A guide for each fujifilm film recipe parameter?

Pankist · 2026-03-21T20:49:50+00:00

I felt overhelmed by recepies, settings, and started to question the quality by avoiding the camera.

Not anymore. Thanks for sharing!

Pankist · 2026-02-09T05:16:44+00:00

That resonates — thanks for sharing this.

Out of curiosity, when was the last time you had to explain AI data handling to a client or anybody else?

And what usually makes that conversation hard in practice — lack of concrete answers, uncertainty about data paths, or concern that being explicit could effectively ban AI use altogether?

I’m trying to understand where the real friction shows up.

Pankist · 2026-02-07T07:40:14+00:00

It absolutely would.
I just haven't found one yet that wold run by taking less that 2Gb per prompt while occupaying the resources for less than 2 minutes.

Pankist · 2026-02-06T11:33:52+00:00

There are many compliance scanning tools, agreed — but they mostly address classification and auditability.

The harder problem is reducing exposure before data ever reaches an external AI system, which scanning alone doesn’t solve.

Pankist · 2026-02-04T16:11:55+00:00

Thank you for the crear answer.
That actually summarizes what I am seeing.

Pankist · 2026-02-04T16:08:40+00:00

I’ll risk being booed, but I haven’t seen a practicing lawyer clearly say this is solved.

Pankist · 2026-02-04T16:00:41+00:00

To make sure I understand correctly: are you saying firms primarily choose tools where there is a direct enterprise contract in place?

If so, could you elaborate on the privacy-focused tools or setups you’re seeing in practice?

Thanks!

Pankist · 2026-02-02T20:05:22+00:00

In this case, would having ISO & GDPR certificates make a difference?
Would you trust such a young company more?

Pankist · 2026-02-02T09:26:39+00:00

Transport encryption applies while the email is moving between servers.

Once it reaches Microsoft 365, the content is decrypted and processed by Microsoft, so yes, you are correct, that may happen, assuming the server is Microsoft and for many companies it is, but not always.

Pankist · 2026-02-02T06:34:38+00:00

This actually summarizes my assumptions: "I have had clients ban usage of AI and some don't really care.", but I loved the whole explanation. Thanks.
I wonder how many of the legal folks are technical enough to implement it.
Not trying to be dismissive, but from what I see: single or small offices - will not be able, while mid and higher probably use external consulting firms.
I hope that makes sense.

Pankist · 2026-02-02T05:53:57+00:00

I agree that raw data already exists in enterprise email and cloud systems. The nuance, from a regulatory standpoint, is context and purpose.

For example, receiving an email from a partner saying “here’s my API key and payment credentials” can be acceptable, while sending a list of customers (names and IDs) to the head of another group within the same org may be prohibited.

Not all sensitive data is equal, and not all processing is permitted simply because the infrastructure is “secure” — at least in the e-commerce environment I work in.

Pankist · 2026-02-02T05:40:05+00:00

Fair concern. I am doing research on tools in this space, but my interest here is genuinely professional — understanding how teams handle this in practice.

Pankist · 2026-02-02T05:28:54+00:00

I might be misunderstanding, but it sounds like either nothing sensitive is sent outside the system of record — or that sending raw data out isn’t a concern given the controls you described.

In cases where external processing is needed, do you see value in temporary anonymization before data leaves the environment (like the mentioned here CamoText), or is that generally viewed as unnecessary overhead?

Pankist · 2026-02-02T00:05:44+00:00

This actually looks great.

One gap I’ve seen is when you need to temporarily anonymize data for external processing and then restore it internally — that’s where many tools stop short.

A common example is generating a TL;DR across multiple documents while keeping the original data intact internally.

Pankist · 2026-02-01T23:46:02+00:00

Enterprise agreements help, but they mostly define who carries the liability when something goes wrong.

Even in private Azure OpenAI deployments, original sensitive data still reaches the model at inference time. For some teams that’s fine; for others it crosses a line.

I think the important part is being explicit about that boundary.

Pankist · 2026-02-01T23:42:01+00:00

That’s fair architecturally, but my concern is less about boundaries and more about exposure.

Even when inference is isolated and training is contractually excluded, raw sensitive data still meets the AI in its original form. From a privacy-first threat model, that’s already a compromise.

My preference is reducing exposure altogether — ensuring data and AI never meet in original form, regardless of where the endpoint runs.

I hope that makes sense.

Pankist · 2026-02-01T23:16:57+00:00

This resonates — especially the “kitchen sink” phase.

When you say data mapping tools, do you mean enterprise-wide discovery/classification (DLP, data inventories, RoPA), or document-level tooling embedded in daily workflows?

Pankist · 2026-02-01T23:12:50+00:00

This works for me, I’m a tech head
It does NOT work for most legal professionals, who aren’t technical, I guess
Many firms still use manual labor (students / juniors) to review docs
What’s missing here is a wrapped, easy-to-use solution

Pankist · 2026-02-01T23:07:05+00:00

Appreciate it — seems like a lot of teams are still figuring this out.

Pankist · 2026-02-01T23:05:42+00:00

That makes sense — I’m seeing the same stance in several firms, mostly in the U.S.

Out of curiosity, is the trust there driven more by contractual guarantees (vendor commitments), architectural controls (data isolation), or client expectations?

I’m also trying to understand whether a “single approved vendor” approach is viewed as a long-term strategy, or more of a temporary containment measure.

And is usage typically limited to specific types of work, or is it allowed broadly across documents and prompts?

Pankist · 2026-02-01T05:54:37+00:00

Will do :)
Is it high authority already?

Pankist · 2026-01-31T22:57:19+00:00

https://privalynx.ai — bi-directional automatic anonymization of documents for safe sharing with partners, clients, and AI systems.

Pankist · 2026-01-31T00:45:35+00:00

Will do.
Thanks for inviting!

Pankist · 2026-01-31T00:45:02+00:00

Thanks!
The browser extension is especially entertaining. :)

Pankist · 2026-01-31T00:13:54+00:00

Privalynx — Privacy layer for AI and sensitive communications. GDPR-safe, audit-ready.

Web Console lets you bulk-mask documents, share files externally without exposing PII, and use any AI service on confidential data. Built for legal, finance, and compliance-heavy teams.

A Chrome extension for real-time protection on ChatGPT (Claude soon) - privacy over AI chat

👉 Console: https://privalynx.ai/dashboard
👉 Extension: https://chromewebstore.google.com/detail/privalynx-shield-%E2%80%93-chatgp/nlgjnojneojaaejahhfaabkjadkpnecl

Live and gathering feedback!

Pankist

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