Alternatives to Notenic

StackAI is an enterprise AI automation platform that allows organizations to build end-to-end internal tools and processes with AI agents. It ensures every workflow is secure, compliant, and governed, so teams can automate complex processes without heavy engineering. With a visual workflow builder and multi-agent orchestration, StackAI enables full automation from knowledge retrieval to approvals and reporting. Enterprise data sources like SharePoint, Confluence, Notion, Google Drive, and internal databases can be connected with versioning, citations, and access controls to protect sensitive information. AI agents can be deployed as chat assistants, advanced forms, or APIs integrated into Slack, Teams, Salesforce, HubSpot, ServiceNow, or custom apps. Security is built in with SSO (Okta, Azure AD, Google), RBAC, audit logs, PII masking, and data residency. Analytics and cost governance let teams track performance, while evaluations and guardrails ensure reliability before production. StackAI also offers model flexibility, routing tasks across OpenAI, Anthropic, Google, or local LLMs with fine-grained controls for accuracy. A template library accelerates adoption with ready-to-use workflows like Contract Analyzer, Support Desk AI Assistant, RFP Response Builder, and Investment Memo Generator. By consolidating fragmented processes into secure, AI-powered workflows, StackAI reduces manual work, speeds decision-making, and empowers teams to build trusted automation at scale.

Cognigy.AI is an enterprise-grade conversational AI platform designed to automate customer interactions across various channels, including voice and chat. Leveraging advanced natural language understanding (NLU) and large language models (LLMs), it enables businesses to create intelligent AI agents capable of delivering personalized, human-like conversations. The platform offers robust integration capabilities, allowing seamless connectivity with existing contact center and CRM systems to enhance customer experience orchestration. With features like Agentic AI, Cognigy.AI introduces autonomous, goal-oriented agents that can think, adapt, and collaborate with both AI and human agents, navigating complex queries with flexibility and precision. This comprehensive solution empowers organizations to streamline customer service operations, improve engagement, and achieve higher efficiency in handling customer inquiries.

Camunda helps organizations coordinate and automate processes involving people, systems, and devices—removing complexity, improving efficiency, and making AI workflows operational. Designed for both business and IT teams, Camunda’s platform runs any process with the speed and scale needed to stay competitive while meeting security and governance standards. More than 700 companies, including Atlassian, ING, and Vodafone, use Camunda to design, automate, and optimize core business processes. Learn more at camunda.com.

The Teradata Enterprise AgentStack is a comprehensive platform designed for the development, deployment, and management of enterprise-level autonomous AI agents that seamlessly connect to reliable data and analytics, aiding businesses in transitioning from experimentation phases to fully operational agentic AI with robust enterprise control. This platform consolidates diverse functionalities to facilitate the entire agent lifecycle; AgentBuilder streamlines the process of creating intelligent agents through both no-code and pro-code tools that are compatible with Teradata Vantage and various open-source frameworks. Furthermore, the Enterprise MCP provides secure, context-rich access to well-governed enterprise data along with tailored prompts that enhance agent intelligence. Meanwhile, AgentEngine ensures scalable agent execution while maintaining consistent memory and reliability across various hybrid environments. Additionally, AgentOps plays a crucial role in centralizing the monitoring, governance, compliance, auditability, and policy enforcement, ensuring that the agents operate within established parameters, which ultimately leads to increased efficiency and adherence to organizational standards. Collectively, these features empower organizations to harness the full potential of autonomous AI in a controlled and efficient manner.

Transform your organization into a fully automated enterprise™ with the UiPath Platform, a hallmark of digital transformation. Achieving a fully automated enterprise fosters business resilience, enhances speed and agility, and liberates employees from repetitive tasks through a comprehensive automation solution. Leverage the insights gathered from your business applications, such as ERP and CRM systems, to gain a profound understanding of intricate business operations. This knowledge empowers you to identify the most effective automation opportunities and measure their impact. As a cutting-edge Robotic Process Automation (RPA) and process mining platform, UiPath enables organizations to streamline their business processes, accelerating their journey towards becoming digital entities while gaining a competitive edge in the realm of AI. With its scalable, extensible, and sustainable architecture, UiPath allows users to create visual workflows without the need for scripting or coding. Additionally, the platform boasts robust auditing features, sophisticated analytical reporting, and personalized dashboards to enhance user experience and operational oversight. Embrace UiPath to not only improve efficiency but also to foster a culture of innovation within your organization.

