Alternatives to Covasant SERAA

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.

Customer experience shouldn't run on disconnected tools and static scripts. Dialpad Contact Center brings voice, digital channels, and human agents together in a single AI-native platform, built to act — not just record — on every customer interaction. This is Agentic AI in practice: agents that reason through a problem, take the next step, and drive it to resolution without waiting on a human to intervene. Where legacy systems leave data trapped in silos, Dialpad Contact Center closes that gap, linking voice and data so context travels with the customer instead of getting lost between systems. The payoff compounds. Dialpad has already generated over 775 million AI recaps, and each new interaction adds to a growing base of operational intelligence — sharper resolution paths, more productive agents, better outcomes quarter over quarter. None of it runs unchecked: Dialpad's Guardian layer keeps AI operations secure and governed, so intelligence scales without sacrificing oversight. In practice, that means up to 80% of issues get resolved autonomously, freeing your team to focus on the conversations that genuinely need a human. Intelligence works at the edge; people stay at the center of the experience. And you don't have to take the ROI on faith. Through Dialpad's Proving Ground, enterprises can validate performance and cost savings before rolling out at scale — a far more reliable path than betting on a brittle, rules-based bot.

NeuBird is the Agentic Operations Center: one secure link to your telemetry and LLMs that resolves incidents, remembers every investigation, and shares one governed truth across your teams and agents.

Retool is a modern AI-native application development platform designed to help teams build internal software quickly and efficiently. It enables users to create agents, workflows, dashboards, and full-stack apps using natural language prompts and visual tools. Retool connects directly to databases, APIs, vector stores, and AI models to ensure applications work seamlessly with existing systems. The platform allows teams to transform raw data into actionable tools such as dashboards, admin panels, and monitoring systems. With drag-and-drop UI building, code-level customization, and AI-assisted generation, Retool supports multiple development styles. Built-in workflows automate complex processes while maintaining auditability and security. Retool fits naturally into standard engineering stacks with support for CI/CD and version control. Enterprise-grade permissions and hosting options ensure sensitive data stays protected. Used by thousands of companies worldwide, Retool helps teams ship AI-powered software faster. It bridges the gap between idea and production with speed and control.

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.

Cortex AgentiX is an advanced AI agent orchestration platform from Palo Alto Networks that transforms how security teams automate and respond to threats. Built as the next generation of Cortex XSOAR®, it enables organizations to deploy AI agents that function as always-on digital teammates. These agents leverage billions of prior playbook executions to plan, reason, and execute complex security workflows with confidence. Cortex AgentiX provides flexibility through a comprehensive catalog of prebuilt agents as well as no-code tools for creating custom agents. The platform allows security leaders to define when agents operate autonomously and when human oversight is required. Strong access controls and permissions ensure agents follow the same governance rules as human analysts. Cortex AgentiX delivers complete transparency into agent behavior, eliminating black-box decision-making. Native support for natural language automation simplifies the creation of executable workflows. With over 1,000 prebuilt integrations, the platform connects easily to existing security tools. Cortex AgentiX helps organizations scale security operations while maintaining control, accountability, and compliance.

SERAA Cortex takes every agent from build to production and keeps watch once it is live, including agents built on Gemini Enterprise, Azure AI Foundry, AWS Bedrock and Databricks. Any agent can be stopped instantly.

Agent Control represents a groundbreaking open-source framework designed to manage the behavior of AI agents on a large scale, setting a new benchmark for governance in this domain. It addresses the issue of disjointed and hardcoded checks by providing teams with a unified governance layer that enforces regulations at each step, all managed from a single control interface that can be updated dynamically without altering the agent's underlying code. Developers can easily designate any function as governable by applying the control() decorator, thereby transforming key decision points within an agent into independently regulated control points, each equipped with its own governance policies. When a decorated function runs, Agent Control assesses the input or output against the prevailing policy and generates a response that could be to deny, steer, warn, log, or allow the action. If a denial occurs, the SDK triggers a ControlViolationError, preventing any unsafe actions from being executed. This separation of policies from the actual code empowers developers to strategically position control hooks, while policy teams determine the enforcement specifics of those hooks, ensuring a collaborative approach to governance. The flexibility and robustness of Agent Control make it an invaluable tool for organizations looking to standardize AI agent governance effectively.

