Best Agentic AI Platforms for Small Business - Page 15

Introducing the Gemini 2.5 Computer Use model, an advanced agent built upon the visual reasoning strengths of Gemini 2.5 Pro, specifically crafted for direct interaction with user interfaces (UIs). This model is accessible through a newly developed computer-use tool within the Gemini API, which takes inputs such as the user's request, a screenshot of the UI context, and a log of recent actions. It adeptly generates function calls relevant to UI tasks, including clicking, typing, or selecting, while also having the capability to seek user confirmation for tasks deemed higher risk. Following each performed action, the model receives updated feedback in the form of a new screenshot and URL to facilitate a continuous process until the task is either completed or stopped. Primarily fine-tuned for web browser navigation, it also shows potential for mobile UI interactions, although it currently lacks the capability for desktop OS-level management. In various benchmarks comparing web and mobile control tasks, the Gemini 2.5 Computer Use model demonstrates superior performance over leading competitors, achieving remarkable accuracy with reduced latency, and paving the way for future enhancements in interface interaction.

Gemini Enterprise, an all-encompassing AI platform from Google Cloud, is designed to harness the full capabilities of Google’s sophisticated AI models, tools for creating agents, and enterprise-level access to data, seamlessly integrating these into daily workflows. This innovative solution features a cohesive chat interface that facilitates employee interaction with internal documents, applications, various data sources, and personalized AI agents. The foundation of Gemini Enterprise consists of six essential elements: the Gemini suite of large multimodal models, an agent orchestration workbench (previously known as Google Agentspace), ready-made starter agents, powerful data integration connectors for business systems, extensive security and governance frameworks, and a collaborative partner ecosystem for customized integrations. Built to scale across various departments and organizations, it empowers users to develop no-code or low-code agents capable of automating diverse tasks like research synthesis, customer service responses, code assistance, and contract analysis while adhering to corporate compliance regulations. Moreover, the platform is designed to enhance productivity and foster innovation within businesses, ensuring that users can leverage advanced AI technologies with ease.

Tasklet is an advanced automation platform powered by AI that allows users to streamline intricate business workflows simply by articulating their needs in natural language. It integrates effortlessly with a multitude of pre-existing connections, direct HTTP APIs, and even cloud-based services to perform tasks across all tools utilized by your team. After setup, automation workflows can be initiated based on a schedule, triggered by incoming emails, or activated through webhooks, facilitating various tasks such as daily summaries that merge calendar events, emails, and to-do lists; managing support emails by consulting knowledge bases and composing responses; monitoring various external sources like news or social media and sending alerts to team communication channels; or providing timely reminders for upcoming deadlines and events. Tasklet eliminates the necessity for tedious “if-this-then-that” configurations or ongoing manual check-ins by employing intelligent agents that adjust to situations, address errors, and function independently. By doing so, it significantly enhances productivity and allows teams to focus on more strategic initiatives.

Nora is characterized as an advanced reasoning agent designed specifically for software development with an emphasis on Web3 technology stacks. This platform accommodates prominent smart-contract languages such as Solidity, Move, Cairo, and Rust, while seamlessly adapting to their respective execution models and semantics. By design, it possesses compiler- and VM-awareness, allowing it to grasp bytecode generation, control flow, instruction-level modifications, and unique runtime environments like EVM and WASM. Its debugging and validation features are contextually intelligent, which empowers it to detect subtle bugs, unintended state anomalies, and architectural constraints within intricate codebases. Furthermore, Nora is dedicated to expediting the transition from conceptualization to product realization by providing support to development teams in critical areas such as core module creation, interface integration, testing protocols, deployment strategies, and upholding architectural consistency, thereby minimizing context-switching and enhancing the efficiency of Web3 product development. Additionally, by streamlining these processes, Nora contributes to a more cohesive and productive development experience.