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.

UiPath Agentic Orchestration serves as the orchestration framework of the UiPath Platform, facilitating the integration and coordination of AI agents, robotic processes, APIs, workflows, and human involvement to carry out intricate, extended enterprise processes from start to finish with oversight, transparency, and ongoing enhancement. This platform transcends conventional automation by merging generative AI agents with RPA bots and human contributions, all within well-defined workflows, which fosters real-time collaboration, adaptive decision-making, and proactive solutions to challenges throughout both structured and unstructured data environments. Furthermore, it offers comprehensive orchestration, process modeling—including BPMN standards—along with seamless integration with external systems and robust monitoring capabilities, thereby allowing organizations to track operations, handle exceptions, and pursue continuous improvement through data-driven analytics. Enhanced by built-in governance, compliance mechanisms, and analytical tools, Agentic Orchestration streamlines the management of widespread automation while guaranteeing dependable performance. Its innovative approach not only boosts efficiency but also empowers organizations to adapt swiftly to changing market demands and operational challenges.

Peta serves as an advanced control plane for the Model Context Protocol (MCP), streamlining, securing, governing, and overseeing how AI clients and agents interact with external tools, data, and APIs. This platform integrates a zero-trust MCP gateway, a secure vault, a managed runtime environment, a policy engine, human-in-the-loop approvals, and comprehensive audit logging into a cohesive solution, enabling organizations to implement nuanced access controls, safeguard raw credentials, and monitor all tool interactions conducted by AI systems. At the heart of Peta is Peta Core, which functions as both a secure vault and gateway, encrypting credentials, generating short-lived service tokens, verifying identity and compliance with policies for each request, managing the MCP server lifecycle through lazy loading and auto-recovery, and injecting credentials during runtime without revealing them to agents. Additionally, the Peta Console empowers teams to specify which users or agents can access particular MCP tools within designated environments, establish approval protocols, manage tokens, and review usage statistics and associated costs. This multifaceted approach not only enhances security but also fosters efficient resource management and accountability within AI operations.

Sapiom serves as a financial and access infrastructure platform that allows AI agents and API-driven applications to securely access, provision, and pay for various third-party services, APIs, tools, and compute resources in real-time, eliminating the need for manual onboarding, individual management of API keys, and the necessity of pre-purchased credits. It features a centralized dashboard that enables organizations to keep track of overall spending, agent activities, service utilization, and real-time analytics, while also allowing the establishment of rule-based spending and usage limits, alongside the enforcement of governance policies to ensure that autonomous agents operate securely within set financial boundaries. Additionally, Sapiom offers SDKs and APIs that empower developers to link agents to a selective network of services, including verification processes, web searching, AI models through OpenRouter, and automation of image/audio generation and browser tasks, facilitating automated authentication and micro-payments for each use. This system meticulously tracks every API invocation, associated costs, and execution traces, ensuring comprehensive visibility and control over operations, which ultimately enhances the operational efficiency of organizations leveraging its capabilities.

Microsoft Copilot Studio is a powerful and flexible platform designed to help users create, customize, and manage AI-driven agents tailored to meet diverse business needs. Combining the simplicity of low-code development with the advanced capabilities of generative AI, the platform enables users to design intelligent agents that can access and utilize internal knowledge bases, perform complex actions through a wide range of data connectors, and operate autonomously to streamline processes and improve productivity. These AI agents can be seamlessly integrated into existing workflows and deployed across various channels, including Microsoft 365 applications, internal websites, and mobile apps, ensuring they adapt to the unique operational environments of any organization. Furthermore, Copilot Studio includes a robust suite of governance and management tools, allowing IT teams to maintain centralized control over agent usage, monitor performance with detailed analytics, and enforce security policies. This combination of ease of use, advanced functionality, and comprehensive governance makes Microsoft Copilot Studio an invaluable tool for organizations looking to leverage AI to transform their business operations.

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.

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.

