15 Best Agentic AI Companies of 2025

Your support ticket queue just hit 500. Your sales team is still qualifying leads manually. Your developers are buried in bug reports instead of building. Meanwhile, your competitor’s AI agents are handling all of this autonomously freeing up teams to focus on strategy, growth, and innovation.

This is the new business divide in 2025: not between big and small companies, it’s between those using agentic AI companies and agentic AI solutions that deploy autonomous agents to automate business processes, and those still doing everything manually.

What is Agentic AI?

Agentic AI technology refers to AI systems that pursue goals independently, use tools, plan multi-step actions, and self-correct when errors occur. These AI agents act like tireless digital teammates, planning, executing, and adapting without waiting for instructions.

Gartner forecasts that by 2028, 33% of enterprise software applications will include agentic AI, up from less than 1% in 2024. The report also states that by 2028, at least 15% of daily decision making will be made autonomously via agentic AI.

In short, it is not just AI that talks; it is AI that does. And the best agentic AI companies are helping enterprises drive real outcomes: reduced manual effort, faster execution, and measurable ROI.

With dozens of vendors emerging, not all deliver real results. Some are hype, while others offer enterprise-grade impact. This guide highlights the 15 agentic AI companies list of 2025 that help businesses deploy autonomous agents effectively.

How we selected the top agentic AI companies in the list

Each company was evaluated on six key factors:

• Production readiness & adoption: Case studies, enterprise deployments, or active pilots

• Agent capabilities: Multi-step planning, tool use, orchestration frameworks

• Ecosystem & integrations: Compatibility with CRMs, ERPs, messaging tools, and RPA systems

• Security & governance: Compliance with SOC 2, ISO, or similar audit-ready standards

• Pricing clarity: Transparent pricing tiers or clear buyer motions

• Roadmap momentum: Recent launches, funding, or product updates showing consistent innovation

Quick glance on agentic AI companies list

Agentic AI companies for Customer Experience

1. WotNot

WotNot is a no-code AI agent platform that lets teams design, deploy, and iterate multi-agent systems across web, WhatsApp, and more without touching code. The suite spans an AI Studio for knowledge-based agents, a visual bot builder, live-chat handoff, and analytics to track outcomes and improve flows. 

Key features:

• Drag-and-drop bot/agent builder with visual flow design.

• Omnichannel deployment (website, WhatsApp, Messenger, voicebot) with human handoff.

• Native integrations, APIs, and webhooks for flexible workflows.

• Built-in analytics to monitor KPIs and optimize performance.

• Enterprise-grade security and hosting options (ISO 27001, SOC 2, GDPR, HIPAA; public/private cloud & on-prem).

Best for:
E-commerce, Real Estate, Healthcare, and support teams that want production-ready AI agents with quick, no-code iteration.

What’s unique:
A genuinely visual, no-code interface paired with enterprise security and flexible deployment including private cloud/on-prem and a growing integration marketplace, making it easy to operationalize and govern AI at scale.

Pricing:
14-day free trial; paid plans from $29/month (Starter $99, Premium $299; Enterprise custom).

2. Botpress

Botpress is an all-in-one AI agent platform aimed at enterprises and developers who need deep customization, full control, and production-scale conversational workflows. The platform combines a visual flow builder with the flexibility of custom code, large language model (LLM) integration, and deployment across channels – all while offering usage-based pricing. 

Key features:

• Proprietary engine that blends generative AI with structured logic to autonomously orchestrate workflows.

• A unified interface with drag-and-drop flow building plus JavaScript/SDK support for custom behaviors.

• Omnichannel deployment across web, WhatsApp, Slack and voice, with seamless CRM/ERP integrations.

• Built-in vector database support and knowledge-base indexing so bots answer from your own content.

• Enterprise-grade hosting options, role-based access control, audit logs and compliance (GDPR, SOC 2).

