But while building an AI agent sounds simple in theory, the reality is more complex. This guide explains how AI agents work, what’s involved in building one, where most SMBs get stuck, and how Kleritt can help you turn the idea into a working system that fits your business.
TL;DR
- AI agents use language models and automation to act and make decisions.
- You can build one using APIs, workflow tools, and your own data.
- Challenges include setup complexity, data integration, and ongoing maintenance.
- Kleritt helps SMBs build reliable agents through AI Implementation, Integration, and Automation services.
What Is an AI Agent and How Does It Work?
An AI agent is software that combines artificial intelligence with automation. It can understand prompts, fetch data, take actions (like sending emails or creating reports), and learn from feedback.
For example:
- A customer support agent that answers questions and creates tickets in your CRM.
- A sales assistant that qualifies leads from forms and schedules calls.
- A data agent that summarises reports and alerts your team when numbers change.
Technically, AI agents rely on a language model (such as GPT or Claude) for reasoning, plus integrations with your systems (e.g., Gmail, Notion, HubSpot, or ERP tools) to perform actions.
How to Build an AI Agent
In simple terms, here’s how you could build one yourself:
- Define the task: What should the agent do? Example: answer FAQs or automate lead responses.
- Pick the core AI model: Choose an LLM like OpenAI GPT, Mistral, or Anthropic.
- Connect your tools: Use automation platforms (like n8n, Zapier, or Make) to link the model to your data sources or apps.
- Give it context: Feed it your own company data, such as FAQs, documents, or product details.
- Test and refine: Run scenarios, fix edge cases, and monitor the responses.
Theoretically, anyone can do this. But in practice, SMBs run into issues fast.
Common Pitfalls for SMBs
- Steep learning curve: Tools like n8n and APIs require technical knowledge and logic design.
- Data security: Without the right setup, confidential data may be exposed to third-party systems.
- Integration limits: Connecting your CRM, email, or databases often needs advanced API configuration.
- Maintenance burden: Agents can break when your tools or prompts change.
- Unclear ROI: Without proper planning, the time spent experimenting outweighs the value gained.
That’s why many businesses start with enthusiasm but never launch a stable, usable agent.
How Kleritt Helps You Build a Working AI Agent
At Kleritt, we help small and mid-sized businesses skip the technical frustration and move straight to results.
Here’s how we do it:
- Strategy first: We define clear goals, what the agent should achieve and how it supports your business.
- Implementation: We connect your tools (CRM, email, docs, chat) with the right AI model using low-code automation platforms.
- Integration: We ensure your data stays secure and compliant while the agent accesses only what’s needed.
- Training & monitoring: We fine-tune the prompts, test accuracy, and teach your team how to manage the system.
- Ongoing optimisation: We monitor how the agent performs and improve it over time as your needs evolve.
We combine expertise from our AI Implementation, Automation, and Process Optimisation services, so you get a full solution, not just a prototype.
What You Can Expect
With the right setup, your AI agent can:
- Reduce repetitive workload by 30–50 %.
- Respond instantly to customer or employee requests.
- Improve lead handling, reporting, or data accuracy.
- Save time on everyday admin while maintaining control.
Kleritt ensures your first AI agent is not just a tech experiment, but a dependable assistant built around your actual business goals.
