Articles
Articles on prompt security, PII masking and secure LLM workflows
Technical articles, implementation guides and practical explainers for building privacy-first AI systems.
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Prompt Privacy
Reducing prompt-level exposure before data reaches AI models
What prompt privacy means, how it differs from AI security and governance, and the control stack that reduces what ever reaches an LLM.
Prompt Privacy
What is prompt privacy?
A definition-first explainer for prompt privacy: reducing prompt-level exposure before data reaches AI models, and how it differs from data privacy, AI security and governance.
8 min read · Jun 7, 2026
Prompt Privacy
Prompt privacy vs. AI security
Two related but distinct disciplines. Prompt privacy reduces what reaches the model; AI security is the broader program around it. A side-by-side, layered-control framing.
7 min read · Jun 7, 2026
Prompt Privacy
Prompt-level data protection
What prompt-level protection means in practice: prompt-level exposure, data minimization, masking, redaction, provider controls — and where each one helps.
8 min read · Jun 7, 2026
Prompt Privacy
How to stop LLMs from seeing sensitive data
A calm walkthrough of the problem, the available approaches, their tradeoffs and their limitations — without fear language or compliance overclaim.
9 min read · Jun 7, 2026
Prompt Security
Securing prompts before they reach the model
Definitions, patterns and practical controls for what leaves your system in a prompt.
Prompt Security
What is prompt security?
A practical definition of prompt security, how it differs from prompt injection defense, and the controls that actually reduce risk before a prompt reaches the model.
7 min read · May 20, 2026
Prompt Security
How to secure prompts before they reach GPT
Concrete patterns for sanitizing, masking and routing prompts before they hit a provider — without rewriting your app.
8 min read · May 20, 2026
Prompt Security
Prompt security vs. prompt injection
Two often-confused terms: one protects what leaves your system, the other defends against what comes in. Why both matter and which one Privian addresses today.
6 min read · May 20, 2026
Prompt Security
How to prevent sensitive data in LLM prompts
A field-tested checklist for keeping PII, secrets and credentials out of the prompts your application sends to LLM providers.
8 min read · May 20, 2026
PII Masking
Keeping personal data out of LLM prompts
How masking, rehydration and redaction differ — and how to keep customer data out of provider calls.
PII Masking
PII masking for LLMs
What PII masking means in the context of LLM applications, how deterministic placeholders work, and how rehydration restores responses on the way back.
8 min read · May 20, 2026
PII Masking
How to remove personal data before sending to GPT
Practical strategies for stripping names, emails, account numbers and secrets out of a prompt — and the tradeoffs of each approach.
7 min read · May 20, 2026
PII Masking
PII redaction vs. PII masking
Redaction destroys data. Masking preserves structure. The choice changes what the model can do — and whether the response is usable.
6 min read · May 20, 2026
PII Masking
How to prevent GPT from seeing customer data
A defense-in-depth approach to keeping customer identifiers, contact info and account data away from third-party model providers.
7 min read · May 20, 2026
LLM Gateway
Routing, BYOK and the LLM gateway pattern
What an LLM gateway is, how it differs from an AI gateway or firewall, and where privacy-first routing fits.
LLM Gateway
What is an LLM gateway?
A clear definition of an LLM gateway, why teams put one in front of providers, and the responsibilities it should own.
7 min read · May 20, 2026
LLM Gateway
LLM gateway vs. AI gateway
The terms get used interchangeably. They are not the same. Here is the distinction we use and why it matters when you pick one.
5 min read · May 20, 2026
LLM Gateway
Privacy-first LLM gateways, explained
Not all gateways treat data the same way. What makes a gateway privacy-first, and what to look for if data minimization is a requirement.
7 min read · May 20, 2026
LLM Gateway
How to route prompts securely
Patterns for routing prompts across providers and models without leaking customer data or hardcoding provider keys into clients.
7 min read · May 20, 2026
LLM Gateway
What is an LLM firewall?
An educational explainer on the emerging "LLM firewall" category — what people mean by it, how it relates to a privacy-first LLM gateway, and where the term is misleading.
7 min read · May 26, 2026
LLM Gateway
LLM firewall vs. LLM gateway
A balanced comparison of LLM firewalls and LLM gateways: what each is responsible for, how their goals overlap, and how privacy-first routing fits in.
7 min read · May 26, 2026
AI Privacy
Privacy, GDPR and enterprise buyer questions
Questions enterprise buyers raise during AI security reviews — GDPR, BYOK, managed vs. self-hosted, and clean data paths.
AI Privacy
GDPR and LLMs, explained
What GDPR means for teams using GPT, Claude and other managed LLMs — personal data in prompts, provider boundaries, retention, and the technical controls teams adopt in practice.
