nth.link is a web-based secure data collaboration tool that lets you and a potential business partner analyze how many rows two data sets have in common while everyone's data remains encrypted (not just at rest/in transit, but even when being analyzed).
Hey everyone!
I'm Andrei, a co-founder of Nth Party and one of the creators of https://nth.link. Big thanks to @matthartman for hunting us!
How often have you worried about what might happen to sensitive data relating to your customers or your organization when you *had* to share it with a business partner or intermediary? Now that new forms of cryptography can be used directly in the browser, you no longer need to worry or take such risks!
nth.link is a web-based secure data collaboration tool that lets you and a business partner analyze how many rows two data sets have in common *while everyone's data remains encrypted at all times* (not just at rest or in transit, but even when the analysis is being performed). We're *not* talking about hashing, here, but secure multi-party computation (https://en.wikipedia.org/wiki/Se...) -- anyone looking at the encrypted ciphertexts will see something different every time.
Whether you'd like to measure the number of common customers (e.g., to determine if a new partnership will be helpful to your business) or to avoid the cost of expensive matching platforms, you can assess new opportunities while eliminating any risk of data exposure.
How does nth.link deliver on its promise?
✅ Complete control: only you can analyze your data with a partner of your choosing.
✅ No 3rd parties or in-the-clear sharing: everyone's data is encrypted *in their own browser* and never decrypted after that.
✅ Aggregate results: only the *number* of rows from your data set that also appear in your partner's data is disclosed, and this is disclosed *only* to you.
How does it work?
📝 You select a CSV file containing the data you'd like to use and (optionally) which column is used to match rows.
🔗 With one click, you encrypt your data and generate a link to send to your partner.
🤝 Your partner selects their data just as you did, and with one click contributes an encrypted version of that data.
🥧 Once they've contributed, you reveal the aggregate results: a measure of the overlap between your two encrypted data sets.
We've spoken to professionals across many industries who routinely need to measure the overlap between data sets:
🏢 M&A firms and buyout funds looking to find if the customers they may acquire are net new.
📈 Sales teams assessing how well they are reaching potential populations of new customers.
📣 CMOs who need to know if target customers are on a partner's list, or if there are likely lookalike customers on the list.
👨👩👧👧 Business Development leads trying to understand if a partner's audience is a good fit.
nth.link is available *for free* for a limited time! Try it as often as you'd like, leave us a comment on what you make of it (or how it can be improved), and follow us @nthparty!
Thanks,
Andrei
As we are aware, there is so much data about us out there. It's pretty exciting that there is now finally a way to companies to continue to work with that data to make relevant, personalized experience, while still keeping that personal data encrypted and private. Maybe this helps marketing become less invasive but no less relevant! @matthartman@nthparty
@matthartman@nthparty@danikadanika Great observation. We hope to make a frictionless privacy experience, as easy as doing what you do today to match the overlap on your spreadsheets, but with the added benefit of never seeing each others' data, never emailing it to each other, and the data remains encrypted during the analysis.
@matthartman@nthparty@danikadanika@shereenshermak I agree with Danika! I am also curious to see how this is one implementation of the tech and how it could enable products to operate on top of encrypted data while preserving user data.
@sorenwrenn Thank you! As a team, we've previously worked together to deploy this kind of technology across many different domains and use-cases. It's definitely exciting to imagine how the underlying tech could be applied to meet a wide range of customer needs.
There is typically a tradeoff between data privacy and accuracy. But a bunch of new encryption technologies are changing the calculus. I'm so excited about nth party because it allows two parties to compare data sets like email lists without actually sharing the underlying sensitive information. Would love to hear what you all think!
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