Years of imports, half-typed tags and duplicates make a CRM hard to use. This demo simulates the cleanup process we run on a real database: agree on the rules, tag with evidence, review every doubt with a person, and report the result. On a real database it is a guided project in clear steps: AI does the heavy reading and your team makes the calls. Here you walk through it in a few minutes, with invented contacts.
Nobody did anything wrong. Tags were typed by different people over the years, leads came in from several imports, and nobody has ten free hours to fix it.
| Contact | Tags today | Notes | Last activity |
|---|
Nothing is tagged from guesswork. Before a single contact is touched, we sit down with the team and write the rules on one page. Every business sorts its contacts differently, so this is where your knowledge counts. It usually takes one conversation. Below is the rulebook used in this demo.
In a real project we start with a small test batch for you to look over, adjust the rules, and then do the full run with a backup. AI does the reading, so your part stays small. The simulation shows you the result in a few seconds.
The words that justify each tag sit right next to it, so you can spot-check any contact in two seconds.
| Contact | New tags | Why (evidence from the notes) | Old tags (kept in backup) |
|---|
These contacts did not have clear evidence, so they were set aside instead of guessed. Each one comes with a suggestion and the reason for the doubt. In a real project we go through this list with you. Try it: approve or pick the right answer.
With consistent tags, the lists you always wanted finally work. Click a list to see who is in it.
| Contact | Tags | Notes | Last activity |
|---|
Once the data is clean, an AI assistant can read it every morning and tell you who to call and why. This example was put together from the contacts above.
A cleanup is only worth paying for if you can check it. Every project ends with a one-page report like this.
This page is a simulation with invented contacts. With your CRM the path is the same: AI does the heavy reading, we do the checking, and you make the decisions in a few short check-ins.
One working session to agree on the categories and what counts as evidence.
We tag a small sample with AI. You look it over and we adjust the rules until the result is right.
The full run produces a proposal. You answer the doubts. Only then is the CRM updated, with a backup.
New contacts are tagged as they arrive and the morning briefing keeps the lists in use.
Tell us which CRM you use and how many contacts you have. If it is not something we would do well, we will say so.
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