Freezerworks

What runs smoothly at 5,000 samples starts to break at 50,000.

A spreadsheet does not announce the failure. It shows up as:

⚠️ Duplicate IDs
⚠️ Sample locations that no longer match the freezer
⚠️ One person who has quietly become the only reliable record of where things actually are

That person is doing integrity work the system should be doing. And that role does not scale. It does not transfer.

And when they leave, the knowledge often leaves with them.

The labs we have seen navigate this transition well did one thing differently:

✅ They switched architectures before the data became unmanageable, not after.

✅ They moved while the cleanup was still small.

The pattern is consistent. The longer a collection waits, the more cleanup it carries across to the new system.

𝗦𝗰𝗮𝗹𝗲 𝗱𝗼𝗲𝘀 𝗻𝗼𝘁 𝗰𝗿𝗲𝗮𝘁𝗲 𝘁𝗵𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺. 𝗜𝘁 𝗲𝘅𝗽𝗼𝘀𝗲𝘀 𝗶𝘁.

If it takes hours to locate, your audit trail isn’t doing its job. Being able to locate a change on demand is what helps you pass your audit.

Plenty of LIMS and tracking systems log everything, but still leave your team scrambling. The record exists, but you can’t see it clearly.

A usable audit trail makes full sample history available on demand.

Search by sample ID, user, date, instrument, or event type, and export a complete record to PDF or CSV for auditors without system access.

See how Freezerworks pulls a full sample history.
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