The Logic platform enables teams to streamline recurring decision-making and review workflows by allowing them to draft processes in straightforward English. Users can outline the decision framework, which may include moderation guidelines, invoice assessment criteria, or lead qualification procedures, or they can upload an existing standard operating procedure (SOP). The advanced AI engine of Logic promptly converts these descriptions into a functional API and web application ready for production. It manages version control, testing, rollbacks, and tracking of audit trails automatically, thus empowering business users to refine process logic without facing engineering delays. Logic is designed for enterprise-level dependability, capable of securely managing extensive decision workloads, and integrates effortlessly as a REST API with tools like Zapier, n8n, ChatGPT, and Claude, among others. By removing the necessity for API keys, prompt engineering, model adjustments, or additional infrastructure, it allows operations, business operations, and workflow teams to completely take ownership of automation processes. This comprehensive approach not only enhances efficiency but also fosters innovation within organizations.

Noah AI serves as an advanced research assistant powered by artificial intelligence, specifically designed for professionals in the life sciences sector, with the goal of automating and expediting intricate workflows in biomedical research, clinical development, and strategic commercial planning. It features an “Agent” mode that efficiently manages and implements multi-step tasks through intelligent web searches, accessing credible scientific databases like PubMed and FDA/NIH resources, summarizing influential research papers, extracting data from clinical trials, and producing high-quality reports, while a simpler “Search” mode provides quick and trustworthy access to summaries of domain-specific content. By integrating extensive medical and public health data, alongside AI-generated insights and real-time tracking of global research and development activities as well as conference intelligence, Noah AI empowers researchers, biotech investors, and healthcare professionals to transform questions into insights significantly faster than traditional methods. This innovative approach not only enhances productivity but also fosters a more informed decision-making process in the ever-evolving landscape of life sciences.

Rebolt is a sophisticated AI platform tailored for enterprises, allowing businesses to develop bespoke applications and intelligent agents through simple verbal commands directed at the AI. It provides seamless integration with various corporate tools like OneDrive, SharePoint, Salesforce, and Slack, as well as custom APIs, and includes essential infrastructure such as databases, file storage, scheduling capabilities (like cron jobs), audit logs, and separate environments for staging and production deployment. Users can generate applications and agents without any need for API key coding, merely by articulating their requirements in natural language, while still ensuring robust enterprise security features, permissions mapping through systems like Azure groups, and role-based access controls. This platform is specifically engineered for constructing operational workflows, internal tools, and automation that link to the firm's existing data and services, thus empowering non-technical users or low-code teams to quickly create solutions that can replace spreadsheets, cumbersome manual processes, and disjointed SaaS solutions. Additionally, Rebolt's intuitive design fosters increased collaboration among teams, enhancing productivity and innovation within the organization.

BotDojo serves as a robust AI enablement platform tailored for enterprises, allowing companies to create, implement, oversee, and expand intelligent agents across various communication channels like chat, voice, email, and web, all through an intuitive low-code visual workflow designer that seamlessly integrates with existing enterprise data systems. It boasts a library of over 100 pre-built templates aimed at streamlining typical applications, including support automation, knowledge retrieval, sales analytics, and internal operations, while also facilitating branching logic, memory capabilities, and the orchestration of tools such as code, RPA, and web browsing. In addition, BotDojo establishes connections with essential business tools like CRMs, ticketing platforms, and databases to enhance its functionality. The platform further fosters continuous improvement and learning for agents through human feedback loops, enabling employees to mentor agents by providing feedback, embedding corrections into agent memory and responses, and assessing performance using comprehensive observability metrics, including deflection rates, first-contact resolution, and cost per interaction. Ultimately, BotDojo not only optimizes operational efficiency but also ensures that intelligent agents evolve and adapt to meet organizational needs effectively.