AI Hive is a comprehensive enterprise AI agent platform built to help organizations deploy and manage intelligent automation at scale. The platform enables businesses to design, orchestrate, and govern AI agents that operate across multiple systems, workflows, and data environments. AI Hive focuses on solving a common enterprise challenge where many companies experiment with AI but struggle to move beyond small proof-of-concept projects. With built-in governance, compliance controls, and scalable infrastructure, the platform ensures that AI deployments remain secure, controlled, and aligned with organizational policies. The AI Hive marketplace provides access to a growing library of ready-made AI agents designed for specific business functions and industries. These agents can perform tasks such as contract review, compliance monitoring, loan assessments, patient triage, and supply chain analysis. Organizations can deploy these agents quickly while also customizing them to match their internal processes. The platform integrates with enterprise tools, databases, and analytics systems to ensure seamless data flow and automation across the organization. AI Hive is model-agnostic, allowing companies to use different AI models without vendor lock-in. By combining AI orchestration, governance, and a modular marketplace of agents, AI Hive helps businesses turn AI initiatives into scalable, production-ready solutions that deliver real operational value.

Zapper Edge is a cloud-native, enterprise-grade Managed File Transfer (MFT) solution crafted to facilitate secure, compliant, and efficient file transfers among partners, vendors, and applications. Functioning as the command center for file management, it upholds zero-trust security principles, implements role-based access control (RBAC) with a defense-in-depth strategy, and incorporates single sign-on (SSO), PGP encryption, customer-managed keys (CMK), and governance based on policies. The platform is equipped to handle Data Lifecycle Management and Data Loss Protection, allowing users to upload, download, preview, delete files, and perform bulk operations while ensuring detailed access control and immutable audit trails. Additionally, it features SIEM-enabled incident reporting and real-time monitoring capabilities, which provide essential visibility for swift detection, investigation, and compliance documentation. Designed with Azure in mind, Zapper Edge boasts rapid performance, the ability to scale horizontally, effortless deployment, and integrated data residency controls. Moreover, it includes an AI Agent Orchestration layer that supports governed API-based data access and features a RAG Foundry, facilitating the creation of micro-level, sanctioned data subsets for secure and efficient retrieval. This comprehensive suite of tools makes Zapper Edge a robust choice for organizations seeking to enhance their file transfer security and operational efficiency.

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.

Emergence Orchestrator functions as an independent meta-agent that manages and synchronizes the interactions of AI agents within enterprise systems. This innovative tool allows various autonomous agents to collaborate effortlessly, handling complex workflows that involve both contemporary and legacy software systems. By utilizing the Orchestrator, businesses can efficiently oversee and coordinate numerous autonomous agents in real-time across a multitude of sectors, enabling applications such as supply chain optimization, quality assurance testing, research analysis, and travel logistics. It effectively manages essential tasks including workflow organization, compliance adherence, data protection, and system integration, allowing teams to concentrate on higher-level strategic objectives. Among its notable features are dynamic workflow orchestration, efficient task assignment, direct agent-to-agent communication, an extensive agent registry that maintains a catalog of agents, a specialized skills library that enhances task performance, and flexible compliance frameworks tailored to specific needs. Additionally, this tool significantly reduces operational overhead, enhancing overall productivity within enterprises.

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. DFM replaces fragmented UIs, brittle scripts, and reactive operations with centralized, AI-driven control, enabling NiFi teams to transition from manual operations to governed, autonomous execution.

Crewship is a platform designed specifically for developers to facilitate the deployment of AI agent workflows. With just a single command, you can deploy your CrewAI, LangGraph, and LangGraph.js agents, allowing you to observe their execution live. Essential features encompass one-command deployment, real-time execution streaming, management of artifacts, auto-scaling capabilities, version control, and secure secrets management. By taking care of the infrastructure, Crewship enables developers to concentrate on creating exceptional AI agents. Additionally, it will soon offer multi-framework support, integrating tools such as AutoGen, Pydantic AI, smolagents, OpenAI Agents, Mastra, and Agno, enhancing its versatility and appeal. This comprehensive approach ensures that developers have all the resources needed for efficient and effective AI development at their fingertips.

