Format · Chats and tickets

Chat logs, tickets and team messages, safe to test with

Support tickets, live-chat logs and Slack, Teams or Jira exports are what chatbots and AI agents are tested and trained on. They are also full of customer names, order numbers and card numbers customers should never have typed.

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Live chat · ticket 51207Masked in your VPCIllustration

Before

[10:02] Maria L: my card 4417 was charged twice [10:03] Agent Priya: sorry Maria, can you confirm your postcode? [10:03] Maria L: LS6 2AB

After

[10:02] Ava O: my card 0000 was charged twice [10:03] Agent Sam: sorry Ava, can you confirm your postcode? [10:03] Ava O: YO1 7HB

Found in this file

Treatment

Customer name×3Consistent

Agent name×1Consistent

Card, last four×1Keep format

Postcode×1Replace

Policy: Customer data v3 Labelled-sample check passed

What people type into chat

Names and handlesOrder and account numbersCard numbersEmails and phone numbersPostcodesStaff namesComplaints in free textLinks and file names

Where it lives

Zendesk and ServiceNow tickets
Live chat and messaging platforms
Slack and Microsoft Teams exports
Jira issues and comments

What you can do

Engineer-ledSlack exportsEvery channel and message treated by the same policy, with each person or organisation resolved to one replacement across the whole workspace.

Engineer-ledTeams, Jira and ticket exportsMask the text fields and keep threads, authors and timestamps intact, platform by platform.

Engineer-ledSynthetic conversationsGenerate conversations for synthetic customers, including the awkward ones: angry, off-topic, or full of details they shouldn't share.

Why it matters now

Chat and ticket archives are now wanted for AI training, data deals and audits, and every one of them needs the people taken out first.

Chat is also where detectors struggle most: nicknames, handles, typos and numbers split across messages. Check any tool, ours included, against labelled samples.

Used for

Testing AI agents and chatbots Keeping data out of LLMs Sharing and licensing data

Questions about chat and ticket data

Customers type card numbers into chat. Is that covered?

Card numbers have a recognisable shape, so pattern detection finds them in complete form. Numbers split across messages or written in words are harder, so the 48-hour proof tests for them on your own exports.

Do you connect to Slack or Zendesk directly?

The starting point is exports, which keep the data inside your environment. Direct connectors are scoped with you, based on the systems you run.

Can masked conversations still train or test a bot?

Yes, if the replacements are realistic and consistent. "Sorry Ava, can you confirm your postcode?" teaches a bot the same thing as the original; "[NAME], confirm [POSTCODE]" does not.

The platform underneath, in production

Documents run on the same platform banks, insurers and health companies already trust with their data.

Documents and text use the same policies, the same engine and the same deployment as these results.

Banking · test data80%less time to provision test data, with compliant data generated through the API inside CI/CD.Deutsche BankCase study Health · masking20bn+rows masked and subsetted in hours, not weeks, with all manual configuration removed.Global HealthTech leaderCase study

Published results from database and synthetic data work on the Synthesized platform.

Testing a bot on real conversations?

Bring 50 conversations from one export. In 48 hours you'll see them masked, with the evidence.

Get a 48-hour proof