Best for:
Mid-to-large enterprises, product or engineering teams requiring tailor-made AI agents (support bots, conversational sales assistants, internal virtual agents) that integrate deeply with existing systems (CRMs, ERPs, databases).

What’s unique:
Botpress‘s combination of a no/low-code interface and full developer-level control makes it stand out: you get visual building for rapid prototyping and direct access to custom logic when needed. Meanwhile its transparent usage-based pricing (you pay for messages/events and LLM tokens) gives more flexibility than many enterprise-only platforms.

Pricing:
Free pay-as-you-go plan; paid tiers start at about $89/month + AI usage.

3. Voiceflow

Voiceflow is a collaborative AI-agent platform designed to help product and design teams quickly build voice and chat assistants with visual workflows, deep integrations, and team-centric tooling. 

Key features:

• Visual canvas to map conversational flows and logic without code.

• Ability to train agents on your own business data (knowledge-base, vector database, multi-LLM support) so responses are tailored and context-aware.

• Multichannel support for both voice-agents (phone calls) and chat agents in web/apps, enabling broader engagement.

• Collaboration tools including shared workspaces, version control, team permissions, and cross-team alignment.

• API-first developer toolkit and integrations (CRMs, data warehouses, telephony, analytics) for customization and scalability.

Best for:
Teams that want to quickly prototype and deploy conversational AI across voice and chat, especially when designers, product owners, and developers collaborate and when you need scalable infrastructure that supports growth and customization.

What’s unique:
Voiceflow stands out by bringing voice-agent capability (phone/voice call workflows) into the same visual and collaborative platform used for chat agents, making it one of the few tools designed for cross-channel conversational products rather than just chatbots.

Pricing:
Free Starter plan; Pro from ≈ US$60/month; Business from about US$150/month (Pricing is user-based).

Agentic AI companies for Software Development

4. OpenAI

OpenAI is an AI-research and deployment organisation whose tools are widely used by software-development teams to build, integrate and scale artificial intelligence driven workflows, agents and applications.

Key features:

• ChatGPT enables conversational AI with text, voice and image input/output, plug-ins/apps and context-aware assistance across complex tasks.

• Codex acts as a software-engineering agent that can generate code, answer questions about a codebase, fix bugs and propose pull-requests all executed in sandboxed environments.

• OpenAI’s APIs allow developers to embed, customise and scale models like GPT-series and Codex into their apps, automate backend workflows and orchestrate multi-agent systems.

Best for:
Software teams, product engineers and development-led organisations that want to embed agentic AI solutions into their toolchain to accelerate coding, automate operations, build AI assistants and reduce manual engineering burdens.

What’s unique:
OpenAI stands out by offering one of the broadest and most powerful suites of agentic capabilities from conversational assistants (ChatGPT) to specialist code agents (Codex) and developer-friendly APIs, allowing organisations to shift from isolated chatbots to deeply integrated software-agent ecosystems.

Pricing:
API pay-per-use; ChatGPT Pro $226.06/month.

5. Cursor

Cursor is an AI-powered code-editor and agent platform developed by Anysphere, Inc. that enables software teams to off-load coding tasks, refactor large codebases and build multi-agent developer assistants integrated into the workflow. 

Key features:

• Ability to understand an entire project’s codebase and answer natural-language queries about it.

• “Agent mode” where autonomous agents can execute tasks like editing code, running tests and committing changes with minimal guidance.

• Support for multi-line edits, smart rewrites, and seamless integration with terminal/CLI commands to streamline developer flow.

• Compatibility with major LLMs (OpenAI, Anthropic, Gemini, xAI) so teams can pick the best model for coding tasks.

• Background-agent and collaboration mode allowing large or multiple agents to work asynchronously, send status updates, and integrate with systems like Slack.

Best for:
Engineering teams, dev-ops groups and product organisations seeking to boost developer productivity, scale code-generation workflows and integrate agentic AI deeply into their software tool-chain.