Oz serves as a cloud-centered orchestration platform tailored for AI coding agents, empowering developers and teams to effortlessly execute, oversee, automate, and expand an unlimited number of parallel cloud coding agents without the need for custom infrastructure. This platform offers programmable, auditable workflows that streamline repetitive development tasks and intricate code modifications, ensuring full control over the process. Users can initiate agents through various interfaces including the CLI, web application, APIs, SDKs, Warp Terminal, or mobile devices. Additionally, Oz allows for the orchestration of numerous agents simultaneously, complete with integrated audit trails, session tracking, and comprehensive visibility, and provides the capability to monitor or engage with active agents within a shared control environment. The platform also accommodates flexible hosting options, whether on your own infrastructure or Warp's, while ensuring that each agent operates within secure, isolated environments. Oz produces tangible artifacts such as plans and pull requests, and is adept at managing multi-repo alterations, allowing agents to effectively synchronize extensive updates across vast codebases. With its robust features, Oz significantly enhances the efficiency of software development processes, making it an indispensable tool for modern development teams.

ServiceNow's AI Agents are self-sufficient systems integrated into the Now Platform, aimed at executing repetitive tasks that were once managed by human workers. These agents engage with their surroundings to gather information, make informed decisions, and carry out tasks, leading to improved efficiency over time. By utilizing specialized large language models along with a powerful reasoning engine, they gain a comprehensive understanding of various business contexts, which fosters ongoing enhancements in performance. Functioning natively across diverse workflows and data platforms, AI Agents promote complete automation, thereby increasing team productivity by coordinating workflows, integrations, and actions within the organization. Companies have the option to implement pre-existing AI agents or create personalized ones to meet their unique requirements, all while operating smoothly on the Now Platform. This seamless integration not only streamlines processes but also enables employees to devote their attention to more strategic initiatives by relieving them of mundane tasks, ultimately driving innovation and growth within the organization. As a result, the implementation of AI Agents represents a significant step towards transforming workplace efficiency.

OpenAI Frontier is an innovative platform designed for enterprises that facilitates the creation, deployment, management, and orchestration of numerous AI agents capable of executing practical tasks within established systems, workflows, and data environments. This unified framework enables organizations to seamlessly integrate AI agents, whether developed by OpenAI or external parties, with their internal tools such as CRM systems, data warehouses, and ticketing applications, ensuring that these agents operate with a shared context, permissions, memory, and oversight to effectively handle business-critical tasks. Frontier aims to transition AI agents from isolated experimental phases into fully operational production environments by offering features such as shared business context, governance controls, streamlined onboarding processes, observability, and secure access boundaries. In doing so, it empowers companies to centralize and expand their intelligent automation capabilities in a manner analogous to how human resources systems manage workforce operations, ultimately enhancing efficiency and productivity across the organization. By leveraging such a comprehensive approach, businesses can ensure that their AI agents are not only effective but also aligned with their strategic objectives.

VoltusWave is an advanced platform for enterprise AI agent workforces that transcends the limitations of standalone automation tools by integrating intelligent agents within a comprehensive execution framework capable of managing end-to-end business processes. This platform offers a cohesive environment where AI agents can interpret documents, make informed decisions, carry out workflows, and address exceptions, all while ensuring full audit trails and human intervention capabilities are in place. It operates through six interconnected engines, which include process orchestration, rules enforcement, document generation, integration infrastructure, no-code application development, and a regulated AI agent workforce, empowering organizations to efficiently manage intricate operations like procure-to-pay or enterprise-to-cash cycles with minimal human input. These AI agents function across all operational layers, dealing with tasks related to documents, approvals, reconciliations, compliance verification, and customer communications, while a robust rules engine guarantees that every action adheres to established guidelines with complete version control and traceability. This holistic approach not only streamlines processes but also enhances overall efficiency and accountability within the organization.

