10 Best AI Agents That Automate Your Business Processes
Running a business means keeping up with fast-moving customer expectations and rising operational demands. Teams are stretched thin trying to manage conversations, handle follow-ups, and maintain consistent service around the clock.
As your business grows, these demands only get more complex, and relying on basic automation for routine tasks often leads to slower response times.
Unlike traditional bots, AI agents are built to understand intent and adapt to different scenarios. They can act intelligently, respond in context, and improve over time.
In this article, we’ll explore the best AI agents and highlight platforms that help you automate support. We'll also discover which AI chatbot solution will help future-proof your business and simplify how your team delivers value.
What Is an AI Agent?
An AI agent is an autonomous software system that observes its environment, analyzes inputs, and takes action toward a goal without human intervention.
Compared to basic scripts or rule-based programs, AI agents are powered by artificial intelligence.
They understand context and adapt their behavior over time. They operate in a continuous sense-decide-act cycle by perceiving inputs, choosing the best response, and then carrying out a task.
Traditional chatbots are often rule-based since they respond only to specific keywords or preset prompts.
In contrast, conversational AI chatbots use advanced natural language understanding to grasp a user’s intent and context. They can handle more varied inquiries, and many improve with every interaction, gradually becoming a more powerful tool in your digital strategy.
Why Are AI Agents the Key to Operational Efficiency?
Using AI agents in your business lets you automate time-consuming, repetitive tasks such as responding to FAQs, routing tickets, scheduling meetings, or retrieving data.
Offloading these tasks lets your human team concentrate on higher-level work that requires empathy, critical thinking, or creativity.
Another reason to adopt AI agents is the consistency and accuracy they bring to your daily operations. Because they respond based on verified content and structured logic, their output often makes sense in a way that improves clarity and reduces mistakes.
You can train an AI chatbot on your documentation, policies, or internal knowledge base for it to respond with precision and cite its sources when needed.
Finally, integrating AI agents prepares your organization for long-term adaptability. With the ability to learn, adapt, and integrate across systems, these agents develop alongside your needs.
AI agents help you stay competitive, meet rising expectations, and future-proof your operations with intelligent, actionable support.
10 Best AI Agent Platforms in 2025
When it comes to choosing an AI agent or chatbot solution, there are many options in the market. Below, we’ve compiled ten of the best AI agent platforms worth considering.
1. Denser
Denser is an enterprise AI agent and chatbot platform focused on easy deployment of custom AI support bots for websites and apps.
The standout feature of Denser is that you can train AI on your own knowledge sources. You can feed it your website content, documentation, PDF manuals, or data from Google Drive. Denser will automatically build an AI agent that can answer questions based on that content.
This is done through retrieval-augmented generation (RAG). When a user asks something, the AI retrieves relevant information from your documents and uses it to formulate a precise answer.
Answers are accurate and come with cited sources for transparency. Denser can highlight the exact snippet in a PDF where the answer came from.
You can also deploy your AI agent on your website via a chat widget, integrate it into platforms like Slack or Shopify, or use its API to connect elsewhere.
Denser is a no-code chatbot. Therefore, your teams can set up workflows and customize the chatbot’s appearance and behavior without coding.
Why Denser is the Best AI Agent
Denser's advanced AI agents are designed to understand context and respond naturally. They can step in to answer common questions and transition smoothly when a human needs to talk with the customer.
Denser brings a rich feature set to the table, which makes it the best chatbot for AI customer support:
- Intelligent document analysis: Denser's document review tool is capable of indexing and analyzing large documents with smart highlighting and source citation with evidence-backed responses.
- Proactive lead generation: Not just for support, Denser’s AI agent can capture and qualify leads by engaging website visitors in natural conversation.
- Fully customizable & brand-friendly: Denser allows customization to ensure interactions align with your brand and compliance requirements.
- Seamless integrations: Denser easily connects with your existing tools to create end-to-end workflows by pulling order data and updating records across your ecosystem.
- 24/7 autonomous support: With always-on availability, Denser’s AI agent can handle after-hours inquiries and repetitive questions consistently.
