to manage essential AI systems while ensuring security, governance, and reliable production performance. By leveraging a high-performance Rust execution core along with a Python wrapper, it offers developers an optimal blend of orchestration efficiency and Python's user-friendly nature, enabling the creation of dependable multi-agent workflows that consume minimal CPU and memory resources. The architecture of GraphBit is meticulously structured to mitigate risks, incorporating various layers such as interfaces, configuration, models, tools, actions, memory, orchestration, and observability. This framework seamlessly integrates with existing applications, facilitates the development of bespoke AI interfaces, and allows users to engage through intuitive workflows while maintaining controlled actions. Teams are empowered to set policies, rules, and guardrails from a central location, with GraphBit ensuring compliance without necessitating modifications to application code. Additionally, it accommodates LLMs and multimodal models sourced from diverse providers, providing teams with the flexibility to interchange models effortlessly while preserving workflows and governance. With its comprehensive design, GraphBit not only enhances operational efficiency but also fosters innovation by enabling teams to focus on developing advanced AI solutions.

Barndoor serves as a robust management layer for data and access, ensuring that artificial intelligence systems interact securely with enterprise data and infrastructure. Acting as a unified control center, it oversees AI agents and applications, empowering organizations to set policies, automatically enforce access rules, and retain comprehensive oversight of AI tool operations within business frameworks. Moving beyond traditional identity-based permissions, Barndoor employs context-aware governance, which allows administrators to dictate the allowed actions of an AI agent by considering variables such as the user in charge of the agent, the system being accessed, the nature of the data, and the task at hand. This system assesses each AI request in real time to apply policies before actions are undertaken, thereby thwarting unsafe or unauthorized operations from affecting internal systems or altering sensitive data. Furthermore, by integrating such a nuanced approach to governance, organizations can enhance both security and compliance, ultimately fostering a more trustworthy AI ecosystem.

The Microsoft Agent Framework is an open-source software development kit and runtime that assists developers in creating, orchestrating, and deploying AI agents alongside multi-agent workflows, utilizing programming languages like .NET and Python. By merging the straightforward agent abstractions found in AutoGen with the sophisticated capabilities of Semantic Kernel, it offers features such as session-based state management, type safety, middleware, telemetry, and extensive model and embedding support, thus providing a cohesive platform suitable for both experimentation and production settings. Additionally, it features graph-based workflows that empower developers with precise control over the interactions among multiple agents, enabling them to execute tasks and coordinate intricate processes efficiently, which facilitates structured orchestration in various scenarios, including sequential, concurrent, or branching workflows. Furthermore, the framework accommodates long-running operations and human-in-the-loop workflows by implementing robust state management, enabling agents to retain context, tackle complex multi-step problems, and function continuously over extended periods. This combination of features not only streamlines development but also enhances the overall performance and reliability of AI-driven applications.

Token Security presents an innovative strategy tailored for the booming era of Non-Human Identities (NHI), emphasizing a machine-first approach to identity security. In today's digital landscape, identities are omnipresent and often unmanaged; they manifest as machines, applications, services, and workloads, continuously generated by various sources throughout the day. The intricate and sluggish nature of managing these identities has resulted in an attack surface that organizations find difficult to navigate. Rather than concentrating solely on human identities, Token prioritizes the resources being accessed, swiftly revealing who accesses which resources, identifying vulnerabilities, and ensuring security without disrupting operations. Furthermore, Token adeptly identifies all identities across cloud environments, seamlessly integrating intricate components such as Kubernetes, databases, servers, and containers, thereby consolidating relevant identity data into a cohesive perspective. This comprehensive approach not only enhances security but also simplifies the management of identities within increasingly complex infrastructures.

Domino is a comprehensive enterprise AI platform that enables organizations to transform AI initiatives into scalable, production-ready systems. It supports the full AI lifecycle, including data access, model development, deployment, and ongoing management. The platform provides a self-service environment where data scientists can access tools, datasets, and compute resources with built-in governance and security controls. Domino allows teams to build machine learning models, generative AI applications, and intelligent agents using their preferred development environments. It also includes advanced orchestration capabilities to manage workloads across hybrid, multi-cloud, and on-premises infrastructures. Governance features such as model registries, audit trails, and policy enforcement ensure compliance and reproducibility. The platform enhances collaboration by providing a centralized system of record for all AI assets and experiments. Additionally, it helps organizations optimize costs through resource management and usage tracking. Domino is designed to meet enterprise standards for security and regulatory compliance. Ultimately, it empowers businesses to accelerate AI innovation while maintaining operational control and accountability.

