AI agent development for businesses
Each agent reads requests and documents, drafts answers and shows its sources. Your team reviews and approves results before they are sent.
What an AI agent can do
The agent
One job, written down: what comes in, what goes out, what it must never do.
Where it runs
Run by us, or installed on your infrastructure and handed over. Either way, you know in writing which data reaches which AI provider.
Review and connections
A queue for approvals and a record of every decision, connected to your tools through their official APIs.
What changes
TodayRequests wait in a shared inbox.
With AL+Each one is read on arrival, with missing details listed.
TodayEvery reply is written from scratch.
With AL+Drafts come from your price lists and templates, with sources.
TodayYou fear AI sending the wrong thing.
With AL+Nothing goes out until a named person approves it.
From task to implementation
One workflow
We map the steps and where a mistake is expensive. If a simple automation is enough, we say so.
Scope and fixed price
In writing. Running costs, such as hosting and model usage, are estimated separately.
Tested on past work
The agent runs on your past examples before it touches live work.
Live, then maintained
It starts on a share of real work. Models, APIs and prices are watched and the agent updated.
Products built by AL+
KeySend reads each client's Google Ads account every day and writes what changed, with the numbers behind it; the consultant decides what to do. Food & Fit returns an AI meal estimate the user checks and corrects before saving.
Who this is for
A good fit
A task that comes back every day or week, someone to approve it, and tools with an API or export.
Look elsewhere if
Nobody can review the drafts, or you want an agent to act on clients unsupervised.
AI agents by industry: AI agents for marketing agencies, AI agents for accounting firms.
Questions
Does the agent talk to our clients?
Only if you decide so, within limits you approve. By default a person sends every draft. An agent that talks to people tells them it is an AI system.
Where does our data go?
It depends on the setup, and we put it in writing before we build: which systems the agent reads, which AI provider receives what, and where records are kept. Hosting the agent on your servers keeps the agent in your infrastructure; a model from an outside provider still receives the text it processes.
What does it cost to run?
Model usage, hosting and subscriptions depend on volume. They are separate from the build price and estimated with you before you commit.
Further reading
Software needs an owner
Software becomes expensive when nobody clearly owns it. Ownership is a role, not a repository permission, and most struggling systems are missing it.
Which task should an agent prepare?
Describe the task, the documents involved and who checks the result. We establish whether an AI agent or a simpler automation fits.
Or copy the address: paul@alplustech.com