Ready to boost your customer support with AI? Request a product demo or sign up for a free trial and experience how an AI agent can transform your service and sales!
2. Zendesk AI
Zendesk is a customer service software that also incorporates AI capabilities into its platform.
Image Source: zendesk.com
The platform's AI can autonomously handle simpler tickets across web, mobile, and social channels, providing 24/7 support to reduce the burden on your team. It uses your existing knowledge base articles and past tickets to generate answers.
Zendesk’s Agent Copilot helps live agents by suggesting reply drafts and next steps based on the context of the ticket. It can also auto-triage incoming requests by analyzing customer intent and sentiment, ensuring urgent issues get priority.
However, advanced AI features can make Zendesk quite expensive for smaller organizations. New or small teams sometimes struggle, and it can be a bit overwhelming to learn all the flow builders, content connectors, and custom QA prompts.
3. Intercom Fin
Fin is Intercom’s AI chatbot solution built to deliver human-like customer interactions across chat, email, and more. Fin is powered by advanced AI and is trained on your Intercom help center articles, FAQs, and policies.
Image Source: intercom.com
Fin is designed to operate continuously and handle a wide range of queries. It can carry on conversations naturally and then escalate to a human agent when it encounters something it can’t handle.
Companies use Fin to deflect routine inquiries and thus lighten the load on support teams. It’s also omnichannel, where it can assist customers on your website chat, in-app messenger, or via email.
Some have mentioned missing features in reporting or integrations. While Fin integrates well with Intercom and some major platforms, custom integration scenarios might need work, and some reporting capabilities were basic.
4. Freshdesk Freddy AI
Freddy AI is a suite of AI tools offered by Freshworks, and Freshdesk is their customer support platform. Freddy includes an AI support agent that you can deploy without coding, plus an AI copilot to assist your human agents.
The Freddy virtual agent learns from your company’s knowledge base and past tickets to answer common questions across email, chat, and other channels. It’s capable of personalized, context-aware responses and supports multiple languages out of the box.
Image Source: freshworks.com
For live support staff, Freddy’s Agent Copilot can summarize incoming tickets, suggest response templates, and adjust the tone of replies to match the customer’s mood. It also performs sentiment analysis to help prioritize critical issues.
But some of Freddy’s most powerful features, like the Freddy AI add-ons for agents or advanced bots, come at an extra cost. Users have also noted that they cannot customize certain AI behaviors or interface elements, which can be restrictive if your workflow is non-standard.
5. Salesforce Einstein GPT
Salesforce Einstein (now referred to as Einstein GPT with the addition of generative AI) is Salesforce’s integrated AI layer across its CRM and Service Cloud.
Einstein AI agents can automate customer interactions on digital channels and help your team inside the Salesforce platform. For customer service, Einstein bots can handle chats, process rich inputs, and answer questions using data from your Salesforce knowledge base.
Image Source: salesforce.com
On the agent side, Einstein can generate draft replies, summarize cases, and recommend the best action by analyzing CRM data and customer sentiment. For sales teams, Einstein can populate follow-up email text or update opportunity info.
As promising as generative AI is, the quality of its outputs depends on the data it’s trained and fed with. If your CRM data is outdated or inconsistent, the AI might produce irrelevant or incorrect answers.
Another drawback is that Einstein GPT is tied to the Salesforce ecosystem. It's beneficial if you already use Salesforce’s platform, but it’s not a standalone chatbot you can plug elsewhere easily.
That said, Salesforce’s recent acquisition of Convergence AI suggests a broader shift toward AI. Agents can learn to adapt across dynamic workflows and enterprise-wide systems.
6. Ada
Ada is an AI-powered customer service chatbot platform known for its no-code builder and automation capabilities. Ada’s AI agent connects to your existing content and performs actions via integrations.
Ada’s Reasoning Engine allows the bot to carry out tasks across other systems through API integrations. It can handle transactional requests end-to-end and supports omnichannel interactions, including web chat, mobile, Facebook Messenger, and WhatsApp.