Webvar provides a comprehensive range of modular, AI-driven tools that integrate smoothly with AWS, enabling businesses to effectively automate, customize, and expand their operations. The platform facilitates the development of AI agent applications within a low-code framework, utilizing an array of robust business components and pre-existing applications such as automation for Excel, document extraction, RAG-based document generation, FAQ creation for support desks, and summarization of meeting minutes, all while ensuring security, monitoring, and operational management capabilities. By employing multi-agent orchestration, human-in-the-loop controls, and tailored process flows, Webvar streamlines knowledge-intensive workflows and incorporates governance features to maintain compliance and transparency. Furthermore, it enhances websites by converting them into engaging, conversational platforms that provide immediate, natural-language interactions from embedded knowledge bases, which may include PDFs and videos, alongside personalized calls to action and behavior-adaptive AI, as well as secure CMS integration, thus enriching the overall user experience. This multifaceted approach not only boosts efficiency but also fosters deeper customer engagement, making Webvar a powerful asset for businesses aiming to leverage AI technology effectively.

Coform AI is a no-code platform designed for enterprises and mid-market companies, enabling the configuration of autonomous AI agents that manage intricate operations and generate tangible business benefits. It empowers teams to create workflows that exceed basic automation, integrating agent orchestration with pre-built templates, monitoring capabilities, governance features, and deployment options within a single adaptable framework. Users can seamlessly connect various enterprise systems, set up workflows, and launch them without any coding or machine learning knowledge, accommodating multimodal inputs like text, images, documents, and audio. The platform's intuitive drag-and-drop interface, over 40 ready-to-use templates, LLM-agnostic framework, API integrations, human oversight mechanisms, built-in safeguards, audit trails, and clear cost structures enable organizations to transition from cumbersome manual processes to secure automated workflows, ultimately enhancing efficiency and productivity. By simplifying the implementation of AI-driven solutions, Coform AI empowers businesses to innovate and stay competitive in their respective markets.

Mind Foundry, an innovative artificial intelligence firm, operates at the crossroads of research, practicality, and user-centered design to equip teams with AI solutions tailored for human needs. Established by top-tier academics, the company creates AI tools aimed at assisting both public and private sector organizations in addressing critical challenges, emphasizing human-centered results and the lasting effects of AI applications. Their collaborative platform facilitates the design, testing, and implementation of AI, allowing stakeholders to oversee their AI investments with a strong emphasis on performance, efficiency, and ethical considerations. The foundation of their approach is rooted in scientific principles, underscoring the importance of integrating ethics and transparency from the outset rather than retroactively. By blending experience design with quantitative techniques, they enhance the collaboration between humans and AI, making it more intuitive, effective, and impactful, ultimately leading to better decision-making and outcomes for all involved. This commitment to fostering a responsible AI ecosystem ensures that the technology remains aligned with societal values and priorities.

Flowise is an open-source agentic development platform designed to help teams build AI agents and LLM-powered applications using a visual workflow interface. The platform allows users to design intelligent workflows through modular components that can be combined to create chatbots, automation systems, and autonomous AI agents. Developers can build both single-agent chat assistants and multi-agent systems that collaborate to complete complex tasks. Flowise integrates with more than 100 large language models, embedding models, and vector databases, providing flexibility in selecting AI technologies. The platform also supports retrieval-augmented generation (RAG), enabling applications to retrieve knowledge from documents and data sources. Built-in features such as human-in-the-loop workflows allow users to review and validate agent actions before execution. Observability tools provide detailed execution traces and compatibility with monitoring systems like Prometheus and OpenTelemetry. Developers can integrate Flowise with existing applications using APIs, SDKs, or embedded chat widgets. The platform supports both cloud and on-premises deployment environments for enterprise scalability. By providing visual tools and flexible integrations, Flowise accelerates the development and deployment of advanced AI-driven applications.

Claude Managed Agents is a ready-to-use, customizable agent framework created by Anthropic, intended to execute long-term, asynchronous activities on managed infrastructure without the need for developers to construct their own agent loops. This system serves as a comprehensive "agent harness," enabling developers to set objectives while the platform takes care of execution, orchestration, and state management seamlessly in the background. In contrast to conventional model prompting, which necessitates interactive, step-by-step engagement, Managed Agents are optimized for tasks that progress over a period, such as research projects, automation processes, or complex workflows, allowing for independent operation once initiated. Furthermore, it boasts sophisticated features like multi-agent orchestration, where a lead agent effectively manages specialized sub-agents that can function simultaneously in distinct contexts, thereby enhancing both speed and the quality of results. This innovative approach not only streamlines processes but also empowers developers to focus on high-level goals while the system efficiently handles the intricate details.