Nimbus fosters collaboration by providing a unified platform where teams can communicate collectively, work alongside AI agents, streamline repetitive tasks, and enable executives to manage AI usage effectively. In this environment, discussions revolve around the work itself—covering briefs, files, and decisions—rather than relying on fragmented private chats that are difficult to piece together later. Teams and AI agents join forces on projects, with AI assisting in research and drafting, allowing team members to remain engaged and complete tasks together. Once a workflow is established, it can be automated to run continuously, with human input required only for critical decisions, creating a smooth, ongoing process rather than a series of isolated prompts. Leadership is empowered to monitor AI utilization, establish guidelines for its application, and ensure accountability by designating responsible parties before significant actions are taken. Currently, many organizations find themselves with AI scattered across personal tools and uncoordinated pilot programs, lacking centralized ownership and strategy. By consolidating these efforts into a single platform, Nimbus offers a comprehensive solution for enhancing productivity and accountability in the workplace.

Lokta Core serves as an AI-centric loan management platform tailored for banks, NBFCs, and digital lenders aiming to streamline modern lending processes while maintaining control, compliance, and autonomy. It seamlessly integrates AI workflows that your teams are currently experimenting with, including agentic servicing, intelligent collections, and copilots for credit operations, ensuring they operate directly within the same record-keeping system rather than as separate add-ons. For a CXO considering immediate changes, three notable improvements emerge on Monday. Firstly, the speed of product launches significantly increases: new loan offerings and policy modifications can be implemented in mere days instead of taking several months, all thanks to a governance-first and policy-driven framework. Additionally, the overall operational costs decrease as a unified, audit-ready system supplants a patchwork of loan management systems, business rule management systems, collections, and reporting tools. Lastly, the platform is inherently AI-ready; every action taken—whether by an operator, customer, or agent—is governed by policies, enforced by a maker-checker approach, and substantiated with evidence, allowing the AI initiatives your board is inquiring about to be put into practice effectively. Furthermore, Lokta Core offers flexibility in deployment options, allowing you to choose between managed SaaS and single-tenant cloud solutions to best fit your organization's needs. This adaptability ensures that you can optimize your lending operations while making the most of the latest technological advancements.

Pulze.ai is an enterprise-level AI platform that eliminates the need for coding, empowering teams to create, implement, and oversee AI-driven assistants and workflows seamlessly. By centralizing access to over 50 top-tier LLMs and AI models, it employs intelligent routing to ensure that every request is processed by the most appropriate model, thereby maximizing performance, quality, and cost-effectiveness. Users can interact with AI models, upload and use documents, conduct web searches, generate images, transcribe audio, and automate various tasks—all from a cohesive “Space” workspace. Additionally, Pulze enables the creation of no-code AI assistants using templates tailored for specific functions, such as managing support tickets, drafting sales materials, and sorting leads. It seamlessly integrates with popular tools like Slack, Google Drive, and Jira, while also upholding enterprise-level security measures, including SOC 2 compliance, data isolation, and a policy of zero data logging by AI providers. This comprehensive approach ensures that organizations can harness the power of AI while maintaining strict security and operational standards.

Ejentum serves as a structured reasoning framework tailored for agentic AI, enhancing the reliability, auditability, and discipline of LLM agents during intricate or protracted tasks. This innovative tool can be invoked by agents mid-task, facilitating precise cognitive operations tailored to the specific challenges they face, allowing for real-time corrections in reasoning rather than depending solely on static prompts. Designed to prevent AI agents from deviating, flattering, fabricating, or fixating on incorrect hypotheses, Ejentum also ensures they don’t settle for superficial answers or lose vital context over successive steps. The framework boasts 679 capabilities organized into four cognitive harnesses: reasoning, code, anti-deception, and memory. Within the reasoning harness, analytical capabilities are directed towards understanding causality, time, space, simulation, abstraction, and metacognition, which aids agents in steering clear of merely recognizing surface patterns. By integrating these diverse functionalities, Ejentum empowers AI to maintain a deeper engagement with tasks, ultimately enhancing the quality of their outputs.

Microsoft Autopilot is a persistent, proactive AI agent within Microsoft Copilot that is designed to perform ongoing work on behalf of users and teams. Formerly known as Scout, Autopilot can be assigned a role and goal and then continue executing tasks without waiting for repeated instructions. It can monitor communication channels, follow up on threads, run recurring processes, and return to a project days later while preserving context. Microsoft describes use cases such as managing a supplier review process, building schedules and workback plans, preparing for meetings, handling follow-ups, and requesting updates from stakeholders. Because Autopilot is cloud-hosted, it can continue working even when the user is not actively using Copilot. The agent operates inside the organization’s Microsoft 365 tenant with its own identity, memory, computer, and workspace. Microsoft IQ provides business context so Autopilot can better understand organizational knowledge, data, and workflows. The agent can appear in Teams, Outlook, chats, channels, and documents and can be mentioned similarly to a colleague. Organizations retain control through permissions, audit capabilities, governance, defined objectives, and boundaries around the work Autopilot performs.

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.