Image Source: ada.cx
Several users mention that the initial setup and training of the Ada chatbot can be a heavy lift, and configuring complex intents and workflows may require some technical know-how.
Another limitation is that some integrations are not available. One user pointed out that Ada didn’t natively integrate with a tool like Zoho Desk, which was a drawback for their particular stack.
7. Forethought
Forethought offers an AI solution for support teams centered on its virtual agent called Agatha. It's designed to resolve support tickets across channels by detecting what the customer needs and retrieving the answer from your knowledge base.
Their Triage AI automatically tags and prioritizes incoming tickets by analyzing the issue described. The Assist AI gives human agents real-time suggestions while they’re working on a ticket.
Image Source: forethought.ai
However, some users feel that the platform’s cost is on the high side. Forethought’s rapid pace of adding new features also means the documentation or UI can occasionally lag. Some features feel a bit confusing or clunky until you get used to them.
8. IBM Watson Assistant
IBM’s Watson Assistant is an AI agent platform, now developed on the Watsonx infrastructure. IBM’s AI agents are known for their natural language understanding and enterprise-grade features.
Watson Assistant allows you to build chatbots that can draw from FAQs, docs, and backend systems to answer user questions.
Image Source: ibm.com
The platform provides a no-code interface with Watson Assistant’s dialog builder to design conversation flows. It also has more advanced options for data scientists to plug in machine learning models if desired.
Cost is one frequently mentioned drawback for small and mid-size businesses. IBM’s pricing is usage-based and requires higher plans for full features, which can be on the expensive side.
Some reviewers also note that certain response types or chatbot elements, like buttons and carousels, were not as easily implemented out of the box and needed custom workarounds.
9. Tidio Lyro
Tidio is a customer service platform popular with small and mid-sized businesses. Lyro is designed as an out-of-the-box conversational AI chatbot that can be added to your website.
Lyro is powered by a large language model and Tidio’s own natural language processing engine. It strictly sticks to the information you provide and can handle common support queries, track orders, and has vision AI capabilities.
Image Source: tidio.com
While Lyro is powerful, its advanced features may require higher-tier plans, which can be limiting for small businesses on a tight budget. There can also be a slight learning curve when customizing complex automation sequences.
10. Zoho Zia
Zoho Zia is the AI assistant integrated across Zoho’s suite of business applications. It serves as an AI agent inside Zoho Desk to help customers and support agents.
Zia can interact with customers via chat or email to answer questions by pulling answers from your company’s knowledge base and past tickets. It also uses sentiment analysis to gauge if a customer is unhappy or if an issue is urgent, and can escalate or notify a human when needed.
Image Source: zoho.com
For internal teams, Zia provides AI-powered insights. It will auto-tag and categorize tickets, offer agents a summary of a customer’s issue, and suggest the best solution article.
But one commonly cited issue is limited customization, as it can be challenging to adjust the AI's behavior to unique business workflows. Zia can also struggle with very complex or ambiguous queries, occasionally failing to interpret what the user means if the question isn’t direct.
Types of AI Agents
AI agents range from simple reactive bots to sophisticated learning systems. Understanding the different types of AI agents will help you match the right solution to your needs:
Rule-Based Reflex Agents
These agents follow simple if-then rules. They react to specific triggers with pre-set responses, much like a basic FAQ chatbot.
For example, a rule-based bot might always reply with store hours when it sees the word “hours.” They’re easy to set up but lack memory and cannot adapt, which is best for various tasks that are simple and repetitive.
Model-Based Agents
These agents have a notion of state as they remember past inputs to inform the current action. For instance, if a customer says "I have an issue with my order" and later types "it hasn't arrived," the agent recalls the context (the "order issue") and provides a relevant follow-up.
Keeping track of context makes these bots better for multi-step conversations, like troubleshooting flows or order tracking.
Goal-Oriented Agents
These AI agents make decisions that move toward a defined goal. For example, a goal-driven sales chatbot might have the objective to get a demo scheduled.
