Dataset Transformation & Sanitization

You bought the data.
Can you use it?

You bought the data.
Can you use it?

Proprietary data is a premium asset, and it is often the reason the deal happened. It is also the part of the target most likely to carry obligations you did not sign up for. We transform acquired data so you keep the value and shed the liability.

The approach

Remediation is not a first-timer’s job

The old way

Hand it back to the target

Remediation gets handed to the company being acquired, who are solving this problem for the first time, under time pressure, with no comparison set. You inherit whatever they produce.

The old way

Hand it back to the target

Remediation gets handed to the company being acquired, who are solving this problem for the first time, under time pressure, with no comparison set. You inherit whatever they produce.

Our approach

Transform, then escrow the source

Tech DNA takes the source data and returns a sanitized version, using the strongest de-identification techniques available. You keep the value you want and shed the liability you do not. Source versions can be held in escrow so nothing is lost and nothing is exposed.

Why it matters

Planning to use the data after close?

If any of these are on your roadmap, the acquired dataset needs to be properly anonymized or de-identified first.

If any of these are on your roadmap, the acquired dataset needs to be properly anonymized or de-identified first.

LLM training

Reference models

Drift tracking

Retrieval and embeddings

Data products

Test and analytics environments

Questions we get

Frequently asked

What are the privacy risks of buying a dataset in an acquisition?

Can we train AI models on acquired customer data?

What is the difference between anonymization and de-identification?

Take the value, leave the liability

Tell us what you acquired.

Tell us what you acquired.

Describe the dataset and what you intend to do with it. We will tell you what transformation it needs and what it takes to get there.

Describe the dataset and what you intend to do with it. We will tell you what transformation it needs and what it takes to get there.