Hindsight is an innovative memory framework designed to enhance AI agents by enabling them to learn progressively rather than resetting their knowledge with each new interaction. Unlike traditional memory systems that primarily focus on recalling past conversations, Hindsight prioritizes the learning process, equipping agents with a persistent long-term memory through advanced biomimetic data structures. This functionality allows AI agents to keep track of essential facts, access relevant context, and engage in reflective reasoning based on their experiences. Hindsight is particularly beneficial for agents that require a deep understanding of user identities, previous discussions, evolving preferences, decision-making histories, and necessary behavioral adjustments across different sessions. To achieve this, it incorporates three fundamental operations: retain, which captures new information; recall, which accesses appropriate memories when required; and reflect, which aids agents in synthesizing observations, developing mental frameworks, and gaining insights from earlier interactions. By implementing these features, Hindsight ensures a more personalized and context-aware experience for users.

PrimeClaws serves as a managed hosting solution for OpenClaw autonomous AI agents, enabling users to easily deploy and operate their OpenClaw instances in the cloud without extensive setup or DevOps expertise; it prioritizes a straightforward, one-click deployment method, allowing an AI assistant powered by OpenClaw to function continuously without the need for a personal laptop or local server to remain operational. The platform supports leading large language models such as Claude, GPT, and Gemini, and features persistent memory across sessions, enabling agents to retain context and continue their tasks over time. Furthermore, it seamlessly integrates with popular messaging platforms like WhatsApp, Telegram, and Slack, ensuring that users can engage with their AI assistant through familiar channels. By utilizing PrimeClaws, users benefit from a simplified approach to infrastructure management, with global cloud operations guaranteeing consistent uptime, root access on self-hosted VPS environments, and comprehensive control over the agent’s ecosystem. This allows for the automatic maintenance of the AI instance, ensuring that it remains active and accessible at all times. Overall, PrimeClaws streamlines the deployment and management of AI assistants, making cutting-edge technology accessible to everyone, regardless of their technical background.

Strands Agents SDK is an open-source development framework that allows developers to build and manage AI agents with precision and control. It supports both Python and TypeScript, making it accessible to a wide range of developers and use cases. Instead of relying on rigid workflows or orchestration layers, the SDK lets developers define tools as functions and rely on the model’s reasoning capabilities to drive execution. The platform works across any AI model or cloud environment, offering flexibility for deployment and scaling. One of its standout features is the use of steering hooks, which act as middleware to guide, validate, and correct agent actions in real time. It also includes support for multi-agent systems, enabling complex workflows through agent collaboration. Built-in memory management ensures context is maintained across long interactions without manual intervention. Developers can monitor performance through observability tools that provide detailed traces and metrics. The SDK also includes an evaluation framework for testing agent accuracy and behavior before deployment. Overall, Strands Agents SDK empowers developers to create reliable, scalable, and intelligent AI agents with minimal complexity.

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.

MemClaw serves as a durable memory service tailored for LLM-driven agents and functions as a regulated shared memory layer among fleets of agents. Its core purpose is to facilitate collaborative learning among AI agents by transforming their isolated contexts into a collective Company Brain, complete with integrated memory features, governance, provenance tracking, contradiction detection, and predefined visibility scopes from the outset. The architecture of MemClaw effectively distinguishes an organization’s agents—including tenants, fleets, nodes, and individual agents—from the managed memory layer via components such as the MCP Server, REST API, OpenClaw plugin, MemClaw Core, and persistent storage solutions. Agents can access and contribute to the Company Brain using MCP-compatible tools, direct HTTPS requests, or integrations through OpenClaw, while the MemClaw Core processes enhancements like entity extraction, contradiction identification, PII screening, and lifecycle management prior to any data being saved. Each memory entry can be labeled with a specific visibility scope and categorized automatically into various types including fact, episode, decision, preference, rule, plan, commitment, action, and outcome. Additionally, this structured approach not only enhances the organization of information but also improves the overall efficiency and effectiveness of AI agent interactions within the network.

The Webex AI Agent offers engaging, lifelike interactions through advanced conversational intelligence, enhancing customer experience across both voice and digital platforms while enabling proactive self-service. By comprehending individual requirements, retaining user history, and adapting to preferences in real time, it ensures a tailored experience for each user. The platform simplifies the creation and implementation of AI agents, allowing for the development of either fully autonomous agents capable of natural dialogues or scripted agents that provide predetermined responses. These AI-driven agents are equipped to manage intricate inquiries by seamlessly integrating with back-office systems to resolve customer concerns comprehensively. Additionally, they can be utilized across multiple communication channels, including voice, SMS, email, live chat, Facebook Messenger, Apple Messages for Business, and WhatsApp, thus offering round-the-clock assistance. When the situation demands, a smooth transition to human agents is possible, with complete context transfer to maintain service continuity. Supporting more than ten languages, the AI Agent effectively breaks down language barriers while enhancing the scalability of customer interactions, ultimately leading to greater satisfaction and efficiency. Furthermore, businesses can leverage analytics from these interactions to continually refine their service delivery.