What’s unique:
Cursor differentiates itself by offering not just autocomplete or chat-assist but full-scale autonomous agents working on your codebase—combined with editor, CLI and remote-machine support. It is built from the ground up for “agentic software development” rather than just smart code suggestions.

Pricing:
Free tier available for individuals; Pro and Team/Enterprise plans available.

6. Adept.ai

Adept's agentic AI tool automates complete computer workflows, orchestrating both browser and app actions beyond APIs. It allows teams to plan and track multi step processes safely and audibly execute repetitive tasks.

Key features:

• An agentic model that can interpret natural-language instructions and operate across desktop or web applications as a human would.

• Multimodal model support (text + UI + images) such as the “Fuyu-Heavy” model designed for UI understanding and task execution.

• Ability to integrate with existing software stacks by automating workflows without needing explicit APIs for each step; for example extracting data from one tool, entering into another, applying business logic, then reporting outcomes.

• Continuous learning loop via feedback and data-collection tools so the custom AI agents improve over time and adapts to the organisation’s workflows.

• Designed for enterprise scale, targeting knowledge workers, operations, finance, HR, and cross-department automation instead of only chatbots

Best for:
Organisations that have complex multi-application workflows (for example across CRM, spreadsheets, internal tools, etc.) and want to deploy multiple AI agents that can directly execute those workflows rather than simply assist via chat.

What’s unique:
Unlike most platforms that provide conversational agents or workflow builders, Adept AI positions itself as an autonomous collaborator - an agent that can navigate software, handle user workflows, and act across tools rather than waiting for API-based building blocks. Their focus on multimodal UI understanding (via Fuyu-Heavy), and using the full digital workspace as the operating environment, makes it particularly suited to organisations wanting to scale internal automation quickly.

Pricing:
Custom pricing (enterprise-oriented); some sources report a Pro plan starting around US $49/month for smaller use cases.

Agentic AI companies for Process Automation

7. UiPath

UiPath, a global leader in automation software, has evolved beyond traditional robotic process automation (RPA) to position itself as a frontrunner in “agentic automation”—autonomous AI-agents that plan, act and adapt to complete complex business workflows. 

Key features:

• Platform enables building agentic AI systems that perceive, reason and execute workflows across systems. 

• Agent Builder tool allows organisations to create, customise and deploy AI agents working alongside robots and humans. 

• Full orchestration of agents, robots and human interaction on a unified platform for end-to-end process automation. 

• Enterprise-grade governance, security and scalability embedded into agentic automation architecture. 

• Wide range of use cases including finance, healthcare, supply chain, and document processing where agents handle dynamic decision-making.  

Best for:
Large enterprises and business functions (finance, HR, IT, operations) that aim to move beyond scripted automation into intelligent agents that can manage unstructured workflows, collaborate with humans and robots, and scale across the business.

What’s unique:
UiPath stands out by combining the maturity of an RPA vendor with pioneering capabilities in agentic AI systems, bringing together AI agents, robots and people into one autonomous orchestration layer. It empowers enterprises to automate not just repetitive tasks but goal-oriented workflows with decision-making logic and adaptability.

Pricing:
Custom enterprise-pricing (tiers depend on scale, modules and deployment).

8. Beam AI

Beam AI is a next-generation agentic process-automation platform that enables enterprise teams to build, deploy and manage autonomous AI agents and workflows at scale.

Key features:

• A unified Agent OS enabling creation, orchestration, memory, integrations and governance in one enterprise-platform. 

• Multi-agent workflows where several agents coordinate tasks, route across systems, and adapt dynamically to achieve complex tasks. 

• Integration-first design allowing agents to connect with CRMs, ERPs, databases, SaaS tools and custom APIs. 

• Learning agents with memory and feedback loops: agents retain context across sessions and improve over time. 

• Pre-built templates and industry-specific agents (finance, insurance, logistics, HR) to accelerate deployments. 