Swiftask allows organizations to seamlessly integrate multiple AI models into automated workflows without requiring any coding, providing robust enterprise governance in the process. By connecting AI models into comprehensive end-to-end workflows, tasks such as lead research, opportunity scoring, CRM updates, competitor monitoring, insights extraction, report generation, ticket analysis, response drafting, content translation, and team routing can all be transformed from hours of manual effort into mere minutes of automation. Additionally, companies can develop AI-driven knowledge assistants capable of responding to inquiries about HR policies, technical documents, and product specifications, significantly cutting down response times from hours to mere seconds. Business teams can easily create customized agents via user-friendly no-code interfaces, allowing them to define specific roles, link relevant data, and configure workflows for rapid deployment within days. With features like role-based access control (RBAC), comprehensive audit logs, and SSO/SAML authentication, enterprises can effectively monitor usage, manage expenses, ensure regulatory compliance, and eliminate instances of Shadow IT, ultimately enhancing operational efficiency and security. This powerful combination of features empowers organizations to leverage AI technology to its fullest potential.

Both AI and non-AI models require effective risk management and oversight to function optimally. Fairly offers a continuous monitoring system designed for robust model governance and oversight. This platform facilitates seamless collaboration between risk and compliance teams alongside data science and cyber security professionals, ensuring that models maintain reliability and security standards. Fairly provides a straightforward approach to staying current with policies and regulations related to the procurement, validation, and auditing of non-AI, predictive AI, and generative AI models. The model validation and auditing process is streamlined by Fairly, which grants direct access to ground truth in a controlled environment for both in-house and third-party models, all while minimizing additional burdens on development and IT teams. This ensures that Fairly's platform not only promotes compliance but also fosters secure and ethical modeling practices. Furthermore, Fairly empowers teams to effectively identify, assess, and monitor risks while also reporting and mitigating compliance, operational, and model-related risks in alignment with both internal policies and external regulations. By incorporating these features, Fairly reinforces its commitment to maintaining high standards of model integrity and accountability.

Superagent is an open-source platform focused on AI safety and agent development, designed to assist developers and organizations in creating, deploying, and safeguarding AI-driven applications and assistants by incorporating essential safety measures, runtime security, and compliance controls into their agent workflows. It features purpose-trained models and APIs—such as Guard, Verify, and Redact—that effectively prevent prompt injections, malicious tool usage, data leaks, and unsafe outputs in real-time, while red-teaming tests evaluate production systems for vulnerabilities and provide actionable remediation strategies. Superagent seamlessly integrates with current AI systems at both inference and tool-call levels, enabling it to filter inputs and outputs, eliminate sensitive information like personally identifiable information (PII) and protected health information (PHI), enforce policy constraints, and prevent unauthorized actions before they can take place. Furthermore, it enhances security and engineering operations by offering comprehensive observability, live trace logs, policy controls, and detailed audit trails, ensuring that teams can maintain robust oversight of their AI systems at all times. Ultimately, Superagent empowers organizations to navigate the complexities of AI safety while facilitating the responsible use of innovative technologies.

Lanai serves as an AI empowerment platform aimed at assisting enterprises in effectively navigating the challenges associated with AI adoption by offering insights into AI interactions, protecting confidential data, and expediting successful AI projects. It encompasses features such as AI visibility to help uncover prompt interactions across various applications and teams, risk monitoring to ensure compliance and detect potential vulnerabilities, and progress tracking to evaluate adoption relative to strategic objectives. Furthermore, Lanai equips users with policy intelligence and guardrails to proactively protect sensitive data and maintain compliance, along with in-context protection and guidance that facilitates proper query routing while preserving document integrity. To further enhance AI interactions, the platform provides smart prompt coaching for immediate assistance, tailored insights into leading use cases and applications, and comprehensive reports for both managers and users, thereby promoting enterprise adoption and maximizing return on investment. Ultimately, Lanai aims to create a seamless bridge between AI capabilities and enterprise needs, fostering a culture of innovation and efficiency within organizations.

OneTrust offers a comprehensive Data & AI Governance solution that integrates various insights from data, metadata, models, and risk assessments to create and implement effective policies for data and artificial intelligence. This platform not only streamlines the approval process for data products and AI systems, thereby fostering faster innovation, but also ensures business continuity through ongoing surveillance of these systems, which helps maintain regulatory adherence and manage risks efficiently while minimizing application downtime. By centralizing the definition and enforcement of data policies, it simplifies compliance measures for organizations. Additionally, the solution includes essential features such as consistent scanning, classification, and tagging of sensitive data, which guarantee the effective implementation of data governance across both structured and unstructured data sources. Furthermore, it reinforces responsible data utilization by establishing role-based access controls within a strong governance framework, ultimately enhancing the overall integrity and oversight of data practices.