HiClaw is a multi-agent operating system that is open source and operates on the Matrix framework, allowing various AI agents to work together within Matrix rooms, where their activities are fully accessible to humans in real-time. The system features a Manager Agent that oversees multiple Worker Agents, efficiently breaking down complex tasks and facilitating simultaneous execution, which enhances the management of these intricate operations. Designed with a focus on enterprise-level security and collaborative capabilities, HiClaw utilizes the open Matrix instant messaging protocol, ensuring that all communications between agents are transparent, easily auditable, and fit for distributed systems and federated environments. Humans have the ability to join any Matrix room whenever they wish, which allows them to monitor agent discussions, intervene as necessary, or adjust agent actions in real-time, thereby safeguarding oversight and control. This structured two-tier system, consisting of Manager and Worker Agents, delineates clear responsibilities for each agent, simplifying the process of integrating custom Worker Agents tailored for various applications, while also promoting adaptability within the architecture. Consequently, the design of HiClaw not only enhances operational efficiency but also paves the way for innovative uses of AI collaboration across diverse scenarios.

Orchestrating actions enables the creation of intricate backend agents that can perform multiple tasks seamlessly. Compatible with all LLMs, you can design a completely tailored user interface for your agent without needing to code, all hosted on your own domain. Monitor each phase of your agent’s process, capturing every detail to manage the unpredictable behavior of LLMs effectively. Implement precise access controls for your application, data, and the agent itself. Utilize a specially fine-tuned model designed to expedite the software development process significantly. Additionally, the system automatically manages aspects like concurrency, rate limiting, and various other functionalities to enhance performance and reliability. This comprehensive approach ensures that users can focus on their core objectives while the underlying complexities are handled efficiently.

Break the invisible barriers between systems, apps, and data. Meet the agentic automation platform that makes quick work of your most complex processes. Make getting things done look easy—because it is. Orchestrate your most complex, critical processes across systems and teams, leaving app and data silos in the dust. Drive every process at maximum speed. Set up and apply AI + automation wherever your teams work with simple-to-use tools and expert support. Get peace of mind and automate with AI in any context, no matter how complex, with full security and governance controls. Get right-size support every step of the way. Start with do-it-yourself training, community expertise from 1M+ automation professionals, and a global partner ecosystem.

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.

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.

Thread AI's Lemma is an advanced AI orchestration platform designed for organizations to seamlessly construct, connect, and oversee secure, scalable AI-driven workflows and agents, thereby facilitating the automation of intricate, critical processes without the need to rebuild existing infrastructure. The platform offers user-friendly interfaces, low-code components, software development kits (SDKs), and application programming interfaces (APIs) tailored for engineering teams, along with centralized monitoring and traceability for all workflows, allowing users to easily create reusable AI “Workers” that blend models, functions, and data from both structured and unstructured sources. With a strong focus on security and compliance, Lemma implements enterprise-grade protections including AES-256 encryption for data at rest, TLS for data in transit, governance controls, and customizable workflow guardrails to ensure sensitive data is managed appropriately, while also accommodating both cloud and on-premise deployments alongside automatic vulnerability assessments. Furthermore, the platform supports human-in-the-loop monitoring, offers dynamic and non-deterministic execution pathways, ensures fallback resilience, and enhances overall observability, making it a comprehensive solution for modern AI application needs. This multifaceted approach not only streamlines the development process but also enhances the overall reliability and security of AI implementations.

Origon serves as a comprehensive platform for developing and managing full-stack AI agents, designed as a cohesive "Agentic Operating System" that facilitates every phase of autonomous AI systems, from initial design through deployment and monitoring. It features a user-friendly Studio that allows for visual agent creation via drag-and-drop functionality, alongside Sessions that enable real-time observation, behavior tracking, and debugging, while Insights dashboards provide centralized performance analytics, reliability monitoring, and outcome evaluation. Operating natively on specialized infrastructure tailored for optimal low-latency performance and enhanced security, Origon eliminates reliance on external cloud APIs and includes an integrated knowledge engine that links agents to contextual memory and domain-specific data, ensuring that their responses remain grounded and coherent. The platform supports a wide array of connectors and APIs, such as chat, voice, WhatsApp, SMS, email, and telephony, empowering agents to execute code and interact seamlessly with real-world systems at the click of a button. Additionally, the versatility of Origon allows businesses to customize their AI agents further, catering to specific operational needs and enhancing overall efficiency.

