Integral Privacy Technologies

Real-world data, ready for AI.

[Integral Privacy Technologies @IntegralPrivacy]

AI companies are paying millions for company data.

Keep the training signal buyers want while protecting your company and your customers.

Retain signal. Stay protected. Get paid.

https://t.co/LWRi4VAuxm

[John Kuhn @johnkuhn58]

Development cycles are shifting. Instead of wireframes and Figma mockups, teams can go straight to a clickable prototype to test a hypothesis.

The cost of building is dropping. The cost of a confusing product experience isn't.

Full convo on Tech Trek: https://t.co/QBPI4Nbz8z

[Shubh Sinha @SHUBH17_]

It is now very public knowledge that real-world data is what the frontier labs demand.

We've seen a massive spike in demand for datasets across the world's richest industries: healthcare, energy, enterprise, and financial services.

That data is incredibly valuable, and that's exactly what makes it so hard to move. It carries real privacy obligations.

Shortcuts and sweetheart deals come at a cost: privacy loss and quality loss.

Scrub too little, and you expose people's private information. Scrub too much, and you destroy the necessary signal.

The value of proprietary data depends on getting that balance right.

Thanks to @alix_coutures for mentioning what we do at Integral.

Like the article mentions, AI labs will need real interactions between real people to progress.

[Shubh Sinha @SHUBH17_]

https://t.co/6sspkRvcjv

[Shubh Sinha @SHUBH17_]

For the past year, AI has been obsessed with compute and the constraints around it.

Chips, memory, power all seem like solvable constraints.

> Context windows started at a few thousand tokens, now run to millions.

> Inference went from prohibitively expensive to cheap enough for everyday use.

> GPUs had a crunch in 2023 but queues are clearing.

Every one of those walls had the same property: a price tag and a build path.

If you take compute as being solvable then there's a strong argument that real-world data is what remains. How consumers take actions, how a sick person describes symptoms, and how blue collar workers operate.

[Shubh Sinha @SHUBH17_]

What's interesting about Dwarkesh's framing is that the three levers aren't independent.

They're all attempts to increase the economic value created by each unit of compute.

The value of compute is increasingly determined by assets that exist outside the datacenter.

Think about proprietary data, enterprise workflows, customer relationships, and distribution which determine whether another billion inference tokens create differentiated economic value or simply more generic output.

[Shubh Sinha @SHUBH17_]

@EverettRandle is right. The $1 trillion data market is coming. But it'll largely be built on data that is locked up today behind privacy, regulatory, and business obligations.

At @IntegralPrivacy, we’re building the layer to make sensitive, real world data AI ready.

Everett lays out a sharp thesis: as tasks become the unit of AI improvement, every domain will need its own expert datasets, evals, and RL environments.

Some of that data can be created from scratch without obligations. But the highest-value data isn’t manufactured. It’s the record of real life.

The actual codebases. Ticket histories. Transaction logs. Deal Memos. Patient files. Decades of real-world interactions that teach a model how work is actually done.

The more valuable the data, the more obligations it carries.

And training is a one-way door. Once identifying, confidential, or regulated data shapes a model, there is no clean recall or unwind.

Everett points out that the task economy lacks a measurement layer. It also needs an independent assessment layer. Audits for equities. Ratings for credit. Title for property. Every trillion-dollar asset class built trust infrastructure to scale supply.

AI-ready data will be no different.

[Healthcare AI Guy @HealthcareAIGuy]

NEW: Company Deep Dive — Integral

We sat down with CEO & Co-Founder Shubh Sinha to explore how Integral is building the privacy layer for proprietary AI data.

Inside: why healthcare was the perfect starting point, why real-world data is AI's next frontier, and more.

Link 👇

[Integral Privacy Technologies @IntegralPrivacy]

🚀

[TBPN @tbpn]

Happy Wednesday. On today's show:

- @markpinc (Zynga)
- @luke10ferrari (Bending Spoons)
- @wayneting (Lime)
- @nickgrossman (USV)
- @SHUBH17_ (Integral)
- @_jeff_liu & @_JonWang (Assort Health)
- @EliotPence (Dominion Dynamics)
- @julianhoenig (Amble)

See you on the stream.

[Integral Privacy Technologies @IntegralPrivacy]

Big news: we've raised an $18M Series A to build the independent privacy layer for the real-world data economy. 🔐

The next generation of AI will be built on real-world data. We solved this challenge in healthcare, and today we bring it to the rest of the data economy.

[Integral Privacy Technologies @IntegralPrivacy]

@SHUBH17_ 🚀

[Shubh Sinha @SHUBH17_]

The next revolution is here: AI is already transforming the multi-billion healthcare sector, from drug distribution to R&D and real-time care.

But its progress depends on the quality and accuracy of the data beneath it. We’re excited to announce Integral 2.0, a compliant data platform that unlocks real-time access to multimodal health data.

Enterprises are eager to harness rich, multimodal datasets including images, text, audio, PDFs, and more to capture every dimension of human health.

But they lacked the right infrastructure - until now.

We’re already working with some of the largest companies in the world, and we’re just getting started.

[Innsena @InnsenaG2M]

Navigating the Data Privacy Maze: A Deep Dive into Consumer Data Management

Intriguing piece by Shubh Sinha of Integral on how to manage sensitive consumer data responsibly

https://t.co/rGiiUEtDFJ #healthcare #data #consumers

[Innsena @InnsenaG2M]

Organizations that move fast for #healthcare transformation:

- Take an enterprise-wide approach to intertwining data & compliance

- Do so by implementing automated privacy tools but choosing them carefully

Find out more @pulse2news Shubh Sinha, Integral https://t.co/Qhs0hHytvB

[STAT @statnews]

A new crop of companies is lining up to buy patient data from hospitals and sell it to those wanting to train AI or do research. https://t.co/0DIkLAkxkm

[Healthcare IT Today @hcittoday]

Healthcare Regulations and Compliance - 2025 Health IT Predictions @IntegralPrivacy @nethealth_us @IntrapriseHLTH @HealthCatalyst @DirectTrustorg @Navina_ai @Wolters_Kluwer @Rhymetec @LexisNexisRisk @DrFirst #healthIT
https://t.co/Ch9nQXPu4a

[World of DaaS @worldofdaas]

Got the chance to speak with the CEO of @IntegralPrivacy to learn how to accelerate the world of data compliance.

https://t.co/kpC4cH2kbQ

[Integral Privacy Technologies @IntegralPrivacy]

🚀 We're thrilled to launch our new self-serve solution for data provider partners!

Connecting regulated data has been a huge pain point, especially for data providers and this powerful tool empowers you to seamlessly upload, configure, and deliver your rich regulated data.

[Integral Privacy Technologies @IntegralPrivacy]

Our team recently released a collaborative article with @VeritasData exploring mortality data's transformative potential in healthcare innovation.

Read the full article: https://t.co/eANWWvv22n

#mortalitydata #healthcareanalytics #dataprivacy

[Sean Falconer @seanfalconer]

Shubh Sinha, CEO and Co-founder of Integral, to discuss the protection and utilization of sensitive health data.

@SHUBH17_

https://t.co/uqsVYB6sqZ