Khorus serves as a versatile platform designed to create a universal communication framework for intelligent systems, empowering developers, startups, and businesses to construct, launch, and profit from networks of AI agents and robotic workflows. At the heart of the platform lies an innovative Agent-to-Agent (A2A) architecture, which facilitates the coordination of tasks, contextual sharing, and collaboration among AI agents, moving beyond simple data exchange. The platform accommodates scalable modules across various sectors including IoT, gaming, robotics, and Web3, while also integrating an on-chain agent economy that leverages standards like ERC-8004 and X402, allowing for the publication, licensing, and monetization of agents and workflows within a marketplace. Users are able to delineate agent roles, skills, and workspaces, connect APIs and integrations, initiate workflows, and track task progression. Furthermore, they can offer their agents or automation blueprints for others to utilize, thereby generating a stream of recurring revenue through their contributions to the ecosystem. As a result, Khorus not only enhances collaboration among AI agents but also fosters a sustainable model for innovation and income generation.

TRAE SOLO is a highly adaptive coding assistant designed specifically for real-world software development, effortlessly merging with a developer’s entire tech stack, including their editor, terminal, browser, documentation, design tools, and deployment systems, to transform ideas from mere concepts into fully realized products. The platform allows for input through natural language or voice commands, enabling users to articulate their needs while it systematically organizes their ideas, identifies the appropriate context and tools, performs tasks across various environments, autonomously generates and reviews code, conducts testing and optimization processes, and ultimately deploys the finished product, all within a cohesive workspace that allows for seamless transitions between AI-driven and manual operations. In addition, TRAE SOLO accommodates multiple agents functioning simultaneously, each equipped with its unique model and context, thus granting users the ability to select the most suitable model for any given task, track each agent’s progress in real time, and make adjustments or redirections whenever necessary, enhancing overall productivity and collaboration. With its comprehensive features, TRAE SOLO stands out as an essential tool for modern developers aiming to streamline their workflow and increase efficiency.

GPT-5.1-Codex is an advanced iteration of the GPT-5.1 model specifically designed for software development and coding tasks that require autonomy. The model excels in both interactive coding sessions and sustained, independent execution of intricate engineering projects, which include tasks like constructing applications from the ground up, enhancing features, troubleshooting, conducting extensive code refactoring, and reviewing code. It effectively utilizes various tools, seamlessly integrates into developer environments, and adjusts its reasoning capacity based on task complexity, quickly addressing simpler challenges while dedicating more resources to intricate ones. Users report that GPT-5.1-Codex generates cleaner, higher-quality code than its general counterparts, showcasing a closer alignment with developer requirements and a reduction in inaccuracies. Additionally, the model is accessible through the Responses API route instead of the conventional chat API, offering different configurations such as a “mini” version for budget-conscious users and a “max” variant that provides the most robust capabilities. Overall, this specialized version aims to enhance productivity and efficiency in software engineering practices.

Dimension is a comprehensive collaboration platform tailored for engineering teams that seamlessly combines chat, code management, tasks, and deployments within a single context-aware environment. This innovative tool allows developers to directly view and modify repositories while effectively managing GitHub issues and branches in real time, tracking their work across various tasks, engaging in conversations with teammates, and monitoring deployments. The platform features advanced AI capabilities that highlight crucial insights and actions derived from inboxes, pull requests, logs, and discussions, while also automating repetitive workflows and offering a global Command-K menu for swift navigation. With a live edge-powered interface and integrations with popular tools such as GitHub, Slack, Gmail, Vercel, and more, Dimension significantly minimizes context-switching, harmonizes divergent workflows into a cohesive process, accelerates shipping timelines, and ensures alignment across code, communication, and actions. By empowering developers and engineering managers with a consolidated view of their code, tasks, and operations, Dimension fosters enhanced productivity and collaboration within teams. Ultimately, Dimension is designed to streamline the entire development process, making it easier for teams to focus on what truly matters.