It will ask questions and offer timeslots with the ultimate goal of booking that meeting. These agents evaluate actions by how much they bring the agent closer to the goal.
Utility-Based Agents
These agents use a utility function to choose the best among many possible actions, scoring options by expected usefulness.
For example, a product recommendation bot might consider multiple factors (customer preferences, price, popularity, etc.) and select the recommendation with the highest utility score.
Learning Agents
The most advanced category, learning agents, use machine learning to improve their performance over time. They have components to explore new actions and a performance element that updates based on what they learn.
These agents might include built-in debugging tools to refine their responses after each interaction. Over time, they become more accurate and effective in helping customers or teams solve problems.
Common Business Use Cases for AI Agents
AI agents are versatile and can be found improving operations across virtually every industry. Here are some of the most impactful use cases and applications of AI agents in businesses:
Customer Support and Service
AI in customer service can handle large volumes of inquiries on websites, mobile apps, and messaging platforms. AI agents for customer service answer FAQs, help users troubleshoot issues, and can escalate complex tasks to human staff when needed.
These agents understand customer intent and provide relevant answers, pulling from your knowledge base or FAQs. Many ecommerce sites and SaaS companies use AI-supported chatbots to great effect.
Denser’s AI agents are designed to build AI agents that respond with context-aware replies and hand off to human agents when necessary. Request a product demo or sign up for a free trial today!
Sales and Marketing Assistants
AI sales chatbots can act as virtual sales agents or marketing assistants. They qualify leads by asking questions, recommending products or content, and helping schedule sales calls.
In marketing, AI outreach agents can send personalized follow-up emails or messages, track customer engagement, and help nurture leads through the funnel.
These agents use past browsing behavior or CRM info to tailor their approach. It improves results while allowing human teams to focus on higher-level strategy and write better campaigns.
You can also run these agents inside a browser to make them easy to access and deploy across your website or digital platform.
Ecommerce and Retail
Online retail uses AI agents for everything from product recommendation bots to virtual shopping assistants. Retail AI chatbots on an ecommerce site can guide customers to find products that fit their needs, answer questions about orders or inventory, and handle reordering.
Some advanced ecommerce agents adjust prices or offer discounts in real time based on demand and user behavior. These uses reduce the load on customer service and create a more interactive shopping experience.
Healthcare Assistants
Clinics and healthcare providers employ AI agents to speed up patient interaction and pre-visit processes.
Typical examples are symptom-checker chatbots that ask patients about symptoms and provide preliminary advice or triage, such as: “If you have X, you might need to schedule an appointment.”
AI agents for healthcare also assist with appointment booking, sending reminders, and answering health FAQs (e.g., “What’s the prep for my blood test?”). These agents help reduce staff workload and ensure patients get timely information.
Hospitals have also started using AI agents to gather patient history or screen for certain conditions before the doctor ever speaks to the patient. Some research teams experiment with open-source healthcare agents to ensure flexibility in deployment and data control.
Education and Training
In e-learning platforms and corporate training, AI agents serve as virtual tutors or assistants. They can answer student questions 24/7, provide feedback on quizzes, or grade simple assignments.
For example, an AI chatbot for education institutions might guide a student through a complex math problem by providing hints, while another agent auto-grades their practice tests.
Businesses also use training bots to onboard new employees, answer HR questions, or help them find resources.
Operations and Logistics
In supply chain and logistics, agents can monitor inventory levels, track shipments, or automatically reroute deliveries when there’s a disruption.
For example, a logistics bot might detect a delay at a warehouse and proactively reorder stock or update delivery estimates.
Internal operations agents can also assist employees, such as an IT support chatbot that helps staff reset passwords or file tech support tickets without waiting for helpdesk staff.
Finance and Security
AI is used in fintech for tasks like fraud detection and customer account support. Fintech chatbots can monitor transactions in real time and flag unusual activity, automatically freeze a card, and alert the user for confirmation.
Banks also deploy chat agents to answer customer questions about account balances, guide them through loan applications, or help with budgeting tips. These agents often connect with internal systems to execute transactions or update records securely.
