AI Agent Development

Your team may answer the same questions every day: Has my payment gone through? Where is my order? Can I get a copy of my receipt? A basic chatbot might explain the process, but a staff member still has to open the system, find the record and respond.

An AI agent can be designed to take on more of that work. For example, when a customer asks about a payment, the agent could identify the transaction, check its actual status in your system and explain the result. If the record is missing or a refund is requested, it could pass the case to a staff member instead of making a decision it has no authority to make.

The difficult part is not getting AI to produce a convincing reply. It is connecting the reply to accurate information, deciding which actions are permitted and making sure a mistake does not become a wrong payment, changed record or misleading promise.

Mfidie Solutions approaches this as a software development problem. We identify the task, examine the systems involved and build the connections and safeguards around it. We have built tools that fill forms on client websites, customer-service AI connected to business databases that can update records, process requests and create transactions, and AI-assisted content moderation. These are different jobs, but they share a practical requirement: the software must use the right information and operate within defined limits. Our experience developing payment integrations, WhatsApp workflows and applications with shared backends also informs that work. We consider whether ordinary software rules would solve a problem more reliably than AI.

• Customers can get help with routine enquiries outside office hours when the connected systems are available.
• Answers can be checked against transaction, customer or service records instead of relying on generated text alone.
• Staff spend less time searching through systems for straightforward information.
• Requests involving uncertainty, exceptions or sensitive actions can be passed to the right person.
• Your business can review what the agent checked, which actions it took and where it needed help.

• A clearly defined use case, such as completing forms on a client website, answering customer questions, processing requests, updating records, creating transactions through approved integrations or helping review submitted content.
• An agent connected to the relevant parts of your website, business application, database or messaging channel.
• Rules specifying what the agent may read, what it may change and which actions require approval.
• Responses grounded in available records, with a clear fallback when information cannot be confirmed.
• Logs and staff handover paths so your team can investigate problems and take over a conversation.
• Testing with realistic requests, including incomplete details, incorrect information and repeated messages.
• Deployment, monitoring and ongoing improvements as the business process changes.

1. We start with the task. We look at what customers or staff ask for, how the work is done today and which parts take the most time.
2. We map the information and permissions. We identify the records the agent needs and define which records may be read or updated, which requests and transactions the agent may process, and which actions require human approval.
3. We build the connections. Depending on the task, the agent may work through a website, WhatsApp or an internal application, use existing APIs to retrieve or update records, submit authorised transactions, or enter information into an approved form.
4. We test the difficult cases. We check what happens when a payment is pending, a customer provides the wrong reference or the system is unavailable.
5. We introduce it carefully. We review actual requests, improve the handover process and expand the agent's responsibilities only when the results support doing so.