NVIDIA OpenShell serves as an open and secure runtime environment specifically designed for autonomous AI agents, regulating their execution, access rights, and the pathways for inference traffic. Instead of embedding security within the model or application, it maintains safety measures in the surrounding environment, meaning that nothing is allowed by default; permissions are assigned through established policies, and enforcement mechanisms operate outside the agent process to prevent any circumvention via prompts. Each autonomous agent operates within a confined sandbox, which restricts direct network connectivity, limits file access, and implements kernel-level monitoring of system calls to ensure rigorous oversight. Acting as the control plane, a gateway is responsible for user authentication, lifecycle management of sandboxes, and the provision of policies, settings, credentials, and inference configurations to the agents. Additionally, a supervisor operates externally to each sandbox, scrutinizing network requests according to policies at various levels—including binary, destination, method, and path—and only grants access to credentials when explicitly permitted, thus enhancing the overall security framework. This layered architecture ensures that the agents function effectively while maintaining robust security protocols throughout their operations.

Strike48 is a cutting-edge Agentic Operations Platform that merges comprehensive log visibility with tailored AI agents capable of executing security, IT, and compliance tasks at extraordinary speed. Many organizations typically only keep an eye on around 60-70% of their operational environment, largely because traditional SIEM and observability solutions render full log monitoring prohibitively expensive. Strike48 effectively addresses this visibility shortfall through an innovative architecture that separates log storage from initial parsing choices, empowering teams to ingest and retain all their logs without straining their budgets. You can either bring your logs to Strike48 or query them directly from their existing locations, such as Splunk, data lakes, or hybrid systems, eliminating the need for any disruptive transitions. Moreover, built on this cohesive data foundation, Strike48 deploys self-sufficient AI agents that conduct investigations, correlate alerts, prioritize issues, gather evidence, and create as well as validate detection rules, seamlessly transferring tasks among themselves. Furthermore, a human-in-the-loop approach guarantees that essential actions such as endpoint isolation and remediation receive human approval, ensuring thorough audit trails are maintained throughout the process. This comprehensive functionality allows organizations to enhance their operational efficiency while ensuring robust oversight and accountability.

VerifyAX serves as a platform for verifying AI agents, enabling organizations to assess their autonomous agents' performances in realistic conditions prior to launching and during their operational phase. This platform offers a comprehensive verification framework that allows for the simulation of agent behavior, the testing of edge scenarios, the tracking of decision-making pathways, and the detection of potential problems before they can impact live systems. Teams are able to integrate their agents, models, and various tools, specify their testing objectives, and conduct evaluations based on simulations aligned with defined criteria. Each evaluation generates detailed audit-level reports that include scores, transcripts, narratives, and actionable recommendations. The platform accommodates various structured data formats such as text, images, tables, CSV, Excel, and PDF, while also enabling synthetic data creation for rigorous stress testing without risking the security of proprietary information. Additionally, VerifyAX assesses agents' proficiency in utilizing enterprise applications like email, Jira, and Slack, analyzing metrics such as workflow completion, accuracy of outputs, efficiency of processes, and consistency throughout multiple assessments. This multifaceted approach ensures that organizations can confidently deploy their AI agents, knowing they have been thoroughly vetted under real-world conditions.

CogniAgent is a no-code AI agent platform for business. Your agents talk across 8 channels and act across 2,700+ systems. An agent can check an order, an open calendar slot, or a CRM record mid-dialogue and reply with the real answer instead of promising a follow-up. The 8 channels are voice, SMS, WhatsApp, web chat, Gmail, Outlook, Slack, and Microsoft Teams. Agents run on three technologies. Conversational AI agents hold natural, multi-turn dialogue to qualify leads, answer questions, and collect details. Autonomous AI agents work in the background on events, schedules, or thresholds and complete multi-step tasks across connected systems. Cognitive AI agents unite the two: they talk and act in the same exchange, for example taking a booking, logging a new lead, or sending a quote while the customer is still in the conversation. When a case needs a person, the agent hands it over with the full context. Common agents include lead qualification and follow-up, appointment booking, customer support and order status, candidate screening and interview booking, HR onboarding, and invoice checks. Setup starts from a ready-made template, or the AI Concierge builds the agent from a plain-language description. No developer is needed. The 2,700+ systems include CRM, scheduling, ERP, helpdesk, and ATS apps, with native Google Sheets and Slack connections, so agents read and write live data. Pricing is usage-based with no subscription and no per-seat fee. Pay as You Go is free to start with 5,000 credits on signup, credit packs from $10, credits that never expire, and up to 5 user seats. Enterprise adds an annual credit package, SSO, your own LLM API keys, and agents built by the CogniAgent team.