Conductor allows you to manage a team of coding agents directly on your Mac, providing each Claude Code or Codex agent with its own distinct workspace to enable parallel software development while maintaining oversight. By integrating your repository, Conductor efficiently clones it and operates solely on your Mac. You can deploy multiple agents, each assigned a unique git worktree, allowing them to function autonomously. With Conductor, you can monitor agent activity, identify tasks that require attention, review code, and merge completed branches. This platform is designed under the concept that developers are evolving into AI managers, orchestrating various agents simultaneously rather than relying on a single chat interface. It accommodates Claude Code and Codex, featuring model selection, Plan Mode, Fast Mode, reasoning controls when applicable, checkpoints, specialized skills, and session controls tailored to individual agents. Additionally, Plan Mode encourages the agent to devise a strategy prior to file modifications, making it particularly advantageous for extensive, complex, or ambiguous changes spanning multiple files, enhancing the overall development process.

Agent2Agent (A2A) is a protocol designed to enable AI agents to communicate and collaborate efficiently. By providing a framework for agents to exchange knowledge, tasks, and data, A2A enhances the potential for multi-agent systems to work together and perform complex tasks autonomously. This protocol is crucial for the development of advanced AI ecosystems, as it supports smooth integration between different AI models and services, creating a more seamless user experience and efficient task management.

The Optimizely Opal platform integrates cutting-edge artificial intelligence into its Digital Experience Platform, empowering teams to create, enhance, and tailor digital experiences with reduced manual tasks and a greater strategic influence; central to this is Optimizely Opal, an AI-driven orchestration and assistance system that gathers context from various sources within Optimizely One and performs tasks within workflows instead of merely providing text responses, thus allowing teams to strategize campaigns, produce content, devise experimental ideas, evaluate outcomes, and make informed optimization choices using branded, context-sensitive AI agents. This AI functionality encompasses a wide array of areas, including content management, personalization, experimentation, analytics, and audience segmentation, enabling it to propose and automatically generate variations for experiments and testing plans, condense results into actionable insights, create customized digital content and messaging, and direct personalization efforts based on the immediate behaviors and preferences of customers. Moreover, the platform's robust AI capabilities not only simplify the process for teams but also drive more effective and engaging customer interactions.

Intent is a public beta desktop workspace tailored for specification-driven development and the orchestration of multiple agents, empowering developers to strategize, carry out, and refine intricate coding tasks through the collaboration of synchronized AI agents. Central to its workflow are dynamic specifications, which enable teams to articulate their project requirements while allowing the agents to carry out those tasks and continuously update the specifications to mirror the actual results. The platform offers a cohesive environment where various agents can operate simultaneously without causing conflicts, thereby removing the hassle of managing multiple terminals, branches, or dispersed prompts. Enhanced by Augment’s Context Engine, each agent possesses a comprehensive understanding of the entire codebase, which guarantees coherence across the planning, execution, and verification phases. Intent is compatible with leading-edge models and provides flexibility for developers to select and combine them according to the complexity of their tasks, whether it’s for designing architecture, executing rapid iterations, or conducting in-depth code analysis. By streamlining these processes, Intent aims to enhance productivity and collaboration within development teams.

Snapper serves as a comprehensive security platform for AI agents, aimed at ensuring thorough governance and protection for organizations that utilize AI across various applications, networks, and systems. It implements runtime enforcement by scrutinizing every action an agent takes, such as tool interactions, API calls, and data access requests, prior to execution, utilizing a multi-layered policy-driven rule engine. Additionally, Snapper provides a holistic view of AI activity by analyzing network traffic, browser usage, DNS queries, and running processes to uncover unauthorized tools and hidden AI applications. It also proactively intercepts outgoing large language model requests via SDK wrappers and a network proxy, allowing it to assess, redact, and document sensitive information in real time. Enhancing its security features, Snapper possesses sophisticated threat detection mechanisms that can recognize prompt injection tactics, exploit chains, unusual behaviors, and complex attack patterns, leveraging behavioral baselines, kill chain analysis, and a composite trust scoring system for robust protection. Ultimately, Snapper represents a critical asset for organizations seeking to navigate the risks associated with AI deployment while maintaining operational integrity.

