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What we build

Software only pays off when people use it.

We train your team on the software we build, on their real work, and we stay on to run it.

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AI enablement means getting your whole company to use AI well. DoubleChecked trains your people by role, on their real work, writes one set of rules for how AI is used in your company, and stays on to run and improve the software afterward. You end up with trained staff, written rules and a partner who stays on to run it.

What does enablement mean in plain terms?

Most firms already have people trying AI on their own, each in a different way, with no shared rules. Enablement fixes that. We teach each role to use AI on the work it does every day, we write down what may and may not go into AI, and we stay on afterward so the training and the rules keep up as the tools change.

Train the teamBy role, on the software and on AI
Write the rulesOne standard for how AI is used
Stay on to run itWe run it and keep improving it

Is it the right fit?

It fits when

  • People are already using AI, but each in their own way and with no written rules.
  • Partners or owners want a clear answer to what may go into AI and what may not.
  • You have software coming, or already running, and want the people who use it to be ready.
  • Managers need a way to judge work that AI helped produce.
  • You want the training to continue as tools change, not end after one day.

It is the wrong tool when

  • Nobody in the company intends to use AI in their work.
  • You want a single generic slide deck with no link to your actual work.
  • Leadership has not decided whether AI may be used at all, and wants training to make that decision for it.
  • A short, standard course from a general training provider already covers what the team needs.

What can you do for a firm like ours?

These ten examples show the kind of enablement work we can do. They are illustrations of the work, not client stories. Each one is about a specific job, and each one leaves the decisions with your people.

CPA and accounting firms

Example

A role based training plan for a tax season team

Today
Preparers, reviewers and administrators each try AI on their own, in the busiest weeks, with no shared method.
What we do
We write a plan by role, with short sessions on the real work of each one, such as client organizers, workpaper notes and reviewer questions, and self-guided modules for the rest.
Your people still own
The partner in charge decides which tasks AI may help with.
Example

A review checklist for AI assisted work

Today
A reviewer cannot tell which parts of a draft or a workpaper AI helped with, so each reviewer checks in a different way.
What we do
We write one checklist for the firm: what to verify against source documents, what to note on the file, and when to send work back.
Your people still own
The reviewer signs off on the work, as always.

Investment advisers and asset managers

Example

An acceptable use policy for AI, written with the partners

Today
Staff ask what they are allowed to do with AI, and the answers depend on whom they ask.
What we do
We hold working sessions with the partners and write a plain policy: approved uses, forbidden uses, who approves new ones and how an exception is recorded.
Your people still own
The partners adopt the policy and own every exception.
Example

A prompt library for an advisory firm's recurring letters

Today
Advisers write the same client letters each quarter, and each one asks AI for help in a different way.
What we do
We collect the letters the firm sends most, write tested instructions for each, and teach advisers how to adjust them for a client.
Your people still own
The adviser reads, edits and sends every letter.

Law firms

Example

A guide to what may go into AI for client data

Today
Lawyers and staff are unsure which matter documents, names and facts may be pasted into an AI tool.
What we do
We write a one page guide with clear categories, worked cases from the firm's own practice areas, and what to do when a case is not covered.
Your people still own
The responsible attorney decides how the guide applies to a matter.
Example

A manager's guide to checking AI output

Today
Senior lawyers review drafts without knowing how AI errors tend to look, such as a citation that reads well but does not exist.
What we do
We run a session for senior lawyers and write a short guide on what to check, how to ask juniors about their method and when to ask for a rewrite.
Your people still own
The supervising lawyer remains responsible for the work.

Mortgage and lending

Example

Onboarding for new hires

Today
New processors and underwriters learn the firm's way of using AI by watching whoever sits nearby.
What we do
We build an onboarding path: the firm's rules on day one, a role module in the first weeks, and a short check that records who has finished it.
Your people still own
The hiring manager confirms that each new person is ready.
Example

A readiness review before a wider rollout

Today
A pilot team has used AI on loan files, and leadership wants to extend it to every branch without knowing what is in place.
What we do
We review the rules, training, access and record keeping, and write a short list of gaps in the order they should be closed.
Your people still own
Leadership decides whether and when to extend the rollout.

Operations-heavy businesses

Example

A champion programme, so each department has one trained person

Today
Dispatch, billing and the front desk each have questions about AI, and nobody inside the department can answer them.
What we do
We train one champion per department in more depth, give them a shared set of materials, and hold a regular call where they bring questions and share what worked.
Your people still own
Each department head chooses the champion and the tasks they will cover.
Example

A quarterly refresh as the tools change

Today
The training was done once, the tools have changed since, and the written rules no longer match what people do.
What we do
Each quarter we review what changed, update the rules and training materials, and brief the champions on what is different.
Your people still own
The owner approves each change to the rules.