Donorlytics serves as the analytical backbone for nonprofit organizations, aimed at converting intricate data into straightforward insights and automated processes. This innovative platform integrates information from various sectors including fundraising, grants, events, marketing, volunteer efforts, and compliance into a cohesive overview. Equipped with advanced analytics and AI-powered suggestions, nonprofit executives can discover overlooked opportunities, significantly reduce the time spent on manual reporting, and enhance their decision-making speed and confidence. By leveraging Donorlytics, research institutions, healthcare facilities, and purpose-driven organizations can achieve operational clarity and efficiency comparable to leading enterprises, ultimately propelling their missions forward. This transformative approach not only streamlines processes but also empowers organizations to maximize their impact in the communities they serve.

Built for event-sourced systems, Axoniq Insights turns your event store into a queryable SQL database. Your event store database holds the complete history of your business, but figuring out "what happened, and why" usually means digging by hand. Insights handles that manual work for you. Ask your question in natural language or write SQL directly, and either way you get the answer. Now included with every Team tier deployment of Axon Server. Built for agentic workflows: When an agent acts in production, the next question is always the same: why? Insights gives you the answer. Ask in natural language what the agent did, which events it saw, and what state it was responding to, then trace each answer back to the event behind it. Ask what an agent did, in plain language: Skip the execution logs and the engineering ticket. Ask Insights what an agent did over a window, on a customer, in a specific scenario, and get a readable answer back, the same way you'd ask a teammate. Replay the decision context on demand: Every agent decision is a reaction to some state of the world. Insights reconstructs the exact events the agent saw, in order, at the moment it acted. The same picture the agent had, available on demand. Every explanation, backed by events: Plain-language explanations are only useful if you can verify them. Insights links every answer back to the underlying events in your event store, so compliance, ops, and regulators can trace any explanation down to the immutable record.

NEO functions as an autonomous machine learning engineer, embodying a multi-agent system designed to seamlessly automate the complete ML workflow, allowing teams to assign data engineering, model development, evaluation, deployment, and monitoring tasks to an intelligent pipeline while retaining oversight and control. This system integrates sophisticated multi-step reasoning, memory management, and adaptive inference to address intricate challenges from start to finish, which includes tasks like validating and cleaning data, model selection and training, managing edge-case failures, assessing candidate behaviors, and overseeing deployments, all while incorporating human-in-the-loop checkpoints and customizable control mechanisms. NEO is engineered to learn continuously from outcomes, preserving context throughout various experiments, and delivering real-time updates on readiness, performance, and potential issues, effectively establishing a self-sufficient ML engineering framework that uncovers insights and mitigates common friction points such as conflicting configurations and outdated artifacts. Furthermore, this innovative approach liberates engineers from monotonous tasks, empowering them to focus on more strategic initiatives and fostering a more efficient workflow overall. Ultimately, NEO represents a significant advancement in the field of machine learning engineering, driving enhanced productivity and innovation within teams.

Utilize our automated insights and customizable metrics to assess, enhance, and perpetually refine your GenAI models. Future AGI streamlines the evaluation of AI model outputs by automatically scoring them, which removes the necessity for manual quality assurance assessments. As a result, your QA team can redirect their efforts toward more strategic initiatives, potentially boosting their efficiency and capacity by as much as tenfold. This ensures that your AI-driven customer interactions remain consistently positive and aligned with your brand identity. By optimizing your models, you can highlight the most pertinent and engaging content tailored to each user. Additionally, you can fine-tune your models to produce the most precise summaries for your audience. Future AGI empowers you to establish bespoke metrics that assess your AI model's accuracy according to the specific priorities of your use case. You can articulate your essential metrics in natural language, providing your QA team with greater adaptability and authority to evaluate model performance. This approach guarantees that your assessments are in harmony with your business goals, transcending conventional metrics such as relevance while promoting a more comprehensive evaluation framework. Embracing this method not only enhances model performance but also fosters a culture of continuous improvement within your organization.

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.

Showly is a platform designed for hosting websites generated by AI agents, providing a sleek environment for users to preview, publish, share, and manage their creations. Users can articulate their desired project to their coding agent—whether it’s a report, research page, presentation, documentation site, portfolio, landing page, prototype, or product specification—and the agent will generate the corresponding page while Showly takes care of the hosting and publication process. The platform integrates seamlessly with various agents like Claude Code, Codex, Cursor, OpenClaw, and Hermes Agent, enabling users to publish their work without disrupting their existing workflows. Changes are first displayed as private previews, allowing users to assess the page, request modifications, and choose the moment of publication. Once live, the work generates a stable, shareable web link, and the version history feature allows for easy restoration of previous versions if necessary. Additionally, Showly has the capability to transform existing outputs into live web pages by simply accepting the provided content. This makes it an invaluable tool for anyone looking to streamline their digital publishing process.

