You sell data, and owe privacy to the people in it. Twinned records protect your data subjects and are worth more to your buyers.
Solutions
The locked data you could never use. Now you can.
Wherever regulated data stalls an AI project, Nakato can help. It sits as a layer between a company and any AI model, converting sensitive details into twins. The answer comes back with the originals restored. Pick a sector below for more information, or go straight to the problem you have.
By sector
Real decisions. Fictional identities.
Financial services is where Nakato is proven first. The same layer applies wherever a record has to keep its meaning and lose its identity.
Banking
Credit decisions on the full picture
Record · Banking Twinned at query time
| Field | Original stays with you | Twin what the model sees | Preserved |
|---|---|---|---|
| Customer | Margaret Ellis | Eleanor Grant | Preserved — gender, name origin |
| Date of birth | 1961-04-12 | 1959-11-03 | Preserved — age band |
| Sort code | 20-45-11 | 31-08-64 | Preserved — valid format |
| Balance | £18,240.55 | £17,905.12 | Preserved — within 2% |
Credit decisions on the full picture. Strip demographics and you strip the vulnerability signals credit analysis depends on. The twin keeps every signal but removes the identity so the model can reason on realistic records.
The model only ever sees the right-hand column, but the answer you read has the originals restored. Where the two columns match is where details essential to the task are kept. The twin removes what identifies but keeps what is essential.
By problem
Start from the problem you have.
Some problems aren't about a sector, but about what the data is, who it goes to, and who has to sign it off.
Compliance has to sign it off. Where the data goes, what happens when detection is unsure, and how every swap is evidenced.
We intend to be the ones who define how this is done.