Edison Analysis serves as an advanced scientific data-analysis tool developed by Edison Scientific, functioning as the core analytical engine for their AI Scientist platform known as Kosmos. It is accessible through both Edison’s platform and an API, facilitating intricate scientific data analysis. By iteratively constructing and refining Jupyter notebooks within a specialized environment, this agent takes a dataset alongside a prompt to thoroughly explore, analyze, and interpret the information, ultimately delivering detailed insights, comprehensive reports, and visualizations akin to the work of a human scientist. It is capable of executing code in Python, R, and Bash, and incorporates a wide array of common scientific-analysis libraries within a Docker framework. As all operations occur within a notebook, the logic behind the analysis remains completely transparent and accountable; users have the ability to examine how data was processed, the parameters selected, and the reasoning that led to conclusions, while also being able to download the notebook and related assets whenever they wish. This innovative approach not only enhances the understanding of scientific data but also fosters greater collaboration among researchers by providing a clear record of the entire analytical process.

Emdash serves as an orchestration layer that allows you to execute numerous coding agents simultaneously, each within its own distinct Git worktree, enabling you to address various subtasks or experiments concurrently without any interference. It is designed to be provider-agnostic, allowing you to select from a range of AI models and command-line interfaces, such as Claude Code and Codex, tailored to your specific workflow requirements. With Emdash, you can directly assign issues or tickets from platforms like Linear, GitHub, or Jira to a selected agent, enabling you to observe multiple agents working in parallel in real time. The user interface provides live updates on agent status and activities, and as soon as agents produce code, you can easily review differences, add comments, and initiate pull requests, all within the Emdash environment. Each agent operates within its own worktree, ensuring changes remain isolated and comparable, which facilitates safe testing of various implementations or strategies side by side. This unique setup not only enhances productivity but also encourages experimentation without the risk of code conflicts.

Sideconvo is an innovative plugin powered by AI that enhances a traditional website, transforming it into an engaging and interactive platform by automatically scanning all its pages, including FAQs, product details, and uploaded documents, to create a comprehensive knowledge base for a smart conversational agent. After a simple installation via a single line of JavaScript added to the site header, Sideconvo activates instantly, allowing users to interact through both voice and text. The AI agent excels in real-time engagement, responding to inquiries, assisting visitors, summarizing or retrieving pertinent information, and facilitating navigation through the website or product offerings, which ultimately boosts usability, customer support, and conversion rates. Additionally, site administrators have the flexibility to customize the AI’s personality and tone—whether it be playful, polished, or professional—and refine its interactions by determining which content areas to emphasize or avoid, specifying target audiences, and personalizing conversation starters or guidelines. This level of customization ensures that the conversational experience aligns perfectly with the site's branding and user expectations.

OpenAGI provides a modern framework for building intelligent agents that behave more like autonomous digital workers rather than simple prompt-driven LLM tools. Unlike standard AI apps that only retrieve or summarize information, OpenAGI agents can plan ahead, make decisions, reflect on their work, and perform actions independently. The system is built to support specialized agent development across domains ranging from personalized education to automated financial analysis, medical assistance, and software engineering. Its architecture is intentionally flexible, enabling developers to orchestrate multi-agent collaboration in sequential, parallel, or adaptive workflows. OpenAGI also introduces streamlined configuration processes to eliminate infinite loops and design bottlenecks commonly seen in other agent frameworks. Both auto-generated and fully manual configuration options are available, giving developers the freedom to build quickly or fine-tune every detail. As the platform evolves, OpenAGI aims to support deeper memory, improved planning skills, and stronger self-improvement abilities in agents. The vision is to empower developers everywhere to create agents that learn continuously and handle increasingly complex real-world tasks.