Best for:
Large enterprises and operations teams looking to move beyond rule-based RPA toward true autonomy, especially when workflows span multiple systems, require decision-making, routing, human-hand-off, and continuous improvement.

What’s unique:
Beam AI distinguishes itself by framing automation as an agentic workforce rather than just workflow scripts or bots. Its platform delivers full autonomy: agents that plan, act and learn, not simply respond. The convergence of multi-agent orchestration, memory/context, integrations and enterprise governance creates a strong foundation for scaling process automation in complex environments.

Pricing:
Custom enterprise-pricing (access on request).

9. Automation Anywhere

Automation Anywhere has evolved from traditional RPA (Robotic Process Automation) into a full-scale “agentic process automation” platform, enabling autonomous AI-agents to orchestrate workflows, make decisions and adapt in real time. 

Key features:

• AI-agents can perceive context, plan actions, execute tasks and learn, thereby performing intelligent automation rather than just following fixed rules. 

• The “Agentic Process Automation System (APA)” includes a process reasoning engine trained on 400M+ workflow interactions so agents can reason about enterprise context. 

• Low-code/​no-code AI Agent Studio enables business users to build agentic automations using templates and AI skills. 

• Multiple specialized agents work across legacy apps, cloud, on-prem systems, CRMs, ERPs and APIs to automate end-to-end processes. 

• Enterprise governance and security built in: audit trails, role-based access, compliance with standards (HIPAA, SOC 2, etc) embedded.  

Best for:
Large enterprises and operations teams (finance, HR, IT, supply chain) that need to move beyond rule-based automation into smart, goal-oriented workflows across multiple systems and business units.

What’s unique:
Automation Anywhere stands out by translating the RPA heritage into true agentic automation: the platform doesn’t just automate steps, it enables AI-agents that reason, adapt and act across systems. Its extensive enterprise features and broad system coverage make it well-suited for large-scale digital transformation.

Pricing:
Custom enterprise pricing; contact vendor for quote.

Agentic AI companies for Research and Development

10. Anthropic

Anthropic is a research-driven AI company focused on building safe, interpretable, and capable large language models (LLMs) for advanced reasoning, coding, and research applications. Founded in 2021, it’s the creator of the Claude family of models, which are known for their long context understanding, strong safety alignment, and natural language fluency.

Key features:

• Claude 3 models handle large-context reasoning (200k + tokens) and multi-step research or analysis tasks with high factual accuracy.

• Claude Code offers AI-assisted software development—writing, refactoring, and debugging code in natural language across multiple programming languages.

• “Constitutional AI” framework ensures model outputs follow human-aligned, transparent reasoning principles.

• API and enterprise-tier tools allow fine-tuning, integrations, and model orchestration for scientific or business R&D.

• Designed for high-trust use cases like legal analysis, technical writing, and research synthesis where reliability and context retention are critical.

Best for:
Research teams, innovation labs, and engineering organizations needing AI for deep reasoning, technical documentation, or multi-step software-development workflows.

What’s unique:
Anthropic combines cutting-edge reasoning models with a strong focus on safety and interpretability, making Claude equally valuable for both research and coding applications.

Pricing:
Free tier for Claude 3 Haiku; paid access from US $20/month (Pro) and API token-based enterprise pricing.

11. IBM Watson

IBM’s Watson brand has evolved significantly into the “watsonx” platform, offering agentic AI capabilities for enterprise research and development, supporting large-scale model building, agent orchestration and trusted deployment.

Key features:

• The WatsonX studio lets developers build, deploy and monitor AI agents in a unified environment, with one-click deployment and built-in tracing of agent behaviour. 

• WatsonX Orchestrate offers multi-agent orchestration: visual drag-and-drop workflows, a catalog of 100+ prebuilt agents and tool integrations, and governance features for enterprise scale. 

• Supports open, hybrid architectures: choose from IBM Granite models, third-party and open-source models, and run across cloud or on-premise. 