The AGAT Secure AI Platform is an AI solution that prioritizes security, offering robust generative AI features tailored for enterprise needs while maintaining strict data protection and governance standards. It can be deployed in various settings, including on-premises environments that are completely isolated, or through cloud services, facilitating scenarios where data exposure is minimized and enabling comprehensive control for enterprises. This platform includes two key components: an AI Suite and an AI Firewall. The AI Suite provides a private AI ecosystem featuring various modules, such as a knowledge assistant that retrieves answers from internal data, a data-analysis agent that performs natural language analytics on spreadsheets and databases, a smart search tool for meaning-based content discovery, an AI code assistant for code completion, generation, and error detection, as well as AI agents capable of planning and executing tasks through file modifications and internet searches. Meanwhile, the AI Firewall functions as a real-time proxy for public AI services, implementing risk-based policies and additional security measures, thus ensuring that organizations can leverage AI safely while adhering to their governance frameworks. Overall, AGAT Secure AI Platform stands out for its commitment to security without sacrificing the innovative capabilities of generative AI.

Cisco AI Defense represents an all-encompassing security framework aimed at empowering businesses to securely create, implement, and leverage AI technologies. It effectively tackles significant security issues like shadow AI, which refers to the unauthorized utilization of third-party generative AI applications, alongside enhancing application security by ensuring comprehensive visibility into AI resources and instituting controls to avert data breaches and reduce potential threats. Among its principal features are AI Access, which allows for the management of third-party AI applications; AI Model and Application Validation, which performs automated assessments for vulnerabilities; AI Runtime Protection, which provides real-time safeguards against adversarial threats; and AI Cloud Visibility, which catalogs AI models and data sources across various distributed settings. By harnessing Cisco's capabilities in network-layer visibility and ongoing threat intelligence enhancements, AI Defense guarantees strong defense against the continuously changing risks associated with AI technology, thus fostering a safer environment for innovation and growth. Moreover, this solution not only protects existing assets but also promotes a proactive approach to identifying and mitigating future threats.

Alice is an enterprise-grade AI security and trust platform designed to protect applications, agents, and foundation models from adversarial threats. Formerly known as ActiveFence, the company leverages its proprietary Rabbit Hole intelligence engine, built on billions of real-world toxic and abusive data samples, to deliver unmatched safety coverage. Alice protects more than 50% of global online experiences, monitoring over 1 billion daily AI-human interactions across 120+ languages. Its WonderSuite platform provides comprehensive safeguards, including pre-launch stress testing with WonderBuild, dynamic runtime guardrails through WonderFence, and continuous automated red-teaming via WonderCheck. These solutions help organizations defend against prompt injection, jailbreaks, model exploitation, and policy misalignment risks. By aligning defenses with regulatory and compliance requirements, Alice supports responsible AI governance and enterprise risk management. Trusted by leading tech companies and model labs, Alice empowers businesses to deploy GenAI systems securely and scale innovation without fear.

Swifter oversees artificial intelligence throughout the entire software development lifecycle. In contrast to code-centric assistants that offer approximately 10% productivity improvements, Swifter's specification-driven agents encompass all phases of the SDLC—from gathering business requirements to design, code generation, testing, and final delivery—resulting in productivity increases of 25-30%. Tailored for enterprises, it ensures complete traceability from initial requirements to the final code, while also providing audit trails, enforcing compliance, and guaranteeing uniform output across numerous developers. Additionally, it accommodates both greenfield projects and the modernization of legacy systems. The platform has established a partnership with Tech Mahindra, serving over 1,100 enterprise clients and enhancing their software development processes. This comprehensive approach not only boosts productivity but also helps maintain high standards of quality and compliance.

AgentMonk is a sophisticated AI-driven platform designed for customer engagement and automation, empowering businesses to create, deploy, and oversee a range of AI agents that are capable of perceiving, deciding, and acting within customer workflows to enhance attraction, interaction, conversion, and retention through tailored experiences that leverage comprehensive customer insights. The platform offers both pre-built and customizable AI agents focused on various functions such as sales, support, reporting, and segmentation, alongside a user-friendly no-code agent builder and automated workflows that streamline intricate tasks while integrating customer data, segmentation, journey orchestration, and omnichannel communication (including Web, WhatsApp, Instagram, voice, and email) into a single, comprehensive toolkit. Additionally, AgentMonk boasts enterprise-level features like stringent guardrails, workflow monitoring, performance analytics, and robust security and compliance protocols, allowing teams to rigorously test, monitor, and refine AI agent interactions to ensure superior quality engagements. Ultimately, this platform is designed to enhance efficiency and drive better outcomes for businesses, making it an essential tool in the evolving landscape of customer engagement technology.