Phinite offers a comprehensive shared infrastructure designed for the efficient construction, deployment, and governance of AI agents, encompassing orchestration, security, observability, lifecycle management, and environment promotion, which allows engineering teams to avoid the repetitive task of rebuilding these foundational layers for each new agent application. Key features include orchestration capabilities for multi-agent systems that facilitate agent-to-agent interactions and nested calls, in-depth session-level observability that tracks execution timelines, decision variables, tool usages, and associated latency and cost metrics. Additionally, Phinite boasts a Private Agent Registry to enhance skill discoverability, an evaluation suite for assessing accuracy and safety benchmarks, and a streamlined Dev-to-Production workflow that supports seamless environment promotion. Moreover, it enables Kubernetes-native deployments and VPC-internal deployability while ensuring adherence to SOC 2 Type 2 compliance standards, ultimately providing a robust environment for developing AI agents efficiently. This combination of features not only enhances productivity but also fosters innovation within engineering teams.

Rithmo serves as a fact-checking tool specifically designed for AI agents, ensuring that organizations avoid the pitfalls of relying on outdated, conflicting, or obsolete business information. By continuously aligning decisions made across various meetings, communications, and operational frameworks, Rithmo enables agents to operate based on the most accurate and current business truths rather than merely leveraging the information they gather. In instances where the context shifts, Rithmo is capable of detecting inconsistencies, supplying the resolved response along with its source, and halting an agent's action if the conflict cannot be resolved safely. As an integral component of the governance and reliability framework for AI agents, Rithmo offers a comprehensive decision history, established provenance, supersession details, and an audit trail that elucidates what changes occurred and the reasons behind them. Furthermore, Rithmo enhances the functionalities of AI agent memory, orchestration, observability, security, and enterprise search by tackling a distinct challenge: confirming whether the business context that informs an agent’s actions remains valid. This capability ensures that organizations can trust the actions of their AI agents are grounded in the most reliable and relevant information.

SRE.ai is an innovative automation platform driven by AI, specifically designed for teams developing on Salesforce. It features AI agents that optimize DevOps processes, facilitating key tasks such as continuous integration, continuous deployment, testing, and managing releases. These agents are customizable to align with unique workflows, which aids in speeding up deployments, resolving errors, and conducting thorough release simulations. By seamlessly integrating with existing tools for communication, ticketing, and version control, SRE.ai boosts productivity and simplifies the complexities associated with releases. Additionally, the platform includes essential functionalities like efficient backups and disaster recovery solutions to protect against potential data loss. With its foundation laid by former engineers from Google Research and DeepMind, SRE.ai enjoys the support of prominent investors and is currently honing its focus on the Salesforce ecosystem. Our agents undergo rigorous quality assessments and include measures to prevent inaccuracies. Moreover, users have the flexibility to configure workflow stages to incorporate human oversight, ensuring a balanced approach between automation and human intervention. This adaptability helps teams to work more efficiently and effectively within their development environments.

OpenWeave serves as a governance mechanism for AI agents and autonomous systems, functioning as a server-enforced state machine that regulates the actions of AI agents and the timing of those actions. Users can outline workflows comprising states, transitions, and authorized triggers; the backend consistently enforces transitions with a strict 403 error, while pivotal states require human approval, effectively preventing bots from acting until a human intervenes. The monitoring feature provides insights into agent activities, ensuring that OpenWeave stops inappropriate actions before they occur. Instead of hardcoding transitions, agents learn about permissible transitions through the API, ensuring that every bot possesses a verifiable identity, and all modifications are logged in an immutable audit trail. The system offers integration through a REST API and a remote MCP server, making it a vital resource for AI-agent developers, AgentOps/MLOps, and platform teams. This comprehensive framework not only enhances security but also streamlines the management of AI workflows, ultimately contributing to safer and more efficient autonomous systems.

Agent 365 is Microsoft’s new enterprise framework for managing AI agents with the same rigor and structure used for human users. It centralizes oversight by providing a registry that surfaces every agent operating within your organization, including identity-secured agents, internally registered agents, and automatically detected shadow agents. The platform enhances security by extending Microsoft Defender protections, Entra identity access controls, and Purview governance policies to all agents. Agent 365 integrates with Microsoft 365, Power Apps, Power Automate, and Power BI, enabling agents to participate in workflows, analytics, and productivity tasks just like any other digital worker. Using Work IQ, organizations can equip agents with deep contextual understanding sourced from company data, relationships, and internal systems. This unified approach simplifies deployment, strengthens compliance, and improves operational insight for IT teams. Through Microsoft’s Frontier early access program, IT admins can explore and activate Agent 365 directly in the Admin Center. Microsoft built Agent 365 to support the rapidly growing role of AI agents across enterprise environments, ensuring they remain secure, governed, and aligned with organizational standards.