• Extensive tool-kit for R&D: includes code assistants (WatsonX Code Assistant) and data/workflow tools to accelerate research, model fine-tuning and knowledge discovery. 

• Strong enterprise-grade governance, scalability and compliance built-in to support mission-critical uses in research labs and development pipelines. 

Best for:
R&D teams, innovation labs, enterprise engineering organisations and data-science groups that need an agentic AI platform to build and deploy intelligent agents and models, manage multi-agent workflows, and apply AI in research or product development contexts.

What’s unique:
IBM Watson’s evolution into WatsonX makes it a comprehensive enterprise-grade agentic-AI platform that spans from research and development through to production deployment, combining model experimentation, agent orchestration and governance in one ecosystem.

Pricing:
Varies by product - please contact IBM for enterprise tiers; free trials available for some components.

12. Google

Google has actively positioned itself at the forefront of “agentic AI” — building systems that don’t just react but plan, select tools, act and learn across workflows. Their push is especially strong in research & development contexts, enterprise agent orchestration, and large-scale agentic infrastructure.

Key features:

• The Gemini 2.0 model family supports multimodal input/output (text, image, audio), tool-use, long-context reasoning and is designed for “agentic era” workflows. 

• The Vertex AI Agent Builder enables organisations to create and orchestrate multi-agent systems built on Google’s infrastructure, bridging developer workflows, data sources and enterprise processes. 

• The open-source Agent Development Kit (ADK) allows precise control over agent behaviour, tool integrations and debugging — making agentic workflows easier to build and maintain. 

• Agent2Agent (A2A) protocol for interoperability so agents can communicate and coordinate across enterprise systems and multi-agent applications. 

• Research-driven “AI Co-Scientist” examples where Google uses multi-agent systems built with Gemini to accelerate hypothesis generation and scientific discovery.

Best for:
R&D teams, data-science groups, enterprise innovation labs and product engineering organisations that want to build agentic systems for complex workflows. e.g., scientific discovery, multi-system orchestration, knowledge-worker augmentation.

What’s unique:
Google is unique in combining cutting-edge model research (Gemini, DeepMind), enterprise tools (Vertex AI, ADK) and the infrastructure to build agentic systems at scale — making it a strong choice for organisations who want to move beyond stand-alone AI assistants and towards integrated, multi-agent workflows.

Pricing:
Varies by product/plan; Google offers scalable enterprise-usage pricing via Google Cloud and Vertex AI; contact Google Cloud for details.

Agentic AI tools for Sales and Marketing

13. Qualified

Qualified is a B2B go-to-market platform focused on agentic sales and marketing automation. Its flagship agent, “Piper the AI SDR”, autonomously engages leads in real time across web chat, email, and meetings—with the goal of converting them directly into pipeline. 

Key features:

• Piper engages website visitors instantly using chat, voice or video to convert them into qualified leads. 

• It sends personalized follow-up emails, nurtures warm leads and books meetings without human SDR intervention. 

• Deep integration with CRM (especially Salesforce), martech stacks and intent-signal systems so the agent acts on buyer data and behaviour. 

• Full-funnel automation: from inbound visitor interaction to meeting booked to pipeline closed. 

• Built-in AI trust, security and compliance (SOC2, GDPR) to support enterprise deployment.

Best for:
Marketing and sales-led organisations (particularly B2B) that need scalable, always-on pipeline generation, faster lead response, and real-time conversion of website visitors into opportunities.

What’s unique:
Qualified differentiates itself by offering a true “AI SDR agent” not just chatbots or email automations, but an agent that reasons over intent signals, acts autonomously across channels, and books meetings at scale. Its enterprise-grade stack plus focus on full-funnel conversion makes it a strong candidate in the "Sales & Marketing” category.

Pricing:
Available by custom quote; plans start from a mid-tier CRM-integrated package.