Want your team using AI well?

Tell us who needs training, and which rules you wish you had.

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Built and running

This is real work, stated as plainly as we can state it.

Built and running

AI Launchpad

What it does
AI Launchpad is our training and certification program for getting a whole company using AI well. It offers courses by role, certification and a record of completion.
Where it stands
It is in use with early clients and still being built out.
See AI Launchpad on Solutions
Built and running

A dumpster rental company: front desk answer book

What it does
A front desk answer book for prices, service area and policies. It runs as skills in the company's own Claude workspace.
A person still decides
The skills were in daily use from the first day, and office administration works through the exceptions.
Read the story

How does it work?

Step 1ScopeOne working session. A plan and a fixed price.
Step 2BuildThe rules, the materials and the modules, written on your own work.
Step 3LaunchYour people trained on their real work.
Step 4RunRefreshed, watched and improved.

The plan sets the timeline. A fixed price follows one working session.

The steps in order

  • 1. Listen

    We learn who does what, and how AI is used today, officially or not.

  • 2. Draft the rules

    We write the acceptable use rules and the data guide with your leaders.

  • 3. Build the materials

    Role modules, prompt libraries and checklists, made from your real documents and tasks.

  • 4. Train by role

    Live sessions, with self-guided modules for people who need to catch up.

  • 5. Name the champions

    One trained person in each department who answers day to day questions.

  • 6. Keep it current

    We stay on to refresh the rules and training as the tools change.

The five training tracks

  • Foundations

    For everyone. The shared basics.

  • Role-specific

    For each job, on daily tasks.

  • Power user

    For people who build their own workflows.

  • Champion

    The go-to person in each team.

  • Manager

    For judging AI-assisted work.

Delivered live, with self-guided modules, on your real work.

What do you get at handover?

  • Written rules

    One standard for how AI is used in your company, and what it may be used for.

  • Training for each role

    Live sessions and self-guided modules, on your own work.

  • A record of who is ready

    A record of completion for each person and track.

  • Trained champions

    A go-to person in each team.

  • A named security review

    Before any software we build goes live for your people.

  • Someone to call

    DoubleChecked stays on to run and improve what it built.

How is our data handled?

Training uses your real work, so we treat your data with care. AI that we build for you runs in a private environment you control, and company data does not go to public AI services. We contract directly with Anthropic under commercial terms and a data processing agreement. Zero data retention is available through the API, not the chat interface. A named security review happens before launch.

Who can get inSingle sign-on and roles
Where it runsA private environment you control
What it may doWritten rules, checked before it confirms an action
Who signs offA person at your company
What it didAn append-only record
Read how we handle security

What does it sit alongside?

Enablement is about the tools your team already uses. The training and the rules are written around them, by category.

  • Email and calendar

    Where most drafting and scheduling starts.

  • Document management

    Where client files and drafts are kept.

  • File shares

    Shared folders and drives.

  • CRM

    Client contacts and history.

  • Spreadsheets

    Where much of the analysis is done.

  • Line of business systems

    The software your industry runs on.

Questions buyers ask

Questions buyers ask

What are the training tracks?

There are five: Foundations, Role-specific, Power user, Champion and Manager. They are delivered live, with self-guided modules, on your real work.

What is AI Launchpad?

AI Launchpad is DoubleChecked's training and certification program: courses by role, certification and a record of completion. It is in use with early clients and still being built out.

How long does it take?

The plan sets the timeline, and we agree it with you after the working session. The training is delivered on your real work, so it fits around your busy periods.

What will it cost?

Every project gets a fixed price after one working session, and you know the number before the work starts. A working session is 45 minutes on one idea from your company.

Where does our data go?

AI we build runs in a private environment you control, and company data does not go to public AI services. Training uses your own documents inside that boundary. Security covers the rest.

What do you need from us to start?

One working session, 45 minutes on one idea from your company. DoubleChecked signs an NDA before that first session and replies within one business day.

Who checks that the training worked?

A record of completion shows who has finished each track. Your managers and champions judge how people use AI in daily work, and we help refresh the training when it falls short.

Dumpster rental story

The front desk answer book, worked daily by office administration.

Read the story

AI Launchpad

Courses by role, certification and a record of completion.

See AI Launchpad on Solutions

Private AI workspaces

A workspace where your team can use AI on client records.

See examples

Tell us what you want built.

A working session is 45 minutes on one idea from your company: what to build, what it needs, and what it would cost.

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  • A fixed price before we build
  • Your data stays in your environment
  • A record of every action
  • Reference calls under NDA
  • NDA before the first session
  • Since 2019
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