Nekuda transforms websites into platforms that AI agents can effectively engage with by integrating WebMCP tools, which allow these agents to perform various site functions while enabling website owners to maintain oversight and control over interactions. Development teams have the option to either create comprehensive WebMCP tools using a coding agent or quickly deploy initial tools by simply adding a single line of code to a public website. Once these tools are in place, businesses gain the ability to define and oversee the actions that agents can perform, including tasks like product searches, policy retrieval, checkout processes, order tracking, and application data updates. Additionally, Nekuda tracks agent activities in detail, recording individual tool interactions and entire agent sessions, which provides teams with insights into how agents navigate their website. The platform also features integrated evaluation and testing functions that assess task success rates and allow for the replaying of scenarios both prior to and following deployment, ensuring that essential workflows such as searching, checkout, policy retrieval, and fallback actions operate smoothly and as expected. This comprehensive approach not only enhances the functionality of websites but also empowers teams to adapt and optimize their digital environments based on real-time data and agent performance.

Trase is a regulated AI platform designed for sectors like healthcare, government, and enterprise, where trust, security, sovereignty, and predictability are paramount. It offers a robust infrastructure for the deployment of AI agents within actual workflows, featuring a multitude of specialized agents that are ready for immediate production use, along with the necessary systems to maintain oversight on every workflow, decision, and escalation. The operational backbone for these agents is Trase Origin, an operating system specifically engineered to manage, secure, and govern agents across various environments including cloud, on-premises, VPC, and edge, all while ensuring data remains in its original location. Within a unified control plane, Trase and third-party agents benefit from shared policy enforcement, comprehensive monitoring, cost management, defined escalation procedures, and a complete, immutable audit trail. Additionally, it enables deployments that comply with HIPAA and SOC2 standards, while ensuring data residency, privacy, model adaptability, and freedom from vendor lock-in. This multifaceted approach allows organizations to effectively leverage AI while adhering to stringent regulatory requirements.

Manifest, developed by Omfang, serves as an action layer for AI agents, transforming any webpage into a structured representation that delineates the capabilities available to an agent. By submitting a URL to the Manifest API, developers obtain a clean JSON output that details the state of the page, encompassing available buttons, forms, inputs, navigation links, mandatory fields, and interdependencies among actions. Manifest operates by loading the webpage in a genuine Chromium browser after executing JavaScript, examining the accessibility tree utilized by screen readers, and cross-referencing it with the underlying DOM to capture intricate details often overlooked by the accessibility layer, such as input types, placeholders, disabled states, and submission prerequisites. Once potential actions are identified, their locators are resolved with precision instead of relying on model-generated guesses; any ambiguous matches are flagged as uncertain rather than assumed. This process provides agents with a machine-readable framework that enhances their reasoning capabilities regarding interactions like clicking, filling, or submitting without depending on screenshots or fragile CSS selectors. Ultimately, Manifest elevates the efficiency and reliability of AI agents in navigating and interacting with web content.

Akka is a runtime and agentic systems platform designed for building reliable, distributed, high-performance applications at enterprise scale. The platform has a long production track record across banking, streaming, analytics, workflows, edge systems, digital twins, and mission-critical event processing. Akka uses in-memory actor-based concurrency, clustering, durable state, sharding, event journals, and real-time streaming with backpressure to support resilient applications that can survive failures and scale globally. Its Agentic AI Platform extends those runtime capabilities to AI systems, giving teams a way to build, govern, deploy, and verify agents as certified production services. Developers and business teams can describe desired systems through specifications, while Akka generates agents, tools, integrations, memory, workflows, APIs, streaming components, and user interfaces. Governance teams can define safeguards, approvals, evaluations, sanitizers, human-in-the-loop controls, human-on-the-loop controls, evidence requirements, and policy boundaries. Akka Verify validates what is running against the approved specification and supports fine-tuning from production data. The platform can run across Akka-hosted environments, customer VPCs, business continuity setups, sovereign cloud configurations, and major cloud providers. By combining runtime reliability, agentic orchestration, governance, observability, durable execution, and enterprise delivery support, Akka helps organizations move AI systems from prototype to production.

