AI tools in use, no structure
People use ChatGPT, Claude or Gemini on their own, each in their own way. Some of it saves time, some of it is risky, and nobody knows which is which or what it adds up to.
AI consulting for businesses that want working systems, not a deck.
Many teams already pay for AI tools. What's missing is a clear answer to three questions: where AI saves real hours in your work, what to build first, and what to leave alone. I find those answers in your actual workflows, in one to two weeks, and write them down so you can act on them.
Where it stalls
Three situations that usually bring a company here.
A decision you need to make
A vendor is pitching an AI product, a competitor launched something, or the board asked for an AI plan. You need a grounded answer before you spend, not another demo.
One process that eats someone's week
Quotes, reports, intake, follow-ups. A task that repeats every week, takes hours, and everyone suspects AI could do most of it. Nobody has had the time to check.
What you get
What the AI Leverage Audit delivers.
A short, paid diagnostic built on your real work. Not a generic report: every recommendation points to a task, the person who does it and the hours it takes.
- A map of where the hours go, task by task, and which of those tasks AI can take on.
- A prioritized roadmap: each opportunity scored by time saved, risk and effort.
- The first quick win, scoped so it can start right away.
- A written build-or-buy decision for each item: an existing tool, a setting in a tool you already pay for, or something built for you.
- A short governance checklist: which data may go into which tool, and what needs a person's approval.
- A clear recommendation for the next step, including when the answer is to wait.
Example, for illustration
A sales team spends about 6 hours a week turning incoming emails into quotes. The audit maps the steps, marks which ones a model can draft and which need a person, and scores the process against the other opportunities before anything gets built.
How it runs
Four steps, in one to two weeks.
The audit is the first stage of the Leverage‑to‑Ownership Method.
Kickoff call Leverage
We agree on the scope: which teams, which processes, which tools. You give me access to two or three people and the real workflow.
Mapping sessions Leverage
Short sessions with the people who do the work. I look at the process as it really happens, not at a description of it, and note where the time goes.
Scoring and roadmap Leverage
Each opportunity gets a score for time saved, risk and effort. Quick wins go first, and anything touching clients or money gets a human approval step by design.
Decision meeting
We go through the roadmap together and decide what happens next: you run it yourselves, I train the team, or I build the first systems with you.
The audit stands on its own. You leave with a plan you can run with or without me.
Who brings what
What you provide, and what you own.
What you provide
- One person on your side who owns the project and can make decisions.
- Two or three people who do the work, for short sessions.
- View access to the tools involved, or a screen share where access isn't possible.
- Honest answers about what has been tried and didn't stick.
What you own at the end
- The opportunity map and the scored roadmap, as documents you can edit.
- The build-or-buy decision for each item, with the reasoning.
- The governance checklist for your tools and data.
- The scope of the first quick win, ready to start with me or with anyone else.
Proof
What this looks like in practice.
A digital analytics firm: three AI systems at work
One mapping session, then three systems built on the firm's own Claude account: email triage with replies drafted in the owner's writing style and a folder opened automatically for every new client, meeting summaries with decisions and tasks, and client-branded reports built from analytics data.
All three were running within two weeks of the first working session. Anything that goes to a client stays a draft until the owner sends it. The client's name stays private until they agree to be named.
My own business runs the same way
Agents prepare my meeting summaries, follow-ups, client records and draft replies. I read, correct and approve what goes out. I use what I recommend.
The AI Daily Brief
Every morning a pipeline I built reads about 30 sources, checks each item against its source and publishes up to three updates in Hebrew and English. It runs on its own, within written rules on what it may publish.
Five stages, written down
Every engagement follows the Leverage‑to‑Ownership Method: map, train, build, lock in the rules, hand over. You always know which stage you are in and what you own at the end of it.
Questions
Straight answers, before the first call.
How long does it take?
One to two weeks from the kickoff call to the decision meeting, depending on how many teams and processes are in scope. Your people spend a few hours in total.
What drives the cost?
The number of teams and processes in scope, how many tools are involved, and how much material has to be reviewed. There are no prices on this site: after a 20-minute call you get a scoped proposal in writing.
What happens after the audit?
You decide. Some teams run the roadmap themselves, others ask me to train the team or build the first systems. The audit is useful either way, and there is no commitment to continue.
Will we need to buy new tools?
Often not. Many quick wins are settings in tools you already pay for. When a new tool makes sense, the roadmap names it, and you pay the vendor directly, on your own account.
What about our data?
Wherever possible I look at your processes, not at your clients' data. Access is view-only, limited to what the audit needs, and you can remove it at any time. Nothing is copied into my own accounts.
Does it work in Hebrew?
Yes. The sessions, the documents and the recommendations are in Hebrew or English, as you prefer. Where a tool is weaker in Hebrew, the roadmap says so.
What needs a person's approval?
Anything that leaves the business or can't be undone: messages to clients, payments, changes to records, deletions. The roadmap marks these steps from the start.
Consulting, training or implementation: which do we need?
Consulting answers where to start. Training gets your people using the tools. Implementation builds systems into your daily work. If you are not sure, start with the audit: it shows which of the other two you need, if any.
Related guides
Longer answers to the questions above, from the field notes.
Guide · 15 Oct 2026Where to start with AI: how to choose the first workflow to automateThe first AI workflow decides whether the team trusts the next one. A simple way to choose it: score five recurring tasks on frequency, hours, clear rules, the cost of a mistake and data access, then start where AI drafts and a person approves.Read the guide ››
Guide · 15 Oct 2026What drives the cost of an AI implementation, and how to estimate itThe cost of putting AI to work is set by drivers you can see before anyone quotes: the tools, the systems involved, data quality, exceptions and approvals, volume and upkeep. How to estimate the tool and time side yourself, with a worked example.Read the guide ››
Not a fit
When this is not the right call.
- The business is in survival mode and has no time or budget to change how it works.
- The hope is for AI to fix things without the team taking part.
- What's needed is a single quick fix, not a look at how the work runs.
- What's wanted is a list of ChatGPT tips. The field notes on this site are free and a better fit.
- The people who can approve the work aren't part of the conversation.
Next step
Start with a 20-minute call.
There are no prices on this site. After the first conversation you get a scoped proposal in writing. On WhatsApp, the message opens with a few short questions, so the first reply can already be useful.
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