9 min read · Jun 2, 2026
AI Privacy
How to reduce sensitive data in LLM prompts
A practical guide for shrinking the sensitive-data footprint of summarization, drafting, support and copilot prompts — with realistic before/after examples and honest limitations.
8 min read · Jun 2, 2026
AI Privacy
BYOK for privacy-sensitive AI
Bring-your-own-key explained for teams with privacy and procurement requirements: what BYOK changes about billing, provider boundaries and trust — and what it does not solve.
7 min read · Jun 2, 2026
AI Privacy
How to protect employee data in AI workflows
AI tools quickly accumulate employee names, emails and internal identifiers. Here is how to keep that data out of third-party prompts.
7 min read · May 20, 2026
AI Privacy
What enterprise buyers ask about AI data privacy
The questions that actually come up in enterprise AI security reviews — what enters the model, what is retained, who can see it, BYOK boundaries, and where managed gateways like Privian fit in a broader control stack.
11 min read · Jun 2, 2026
AI Privacy
Policies vs. technical controls for AI
Acceptable-use policies and training matter, but people inevitably paste sensitive data into tools that help them move faster. A neutral guide to where technical controls reduce exposure risk — and where they do not.
9 min read · Jun 2, 2026
AI Privacy
What is a clean AI data path?
A definition-first explainer: what "clean" means when enterprise buyers ask about an AI data path, what enters the model, what is retained, and how managed gateways and self-hosting fit in.
8 min read · Jun 2, 2026
AI Privacy
Managed vs. self-hosted LLMs
A neutral comparison of managed model APIs and self-hosted inference across privacy, cost, latency, governance and operational complexity — plus hybrid patterns teams actually use.
10 min read · Jun 2, 2026
AI Privacy
Why employees paste sensitive data into ChatGPT
People use the tools that make work easier. AI accelerates work — which creates predictable exposure risk. A calm look at the behavior, why training alone struggles, and which technical controls reduce the surface.
9 min read · Jun 2, 2026
AI Privacy
Lessons from the Samsung ChatGPT incident
A measured retrospective on the 2023 Samsung internal-code paste incident: what happened, why it mattered, what organizations actually changed afterwards, and where prompt-level controls fit alongside policy.
9 min read · Jun 6, 2026
AI Privacy
Why redaction alone is not enough for AI privacy
Redaction is one tool. AI privacy is a layered problem: redaction, masking, minimization, retention controls, provider boundaries and governance each do something different — and none is a silver bullet.
10 min read · Jun 6, 2026
AI Privacy
How enterprise AI security reviews have changed
What buyers asked about AI in 2023 vs. 2024 vs. 2025 vs. 2026: from retention checkboxes to data-path diagrams, subprocessor maps and model-level controls. A practical guide for vendors and buyers.
11 min read · Jun 6, 2026
AI Privacy
The clean data path framework
A reusable framework for describing — and defending — an AI data path: what enters, what leaves, what is retained, who can see it, and what is deleted. The vocabulary enterprise reviewers are starting to expect.
10 min read · Jun 6, 2026
Internal Copilots
Building secure internal AI workflows
Reference patterns for internal copilots and AI features in multi-tenant SaaS without leaking customer data.
Internal Copilots
How to build secure internal copilots
A reference architecture for internal copilots that lets employees query LLMs without exposing customer or employee data to the provider.
9 min read · May 20, 2026
Internal Copilots
Secure AI features for SaaS products
Shipping AI features in a multi-tenant SaaS product without exposing one customer's data to another — or to the LLM provider.
8 min read · May 20, 2026
Procurement
Procurement, security review and vendor assessment for AI
Resources for enterprise AI procurement, security questionnaires and vendor risk assessments — written for security, compliance and procurement teams.
Procurement
The AI security questionnaire
What to ask AI vendors during a security review: data handling, retention, logging, encryption, authentication, incident response, subprocessors and compliance. A reusable framework for enterprise buyers.
12 min read · Jun 15, 2026
Procurement
AI vendor risk assessment
A practical framework for assessing AI vendors across operational, privacy, compliance, dependency, data-exposure and governance risk — written for security, procurement and architecture teams.
11 min read · Jun 15, 2026
Procurement
AI vendor due diligence checklist
A practical review framework for enterprise teams evaluating AI vendors before approval — covering privacy, security, compliance and operational due diligence in one workflow.
12 min read · Jun 17, 2026
Procurement
AI data residency, explained
How enterprise buyers should evaluate data residency when deploying AI systems — the difference from sovereignty, how LLM traffic crosses jurisdictions, and the questions to ask vendors.
11 min read · Jun 17, 2026