The HelpNow Agentic AI Platform by Bespin Global is a robust automation and orchestration solution designed for enterprises, enabling them to swiftly develop, implement, and oversee autonomous AI agents that are specifically aligned with their business processes, all without the need for extensive coding skills. This is achieved through a visual interface known as Agentic Studio and a centralized management portal, which allows for the creation of both single and multi-agent workflows, seamless integration with current systems using APIs and connectors, and real-time performance monitoring through an Agent Control Tower that ensures governance, enforces policies, and maintains quality standards. Furthermore, the platform facilitates LLM orchestration, accommodates various input formats (including text, voice, and STT/TTS), and offers flexible deployment options across multiple cloud environments such as AWS, GCP, Azure, and on-premises solutions, while ensuring connectivity to internal data and documents. By tapping into context-rich enterprise information, these agents are empowered to perform effectively. Additionally, the platform encompasses features for managing the entire lifecycle of agents, providing real-time observability, and integrating with both voice and document processing systems, all while adhering to enterprise governance protocols. Thus, organizations can harness advanced AI capabilities without compromising on control or oversight.

Forsy is centered on genuine human signals derived from actual agent workflows, assisting teams in capturing, interpreting, and trading trajectory data across the entire agent ecosystem. It monitors agent activities in real time as they occur, instead of reconstructing actions after the fact, enabling native capture of traces, tasks, and toolchain interactions. The platform is crafted to ensure comprehensive coverage of routine tasks, specialized workflows, and various domains, providing teams with a unified engine for trajectory data based on their existing agents. By transforming AI agents into valuable strategic resources, Forsy makes authentic workflow information easily discoverable, licensable, and marketable within the agent data marketplace. Its high-quality data is specifically tailored for teams aspiring to develop more proficient and dependable agents, facilitating access to the critical real-world workflow traces necessary for enhancing agent performance, reliability, and assessment. This innovative approach not only streamlines workflows but also empowers organizations to leverage their data effectively, leading to more intelligent and adaptable AI solutions.

Isle offers managed environments for desktop applications tailored for computer-use agents, incorporating built-in guardrails, application monitoring, and artifact checkpoints. Rather than providing a standard machine and expecting the agent to handle the application, Isle encapsulates each application with necessary monitoring, containment, and recovery measures to enable effective work. The environments are pre-loaded with the required software that is already set up and accessible, while health checks ensure the application is operational instead of merely verifying the machine’s online status. Developers can integrate any computer-use model or agent loop through commonly used screenshot, mouse, keyboard, file-transfer, and execution functionalities. Furthermore, artifact checkpoints safeguard valuable progress before significant actions are taken and can be restored if an issue arises, while recovery controls empower agents to restart applications and revert to the most recent stable state. This comprehensive approach enhances productivity and minimizes disruptions, making it an ideal solution for managing desktop applications.

Bid farewell to the hassles of manual coding and accelerate the creation of agents like never before. Simply articulate your requirements, and SmythOS will generate it based on your conversation or image, leveraging top-tier AI models and APIs tailored to your needs. You can utilize any AI model or API, seamlessly integrating with platforms such as OpenAI, Hugging Face, Amazon Bedrock, and countless others without needing to write a single line of code. With a library of pre-built agent templates, you can access agents that are ready to function for various use cases instantly; all it takes is a click of a button and your API keys to connect. It's essential that your marketing team does not have access to agents interacting with your code, and we ensure that protection. Establish dedicated spaces for each client, team, and project with comprehensive user and permission management capabilities. You can choose to deploy on-premises or on AWS, while integrating with Bedrock, Vertex, Adobe, Salesforce, and much more. Enjoy explainable AI with complete oversight over data flows, including audit logs, encryption, and authentication measures. You can engage in conversations with your agents, assign them bulk tasks, review their logs, set work schedules, and perform an array of additional functions to streamline your operations efficiently. This innovative approach empowers your team to focus on strategy and creativity, leaving the technical complexities to SmythOS.

Lumro serves as a comprehensive platform designed for the creation, management, and deployment of AI agents that are capable of handling various tasks including sales, customer support, lead generation, appointment scheduling, and ensuring customer satisfaction, all while providing human-like engagement around the clock. These AI agents integrate effortlessly with multiple communication channels such as website chat, email, WhatsApp, Instagram, Facebook, and phone services. Furthermore, they are compatible with existing business tools like CRMs, payment gateways, and scheduling applications, enabling them to perform more than just answering common queries; they can actively capture leads, manage support tickets, schedule appointments, process transactions, escalate issues, retrieve product details, and execute customized workflows that align with specific business needs. Lumro also offers features for brand customization and voice alignment by training the agents on company-specific data such as websites, PDFs, manuals, and previous interactions, while continuously monitoring performance through detailed analytics to ensure optimal operation. This comprehensive approach not only enhances efficiency but also ensures that businesses can maintain a consistent and engaging customer experience across various platforms.

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