IndyKite serves as a specialized context graph designed to provide real-time trust, oversight, and clarity for both applications and AI technologies. By converting various signals into immediate enforcement contexts, it evaluates access permissions at the point of usage, answering critical questions about who or what can access specific data, under which circumstances, and the rationale behind it. This innovative platform consolidates identity, metadata, provenance, and policies into a cohesive operational context engine, allowing applications and AI systems to function effectively without the need to navigate through fragmented IAM systems, catalogs, MDM, security tools, code, and documentation. Moreover, IndyKite integrates identity, data, and policy into a unified model, ensuring that controls are applicable to humans, machines, and AI alike. Its Identity Knowledge Graph accurately depicts users, applications, machines, data types, and their interconnections, ultimately creating a comprehensive data model that encompasses both personal and non-personal entities. This robust framework lays the groundwork for intelligent and predictive access control, enriched with contextual insights, facilitating enhanced decision-making across diverse scenarios. By ensuring that all elements of identity and access management are interconnected, IndyKite enhances the overall security and efficiency of AI-driven applications.

Straiker is an innovative security platform designed exclusively for safeguarding enterprise AI applications and autonomous agents, particularly addressing the emerging hazards posed by “agentic AI” systems that engage with various tools, APIs, and sensitive data. By offering comprehensive visibility and control throughout the entire AI stack, it analyzes behavioral signals from models, prompts, tools, identities, and infrastructure, which facilitates the immediate detection and prevention of AI-specific threats, including prompt injection, privilege escalation, data exfiltration, and the misuse of tools. The platform integrates continuous discovery, adversarial testing, and runtime protection through essential components such as Discover AI, Ascend AI, and Defend AI, working in harmony to identify all active agents, simulate potential attacks to reveal weaknesses, and implement real-time protective measures during operation. Its intricate, multi-layered architecture captures profound contextual signals from user interactions, network activities, and agent workflows, ensuring a robust defense against evolving threats. As AI technologies continue to advance, the necessity for such tailored security solutions will become increasingly critical for enterprises navigating this complex landscape.

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.

CosmOS is an innovative operating system centered on artificial intelligence and serves as an intelligent orchestration platform that was initially created by Humane and is being further developed by HP IQ, the AI innovation division of HP dedicated to infusing contextual intelligence into various devices. In contrast to conventional operating systems that depend on users to manually manage app workflows, CosmOS is designed around a network of specialized AI agents, complemented by an “AI Bus” orchestration layer that facilitates the seamless flow of information between hardware, models, and services, enabling the system to predict user needs, carry out complex tasks, and provide contextual support without requiring users to open separate applications. Additionally, it supports a variety of interaction modes including voice, text, vision, gesture, and touch, which allows for a more intuitive and fluid user experience while the system continuously learns from user behavior to tailor its responses and evolve over time. This sophisticated approach aims to redefine how users engage with technology, making it more responsive and user-friendly.

Proofpoint AI Security is an integrated solution aimed at assisting organizations in managing, monitoring, and safeguarding the deployment of AI technologies, including large language models and autonomous agents. This platform offers insight into both approved and unapproved AI activities, allowing security teams to identify unauthorized AI tools, track prompts and responses, and analyze AI interactions with sensitive information in real-time. By utilizing intent-based detection and behavioral analysis, it effectively spots anomalies, attempts at prompt injections, and potentially dangerous interactions, while simultaneously enforcing policies during operation to avert data breaches and misuse. Furthermore, it reconstructs comprehensive AI transactions from the initial user query to the actions and results produced by the agents, ensuring organizations maintain complete traceability and are prepared for audits. With its capabilities extending to endpoints, web browsers, and AI agent connections, it facilitates detailed access governance, guaranteeing that AI systems are restricted to utilizing and sharing only the necessary information. This comprehensive control enhances the overall security posture of the enterprise as it navigates the complexities of AI system integration.

Calljmp is a developer-first AI runtime for building and running long-lived, stateful agent workflows in production. Unlike AI agent frameworks that focus mainly on authoring logic in code, Calljmp provides a managed runtime that handles execution concerns by default. This includes durable state persistence, pause and resume for human-in-the-loop workflows, safe retries with idempotency, and built-in observability across every step of an agent’s execution. Calljmp is designed for teams using TypeScript who want to ship production-grade AI systems without stitching together queues, databases, custom state machines, and monitoring infrastructure. Developers write agent workflows as code, while the runtime guarantees reliable execution over time, even across crashes, restarts, and long waits. Calljmp targets the gap between developer-first agent frameworks and heavy workflow engines, offering a practical path from prototype to production for real-world AI agents.

