GBCORP BLOG · AI
AI Agents Company: Software That Takes the Next Step Itself
An AI agent is a model that does not only answer but acts: reads the request, looks something up, fills the form, sends the reply, and stops when it should. An AI agents company is judged on the stopping part.
An AI agent is a model step that is given tools, such as search a catalogue, read a record, draft a message, create a task, and permission to use them in sequence to complete a job. GBCORP builds agents inside the business software it already runs, with the same discipline as any AI step: an evaluation set, a review screen, measured accuracy, tracked cost, and limits on what the agent may do without a person.
What an agent does in business terms
| Agent | What it does | Where |
|---|---|---|
| Customer service agent | Reads the message, checks the order, drafts the reply, escalates when unsure | Support inbox |
| Booking agent | Understands the request, checks availability, proposes slots, books on confirmation | Front desk |
| Back-office agent | Reads documents, fills records, flags exceptions, files the result | Finance, logistics |
| Research agent | Gathers facts from the company’s own sources and drafts a brief with citations | Sales, management |
Tools and permissions
An agent is only as safe as the tools it is given. Read tools are granted freely; write tools, such as send, book, pay, delete, are granted one at a time, with limits, and behind a review step until the numbers justify removing it. Every tool call is logged with what the agent saw and did, so a person can audit any outcome.
Review, limits and stopping
An agent must know when it does not know. Confidence below a threshold, a request outside its scope, a sum above a limit, a customer asking for a person: each hands the job to a human with the context attached. GBCORP builds these rules first, because an agent that never stops is a liability, and one that stops well saves most of the time anyway.
Where agents pay first
Queues with volume, repetition and clear rules: support inboxes, booking requests, document processing, order checks, internal requests. The agent takes the first pass, the person keeps the decisions that matter, and the weekly report shows time saved and accuracy per task.
Checklist before building an agent
- The one job, with fifty to two hundred real examples and their correct outcomes.
- The tools the agent needs, read and write, listed.
- The limits: amounts, actions, topics it must hand over.
- Where the review screen sits at first.
- What is logged and who audits it.
- The number that proves it: time to resolve, accuracy, escalation rate.
The numbers to expect
Scoping in one week. A first agent with read tools and a review step in four to eight weeks at a fixed price; write tools added as accuracy holds. Weekly accuracy, cost and escalation reports. Customised or more complex functionality is quoted separately before any work starts.
A worked example
A property management company’s inbox receives several hundred tenant messages a week. The agent reads each message, looks up the tenant and the property, classifies the request, drafts a reply or a work order, and, for routine cases, files it. At first every action passes a review screen; the coordinator confirms or corrects, and the corrections join the evaluation set. After six weeks, routine categories post without review; anything mentioning safety, money above a limit, or a request to speak to a person goes straight to a human with the context attached. Response time falls from a day to under an hour, and the coordinator handles exceptions rather than the whole inbox.
Cost and control
An agent calls a model several times per job, so cost per job is tracked from the first week and shown beside accuracy and escalation rate. Tools are granted one at a time; limits are set in the console, not in code; and an agent can be paused for a category with one switch. The evaluation set runs on every change, so a model swap or a prompt change is measured before it is live. This is ordinary operations for a component that happens to reason, and it is why GBCORP prices it as a plan.
Agents inside existing software
An agent is most useful where the work already is: the support console, the booking screen, the document queue. GBCORP adds agents as releases inside the client’s existing app or console on its engine, with the same accounts, roles and audit history, so the person reviewing the agent’s work is in the screen they already use. An agent bolted on beside the software is one more tab nobody opens.
Where the data goes
The agent runs in a cloud project in the client’s name. Prompts and documents go to a model provider only for the request and are not used for training under the terms GBCORP configures. Sensitive fields are masked before they leave. Every tool call and model call is logged, so a customer’s security team gets a plain answer.
Questions to ask any AI agents company
Show me an agent running in production and its weekly report. Which tools does it have, and which write tools were granted after the review period rather than before. What happens when it is unsure, and show me a case where it handed over. How is cost per job tracked and who sees it. Can the model behind it be swapped without rebuilding. What is logged, and can we audit any outcome. A company that answers all six with screens rather than slides has built agents that businesses rely on; one that cannot has built a demo.
Questions we hear first
Is an agent different from a chatbot?
A chatbot answers; an agent acts, using tools, within limits, and hands over when it should.
Can an agent make payments or send e-mails?
Only with a write tool granted deliberately, with limits, and after the review step has shown it is safe.
What happens when it is wrong?
The review step catches it at first; later, the log shows what happened and the case joins the evaluation set.
Which models?
Commercial models behind an interface, swappable; no client data used for training.
Where to start
The GBCORP AI Development and Automation product is the priced starting point; the GBCORP AI development hub sets out the method. For the answering side, read what an AI chatbot company should deliver.
GBCORP operates across 17 countries on 4 continents through six pillars: AI & IT, Innovation, Sustainability, Infrastructure, Business Lounge, and EV's & Solutions.
