Paste the client's account, messages and evidence list to get a timeline and spot missing evidence.
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Good for
A client told you a lot at once and you need it in order
Checking for missing evidence before mediation or a hearing
Handing a matter to a colleague who needs to catch up fast
1. Fill in the details
2. Adjust the options
A filled-in example
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Matter name
Company A payment dispute
Material
Client says: contract signed last June, first batch delivered in August, the buyer claimed quality problems and withheld the final payment. Sept 5 the buyer emailed asking to return the goods; we replied on Sept 12 offering a replacement. Since October they stopped answering calls. Evidence: contract, delivery note, emails of Sept 5 and Sept 12.
What it is for
Preparing for mediation
What the AI's answer looks like
Illustrative excerpt: the real answer depends on the AI you use and what you fill in.
| Date | Event | Who | Source | Strength |
|---|---|---|---|---|
| Last June (date to confirm) | Contract signed | Both | Contract | Strong |
| Last August (date to confirm) | First batch delivered | Us | Delivery note | Strong |
| After August (date to confirm) | Buyer claims quality issues, withholds payment | Buyer | Client's account | Weak |
| Sept 5 | Buyer emails asking to return goods | Buyer | Email | Strong |
| Sept 12 | We reply offering a replacement | Us | Email | Strong |
| From October | Buyer stops answering calls | Buyer | Client's account | Weak |
Missing evidence
- The buyer's acceptance or signed receipt
- Anything in writing or photos describing the quality problem
Questions for the client
- When and how was the quality problem first raised?
Tips
Always use code names for the parties, such as Company A or Mr. B
Note where each piece came from (statement, email, contract) so the AI can rate the evidence
Anything marked "date to confirm" is where you need to go back for records
How to use it
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Choose the tone, length and where you will paste it, then press Copy.
Paste it into ChatGPT, Claude, Gemini, DeepSeek or a local model. If the AI asks you questions, answer them and the result gets better.