14. Salesforce Agentforce

Agentforce is Salesforce’s autonomous AI platform that lets businesses build, deploy, and manage intelligent agents that act across sales, service, and marketing workflows using trusted enterprise data. Considered one of the best agenti AI platforms for enterprises within the Salesforce ecosystem.

Key features:

• Agents reason through data, plan next steps, and take actions autonomously across CRM workflows.

• Easily manage AI agents and its usage across departments and teams through role-based permissions.

• Low-code Agent Builder helps business users create topic-based or task-based agents, while developers can extend capabilities using Apex, APIs, and SDKs.

• Deep integration with Salesforce CRM, Data Cloud, Slack, and MuleSoft ensures agents can engage customers across multiple channels.

• Prebuilt templates for roles like Sales Assistant, SDR Agent, and Service Agent help teams launch quickly.

• Built-in governance, guardrails, and compliance maintain control and security across agent activities.

Best for:
Enterprises using Salesforce that want to scale customer engagement, automate lead qualification, or improve service efficiency with intelligent agents working within their existing stack.

What’s unique:
Agentforce is unique because it embeds AI agents directly inside Salesforce, enabling teams to automate actions using real customer data while maintaining enterprise-level security and governance.

Pricing:
Custom enterprise pricing based on deployment and usage.

15. Relevance AI

Relevance AI is a low-code/no-code agent platform that enables businesses to build and deploy autonomous “AI workforces” composed of multiple agents that integrate, act and learn across workflows. 

Key features:

• Create and customize AI agents equipped with tools, APIs, and integrations to perform research, outreach, or content creation tasks.

• Build and manage multi-agent workflows where agents collaborate to complete larger business goals.

• Connect seamlessly with CRMs, spreadsheets, and SaaS apps to automate real business processes.

• Enable continuous learning as agents improve through feedback and performance data.

• Enterprise-ready with SOC 2 compliance and options for private or single-tenant deployment.

Best for:
Sales, marketing, operations, and business teams that want to stand up autonomous agents quickly to research prospects, generate content, automate campaign flows, qualify leads, or manage workflows without heavy engineering overhead.

What’s unique:
While many platforms provide bots or chat assistants, Relevance AI focuses on creating agent teams that act with autonomy equipped with tools, integrations, and learning capabilities.

Pricing:
Free tier available; paid plans start from custom enterprise pricing. 

How to choose an agentic AI platforms

Selecting the right agentic AI company requires more than just comparing model accuracy or automation speed. Look for a solution that aligns with your business goals, scales across teams, and integrates well with your existing enterprise systems.

• Agent capabilities – Assess whether the platform supports multi-step reasoning, tool usage, multi-agent collaboration, and error recovery mechanisms.

• Integration fit – Ensure seamless compatibility with CRM, ERP, messaging tools, document stores, RPA systems, and data warehouses to enable true end-to-end automation.

• Security and governance – Check for SOC 2 or ISO certifications, clear data residency policies, audit trails, and role-based controls to maintain compliance.

• Observability – Look for platforms that offer logs, runbooks, guardrails, and built-in evaluation tools to monitor and improve agent performance.

• Pricing and total cost of ownership – Compare pricing structures such as API-based, seat-based, or platform-based models, and factor in infrastructure and scaling costs.

• Vendor stability – Favor vendors with a strong enterprise customer base, consistent innovation, and a proven track record of product reliability.

By focusing on these aspects, you can identify an agentic AI partner that not only meets your technical needs but also integrates deeply into your organization’s ecosystem.

The Road Ahead for Agentic AI Technology

Agentic AI revolution amplifies human capabilities. Like a self-driving car, it handles repetitive tasks, complex processes, analyzes the road ahead, and keeps your business processes moving while you steer strategy. These 15 companies are the linchpins driving innovation, efficiency, and a smarter future.

If your business has not explored agentic automation yet, now is the time. Begin your journey of developing agents with WotNot and transform operations one smart decision at a time.