HPE Aruba Networking ClearPass Policy Manager enhances network security by implementing policies aligned with Zero Trust principles, which are essential for supporting initiatives in hybrid workplaces, IoT devices, and the connected edge. It streamlines access for legitimate users and devices through least-privilege controls, thereby safeguarding visitors, partners, customers, and employees across Wi-Fi, wired, and WAN networks, complemented by features like integrated guest portals and device configuration monitoring that adhere to SASE-oriented Zero Trust security. By integrating Zero Trust security measures, IT teams are equipped to create and enforce reliable, role-based policies that apply enterprise-wide, ensuring a robust approach to Zero Trust implementation. The extensive partner ecosystem facilitates smooth integration with existing security solutions, while dynamic, identity-driven traffic segmentation guarantees consistent protection throughout various network environments. Moreover, HPE Aruba Networking ClearPass Policy Manager empowers security teams to effectively authenticate, authorize, and enforce secure access to the network, utilizing role-based and Zero Trust policies to maintain a high level of security across all operations. This comprehensive solution not only enhances security but also fosters a more efficient and manageable network environment.

Draftt is an innovative governance software designed to proactively manage tech stacks by continuously overseeing the lifecycle and configuration of every component across various environments, including clouds, workloads, and code. This solution empowers teams to stay ahead of potential technical debt and mitigates the risks associated with unforeseen end-of-life scenarios. Offering comprehensive visibility, Draftt features a consolidated control plane that visually organizes all technologies, their versions, dependencies, and Kubernetes clusters, effectively replacing outdated manual audits and static spreadsheets with a dynamic inventory and context. Utilizing secure, read-only integrations with cloud platforms and developer tools, it gathers lifecycle metadata, identifies version discrepancies, and uncovers compatibility issues early on. With its AI-enhanced prioritization and impact assessment capabilities, Draftt brings attention to upgrade risks by evaluating urgency, effort, and business significance, while also generating in-depth remediation plans customized to fit specific environments. Furthermore, it provides well-structured, step-by-step upgrade pathways, complete with prebuilt actions and automated workflows that can be seamlessly executed within the Draftt interface, thereby streamlining the upgrade process for teams. By integrating these features, Draftt not only simplifies governance but also enhances operational efficiency and reduces the likelihood of technical pitfalls.

Thenvoi serves as a collaborative platform for multiple coding agents, allowing them to work together seamlessly within a unified development environment, thus removing the necessity for developers to manually manage the interactions between various AI tools. Often, developers utilize several coding agents at once—one for system architecture, another for implementation, and yet another for making quick modifications—but maintaining synchronization among them usually demands ongoing copying, pasting, and context management. By providing a shared workspace where agents can access the same repository, files, and communication channels, Thenvoi alleviates these challenges, enabling agents to coordinate and communicate independently. Each agent connects to the platform and engages in discussions through a common chat interface while also interacting with a mounted codebase and workspace directories that encompass plans, reviews, and the overall status of the project. This innovative approach not only streamlines the development process but also enhances the efficiency of collaborative coding efforts.

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.

Gentoro is a comprehensive platform designed to enable enterprises to effectively harness agentic automation by seamlessly integrating AI agents with existing real-world systems in a secure and scalable manner. It operates on the Model Context Protocol (MCP), which empowers developers to effortlessly transform OpenAPI specifications or backend endpoints into production-ready MCP Tools, eliminating the need for manual integration coding. The platform efficiently addresses runtime challenges such as logging, retries, monitoring, and cost management, while simultaneously ensuring secure access, audit trails, and governance policies, including OAuth support and policy enforcement, regardless of whether it is deployed in a private cloud or an on-premises environment. Notably, Gentoro is model- and framework-agnostic, allowing for flexibility in integrating various large language models (LLMs) and agent architectures. This versatility aids in preventing vendor lock-in and streamlines the orchestration of tools within enterprise settings, as it manages tool generation, runtime operations, security measures, and ongoing maintenance all within a single integrated stack. By providing a unified solution, Gentoro enhances operational efficiency and simplifies the journey toward automation for businesses.