Lux introduces a breakthrough approach to AI by enabling models to control computers the same way humans do, interacting with interfaces visually and functionally rather than through traditional API calls. Through its three distinct modes—Tasker for procedural workflows, Actor for ultra-fast execution, and Thinker for complex problem-solving—developers can tailor how agents behave in different environments. Lux demonstrates its power through practical examples such as autonomous Amazon product scraping, automated software QA using Nuclear, and rapid financial data retrieval from Nasdaq. The platform is designed so developers can spin up real computer-use agents within minutes, supported by robust SDKs and pre-built templates. Its flexible architecture allows agents to understand ambiguous goals, strategize over long timelines, and complete multi-step tasks without manual intervention. This shift expands AI’s capabilities beyond reasoning into hands-on action, enabling automation across any digital interface. What was once a capability reserved for large tech labs is now accessible to any developer or team. Lux ultimately transforms AI from a passive assistant into an active operator capable of working directly inside software.

Kodey serves as a versatile AI-agent platform that allows individuals to create, launch, and oversee autonomous AI agents without any coding expertise required. It features an intuitive visual builder tailored for non-technical users, who can effortlessly drag and drop elements and link workflows or data sources in just a few minutes; for developers seeking advanced customization, comprehensive SDKs and APIs such as Python, JavaScript, and REST/GraphQL are provided. After setting up, the agents operate within secure, containerized environments and can be deployed in production through REST, WebSocket, or as integrated web components, with Kodey.ai automatically adjusting infrastructure to accommodate varying demands. Furthermore, the platform comes equipped with pre-existing integrations for databases and third-party applications, along with capabilities for real-time monitoring, analytics, version control, and collaborative features that include role-based access control, thereby ensuring reliability, security, and ease of maintenance within production workflows. Kodey's design enables users to focus on innovation while it efficiently handles the complexities of AI deployment.

TruGen AI revolutionizes conversational agents by creating fully immersive, human-like video avatars capable of seeing, hearing, responding, and acting in real time. These advanced agents feature hyper-realistic avatars equipped with expressive facial features, eye contact, and fluid body and facial animations. Central to this technology are two key models: the video-avatar model, which produces high-fidelity facial animations instantly, and the vision model, which supports interactions that are sensitive to context and emotions, such as recognizing faces and detecting actions. Utilizing a developer-friendly, API-centric platform, integrating these video agents into websites or applications can be accomplished with minimal coding effort. Once activated, these agents operate with remarkable speed, exhibiting sub-second response times, retaining conversational history, and seamlessly linking with existing knowledge bases. Additionally, they can interact with custom APIs or tools, thus providing responses that are not only context-aware and consistent with the brand but also capable of executing specific actions beyond mere conversation. This innovative approach opens new avenues for enhancing user engagement and delivering personalized experiences.

The Mistral Vibe CLI is an innovative command-line tool designed for "vibe-coding," allowing developers to engage with their projects using natural language commands instead of relying solely on tedious manual edits or traditional IDE functionalities. This interface integrates with version control systems like Git, examining project files, the structure of directories, and the status of Git to establish context. It leverages this context alongside advanced AI coding models, such as Devstral 2 and Devstral Small, to perform a variety of tasks including multi-file edits, code refactoring, code generation, searching, and manipulating files— all initiated through simple English instructions. By keeping track of project-specific details such as dependencies, file organization, and history, it is capable of executing coordinated updates across multiple files at once, such as renaming a function and ensuring all references throughout the repository are adjusted accordingly. Additionally, it can create boilerplate code across different modules and even help outline new features starting from an overarching prompt, significantly streamlining the development process. This approach not only enhances productivity but also fosters a more intuitive coding environment for developers.

Forge Code is an AI-driven pair-programming tool that operates within the terminal, allowing users to manage their entire codebase through conversational commands. It integrates effortlessly into your shell environment, meaning there's no need to disrupt your current IDE or workflow; you can continue using the tools you are familiar with. Once activated, Forge Code gains insight into project files, Git history, dependencies, and the surrounding environment, enabling it to grasp the structure of your codebase and respond to queries without needing constant clarifications. It features a dual-agent system, consisting of a “Forge Agent” that carries out code modifications and executes real-time operations, alongside a “Muse Agent” that focuses on planning, evaluating, and reviewing code without making any alterations to your files. Furthermore, Forge Code can be utilized with your chosen AI service providers or self-hosted LLMs, ensuring you maintain complete oversight of your code's handling and the model's operation. This flexibility allows developers to tailor the experience according to their specific needs and preferences.