Human Resources and Internal Helpdesks
AI in HR helps answer common questions about company policy, assists with benefits enrollment, or schedules interviews with job candidates. Internal knowledge base agents help employees find information or documentation.
Best Practices for Implementing AI Agents Successfully
The way you implement and manage your AI agent will determine its success. Here are some best practices and tips to make sure your AI agent delivers real results:
Start With a Narrow Focus
When you first deploy an AI agent, begin with a specific, well-defined use case or task. For example, you can launch it to handle password reset requests or basic FAQ answers initially.
Starting small helps you validate that the agent works correctly and lets it gather data in a controlled scope.
You can then gradually expand its responsibilities as it proves itself. This phased approach prevents the bot from getting overwhelmed or going wrong in complex scenarios early on.
Ensure High-Quality Knowledge Base/Data
AI agents are only as good as the information they have. Before launching, you need to audit the data or content you’ll feed into the agent. Clean up any outdated FAQs, make sure your product info is current, and fill knowledge gaps where you know customers ask questions.
If you’re connecting to databases, check that the data is accurate and accessible. This kind of upfront research makes sure your AI agent delivers consistent answers and doesn’t rely on assumptions.
Define Clear Escalation Rules
No matter how good your AI agent is, there will be questions or situations it can’t handle. You need to plan for these by defining when and how the bot hands off to a human.
You might decide that if an AI agent sees a customer mention “cancel account” or detects very negative sentiment, it should tag a human agent to step in immediately. Set up triggers such as “if the AI provides two answers and the user is still unhappy, route to live chat.”
Make sure the escalation process is smooth. The human agent should get the conversation history and context so the customer doesn’t have to repeat themselves.
Test in a Sandbox Environment
Before fully rolling out your AI agent to all users, use a staging or sandbox setup to simulate real interactions without impact on actual customers.
You may have team members throw sample questions or feed it historical chat logs to see how it responds. This phase also helps evaluate workflow automations under safe conditions, so you can catch misfires before they affect real users.
Monitor and Tune Performance Continuously
Once your AI agent is live, you need to assign someone on your team to regularly monitor the bot’s performance via dashboards and conversation transcripts. Watch metrics like resolution rate, confusion rate, user ratings, and any escalation frequencies.
You need to make performance reviews part of your regular AI workflows. This helps you catch weak points and refine your agent’s behavior, so it continues to deliver value in a real-world setting.
Intelligent AI Agents Without the Complex Setup—Choose Denser!
AI agents are becoming essential for running smarter, faster businesses. But most platforms feel too complex, require advanced setup, or only solve one small part of the problem.
Denser makes it easy to build intelligent agents that work across departments, from automating customer support to simplifying operations and assisting with internal tasks.
Unlike generic chatbot tools, Denser goes beyond scripts. It uses RAG technology to pull real answers from your own documents, knowledge base, or website.
Each agent is built to learn, adapt, and grow with your needs. They integrate easily with the tools you already use and help your team save time and stay focused on higher-value work.
Request a product demo or sign up for a free trial and see how it transforms your support team’s efficiency!
FAQs About Best AI Agents
Who are the Big 4 AI agents?
The “Big 4” AI agents leading the space right now are:
- Operator by OpenAI
- Devin AI by Cognition Labs
- Claude by Anthropic
- Nova Act by Amazon
Each focuses on different capabilities like tool use, software development, reasoning, and task execution.
What is the best AI sales agent?
There are a few AI agents built for sales, but most still need a heavy setup or are tied to complex ecosystems.
If you're looking for something smarter and easier to deploy, DenserBot is your ideal AI teammate. It can qualify leads, follow up, recommend products, and hand off warm prospects to sales teams in real time.
What is the best AI code agent?
Some platforms, like Devin and Claude, are designed for developers. Still, if you want a flexible solution that can assist with technical workflows and customer-facing tasks, Denser is a better fit.
You don’t need to be a developer to build with it, and it supports both simple logic and advanced flows, which makes it helpful for growing teams with limited technical resources.