AI agents and assistants
Agents that work inside your business, under your rules
An AI agent can look things up, draft responses and take actions in your tools. We design agents with clear permissions, human approval for anything consequential, and honest limits.
How it fits together
How a business agent handles a task
Input
Task or question
From a person, an inbox or a system
Rule / check
Check permissions
What this agent may read and do
AI step
Plan and gather
Looks up records and documents it is allowed to use
Human approval
Approve actions
Sends, writes and payments wait for a person
Output
Act and log
Completes the task, records every step
An agent is only as safe as its permissions. We design those first.
In plain terms
What an AI agent means for a business
An agent is software that uses an AI model to work through a task in several steps: understanding the request, finding information, deciding what to do next, and using your tools to do it. An assistant is the same idea with a person driving each step.
What they do
Tasks agents handle well
- Answering staff questions from approved company documents, with sources
- Researching and structuring incoming leads, then drafting the next step
- Triaging support requests and drafting replies for review
- Gathering information from several systems to prepare a report or a case
- Keeping CRM and other records complete and up to date
Permissions and approval
You decide what an agent may do
Read access
Which systems, records and documents the agent can see, often limited by the role of the person using it.
Write access
Which records it may create or change. Many agents start read-only and earn more access once proven.
Approval rules
Customer messages, financial actions and deletions wait for a person unless you explicitly decide otherwise.
Audit trail
Every lookup, decision and action is logged, so you can see exactly what the agent did and why.
Integration
Connected to your systems through controlled tools
Agents never get open access to a system. They use a defined set of actions, such as "look up customer" or "create draft quote", each with its own permissions, built on your systems’ APIs.
Testing and monitoring
Proven before launch, watched after
- Tested against realistic tasks, including the unclear and the out-of-scope
- Checked for answers without support and actions outside its permissions
- Monitored after launch, with logs reviewed and failures followed up
- Improved within the agreed support period as real usage shows gaps
Limitations
What agents cannot do reliably
AI models can produce confident answers that are wrong, and agents can misread an ambiguous request. That is why we limit their permissions, require sources for answers, add approval steps and keep logs. We do not recommend agents running unsupervised where mistakes are costly.
Questions
Common questions
Is an agent the same as a chatbot?
Can an agent run without anyone checking it?
Which AI models do you use?
Have a task an agent should take off your team’s plate?
Tell us about the workflow, the systems involved and what a good outcome looks like. If AI is the right tool, we will show you where to start. If it is not, we will tell you.