SciSpace BioMed serves as an innovative AI-powered "co-scientist" tailored for the field of biomedical research, integrating an extensive literature repository with over 150 bio-tools and more than 100 academic databases and software applications to enhance intricate research processes, which encompass areas such as genomics, single-cell analysis, drug discovery, and clinical genomics. This platform empowers researchers to pose questions in natural language, manage datasets, analyze variants or multi-omics results, plan experimental workflows, reason about clinical biology and diseases, and produce publication-ready materials, including figures, tables, and presentations, all while ensuring transparency and proper citations. Furthermore, users have the capability to engage with scientific articles through a “chat with PDF” feature that allows them to highlight and seek clarification on challenging text, mathematical content, or tables, making it an excellent tool for grasping complex methods or concepts. For the purposes of literature review or preliminary research, its AI-enhanced semantic search can sift through millions of academic papers, providing citation-supported summaries that facilitate deeper understanding and exploration of the relevant literature. This functionality significantly accelerates the research process, allowing scientists to focus more on their discoveries rather than administrative tasks.

Charlie Labs presents Charlie, an AI-driven autonomous engineering assistant designed to expedite the coding process for software teams by automating various tasks such as coding, reviewing pull requests, fixing bugs, implementing features, and more, all while fitting seamlessly into existing workflows. This innovative tool integrates effortlessly with familiar developer platforms like GitHub, Slack, Linear, Sentry, and Vercel, functioning in the midst of daily operations by monitoring events such as pull requests and mentions, subsequently producing high-quality TypeScript code, managing branches, and creating pull requests with clean commits and successful tests automatically. It effectively identifies bugs, delivers actionable inline feedback, generates feature code based on issue descriptions, and can even interpret natural language requests within team communication channels, allowing engineers to concentrate on strategic planning and design rather than mundane implementation tasks. Consequently, Charlie not only enhances productivity but also empowers teams to innovate and deliver higher quality software at a faster pace.

Action State Labs focuses on creating infrastructure for native Android AI agents, featuring an open-source tool named Android Use that facilitates seamless interaction between AI agents and native Android applications by directly accessing the Android Accessibility Tree, thus avoiding unreliable computer vision techniques. This innovative method allows AI agents to manage and interpret app user interfaces more quickly, at a significantly reduced cost (up to approximately 95% less), and with enhanced resilience to changes in UI, which simplifies the automation of intricate tasks such as logistics, field operations, and various functions usually performed on native mobile platforms. Furthermore, it offers an open-source core that can operate on local devices or emulators, along with a managed cloud solution that includes auto-scaling capabilities for enterprise applications, API endpoints, and comprehensive support services, enabling developers to efficiently create, test, and implement automation workflows powered by agents across multiple devices simultaneously. The combination of these features positions Action State Labs as a leader in the field of AI-driven automation for mobile applications.

Do Anything is an innovative AI-driven personal assistant platform that goes beyond merely supplying answers by actively executing tasks for users, facilitating the delegation of both everyday activities and intricate projects through natural language commands; this platform seamlessly integrates with a user’s preferred applications, tools, and online services to autonomously manage tasks such as sending emails, creating to-do lists, conducting web searches, filling out forms, gathering information, scheduling appointments, organizing events, and completing complex multi-step operations, thereby minimizing tedious manual tasks and boosting overall productivity. In contrast to conventional AI chatbots that merely provide recommendations, Do Anything’s smart agent operates in the background to carry out specific actions based on user instructions phrased in everyday language, leveraging calendars, communication applications, project management tools, and various integrations to perform work that would typically necessitate direct user interaction, ultimately transforming the way users manage their tasks and responsibilities. This platform not only enhances efficiency but also empowers users to focus on more strategic endeavors by offloading repetitive work to the AI assistant.