AI Agent Development
AI agent systems put AI agents to work inside a business, handling tasks such as customer conversations, request routing and document preparation within rules the business sets. Digital Hub's core team includes an agent builder, a chatbot developer and a data scientist.
Every business has messages that staff answer the same way a hundred times a week. AI agent development turns that repeated work into a system that handles it within rules the business controls, and passes the rest to a person.
AI agent systems put AI agents to work inside a business, handling tasks such as customer conversations, request routing and document preparation. They are one of the sub-services of Digital Hub’s CRM, ERP and AI Systems service. Digital Hub has an agent builder, a chatbot developer and a data scientist on its core team, and builds agent systems for companies that want repeated work handled by software.
What problems does AI agent development solve?
AI agent development solves the problem of skilled staff spending their time on repeated tasks. It helps when:
- The same questions arrive again and again through chat or email.
- Requests must be sorted and sent to the right person before anyone can start.
- Documents follow a standard form but still take time to prepare.
- Customers wait for an answer outside working hours.
An agent handles the routine cases and passes the others on, so people spend their time where judgment is needed.
What Digital Hub delivers in AI agent systems
An AI agent project delivers a working agent built to the scope document. Depending on the project, that includes:
- The tasks the agent handles, and the limits on what it may say and do
- The information and systems it can use
- A handover path to a person for cases it should not handle
- Testing with real examples, then a walkthrough so your team can run it
Agents are built with the OpenAI and Claude APIs, with n8n and Make for automation and Voiceflow or Dialogflow for chatbots. The rest of the toolset is chosen per project.
Tools for AI agent systems
These are the tools Digital Hub uses most for agents and chatbots. The rest of the toolset is chosen per project.
AI models
- OpenAI API
- Claude API
Automation
- n8n
- Make
Chatbots
- Voiceflow
- Dialogflow
Databases
- MySQL
- PostgreSQL
- MongoDB
- Firebase
How an AI agent project runs
The same seven-step process runs on every Digital Hub project, whatever the service. For an AI agent system it works like this.
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Step 1
Discovery call
We go through the project in detail, the budget and the timeline. For an agent, that covers the tasks to hand over, the volume and the systems involved.
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Step 2
Proposal and scope
A written proposal and a scope document, so both sides know exactly what is being built. The scope states what the agent may do and where it hands over to a person.
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Step 3
Milestone plan
The scope is broken into milestones, each with its own deliverable and date. Work begins on an advance of 50 to 70 percent, taken in milestones only on large projects, and the balance is paid before delivery, after your final test.
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Step 4
Build, milestone by milestone
Work is delivered one milestone at a time. Each is reviewed and signed off before the next one starts, so nothing is discovered at the end. For example, one task is signed off before the agent takes on the next.
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Step 5
Testing and handover
Everything is tested, then handed over with a walkthrough so the client's own team can run it. The agent is tested against real examples before it meets customers.
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Step 6
Launch
The agent goes live on the channels in scope.
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Step 7
Support after launch
One month on short projects, three months on long ones. Longer cover is available as a retainer.
How long does an AI agent take, and what affects the cost?
An AI agent system typically takes 4 to 8 weeks at Digital Hub. That is the normal range, not a best case. Scope moves it: more tasks, more connected systems and more channels make the project longer.
Digital Hub publishes no prices or packages. These factors shape the quote.
| Factor | How it changes the quote | |
|---|---|---|
| Number of tasks | Each task the agent handles needs design, limits and testing. | — |
| Connected systems | An agent that reads and updates other systems needs each connection built and tested. | — |
| Channels | Web chat, messaging apps and email each need their own setup. | — |
| Handover rules | The more cases the agent must pass to a person, the more routing logic is built. | — |
| Testing | More cases and more varied inputs need more testing before launch. | — |
Related CRM, ERP and AI services
Agents often work with AI automation, which removes repeated steps behind the scenes, and a custom CRM, which holds the customer record the agent reads and updates.
Start an AI agent project
Describe the tasks you want to hand over, and you will get a written proposal and scope.
Questions
What is an AI agent?
An AI agent is software in which an AI model takes actions toward a goal, such as answering a customer, routing a request or preparing a document, instead of only producing text on demand. A business sets the agent’s limits, the information it can use and the actions it is allowed to take.
What is the difference between a chatbot and an AI agent?
A chatbot mainly holds a conversation. An AI agent can also act, for example by looking up an order, updating a record or passing a case to a person. Many systems combine both. Digital Hub’s core team includes a chatbot developer and an agent builder, so projects can range from one to the other.
What can an AI agent do for a business?
An agent can take over repeated tasks that follow clear rules, such as answering common questions, sorting incoming requests or drafting standard documents. People then handle the cases that need judgment. What an agent should do in your business is decided on the discovery call, by looking at where staff time goes.
How long does it take to build an AI agent system?
An AI agent system typically takes 4 to 8 weeks at Digital Hub. That is the normal range, not a best case. What the agent must do, which systems it connects to and how much testing the cases need move it, and the work is delivered in milestones, each signed off before the next one starts.
Is it safe to let an AI agent talk to customers?
It is safe when the agent has clear limits and a way to hand over to a person. The business decides what the agent can say and do, and the system is tested before it meets customers. Digital Hub builds those limits and the handover into the scope and tests them with real examples.