An AI agent does a whole task, not one step. It works inside the systems you allow and tells you what it did.
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An AI agent is software that carries out a whole task, not one step. It reads the material, decides within rules you set, acts inside the systems you allow, and writes up the result. It can take over repeatable work such as contract review, month-end preparation and inbox triage, while a person signs off on outputs that matter.
You hand it a job in plain words. It does the job, checks its own work, and shows you the record.
A single AI step answers a question or drafts a paragraph. An agent strings many steps together: it opens the documents, works out what is missing, sends the request, files the reply and tells the right person. It can only touch the systems you allow, and every action is written to a record you can read afterwards.
We will say so when an idea is not worth building. These are the signs we look for.
These ten examples show the kind of whole job an agent can take. They are illustrations of what we can build, not client work. The real builds are further down.
Agents we have built, and that are in use today.
A dumpster rental company
A dumpster rental company
In use at DoubleChecked
In use at DoubleChecked
Client work is anonymized at client request. Reference calls available under NDA.
The plan sets the timeline. For a larger build you can start with a scoping sprint: two weeks and a working prototype on your own documents. The price is fixed after one working session. For an agent, the steps look like this.
Running in your own environment, on your own systems.
An append-only record of every action the agent took.
What the agent may do, what it may not, and where a person decides.
The people who use it, taught on their real work.
A named review of the build before it goes into use.
We run it for you: hosted, watched and improved.
The agent runs in a private environment that your company controls, and client data does not go to public AI services. DoubleChecked contracts directly with Anthropic under commercial terms and a data processing agreement, with no reseller in between. Zero data retention is available through the API, not the chat interface. Read the security page
Inside your environment
Outside
Company data does not go to public AI services.
The plan sets the timeline. After one working session you have a plan and a fixed price. You then see working software early and often during the build, so you are never waiting for a single reveal.
Every project gets a fixed price after one working session, so you know the number before we build. A scoping sprint is an optional first step for larger builds: two weeks and a working prototype on your own documents.
The software runs in a private, client-controlled environment. Client data does not go to public AI services. DoubleChecked contracts directly with Anthropic under commercial terms and a data processing agreement, with no reseller in between.
The software checks before it confirms an action and keeps an append-only record of what it did. A person at your firm reviews and signs off on outputs that matter. Each build gets a security review before launch.
The checks before each action catch many errors, and approval points put a named person in front of the rest. The record shows what the agent did, so the cause can be found and the rules corrected.
A person who knows the job, examples from your own files, a decision on which systems the agent may use, and a named reviewer. Your people are trained on their real work at launch.
That is a rule you set. Where an action is hard to undo, such as saving a payment, we put approval gates in front of it. Every action is recorded either way.
Remittance with two approval gates, and a front desk answer book.
Intake that sorts, names, files and checks case documents.
Routines that run on a schedule, with exceptions set aside.
Everything we build and run.
A working session is 45 minutes on one idea from your company: what to build, what it needs, and what it would cost.
