Sending Sensitive Data to AI by Accident: A Lightweight Personal Information Remover for Developers

Remova - AI for Companies — Fri, 03 Apr 2026 11:16:31 +0000

If you’re building with OpenAI, Anthropic, or any external LLM API, there’s one risk that gets ignored too often:

private user data leaking into prompts.

That usually doesn’t happen because of bad intent. It happens because developers move fast, prompts get assembled dynamically, logs get copied into AI tools, and suddenly emails, phone numbers, credit cards, IDs, or tokens are being sent outside your system.

That’s why I built Personal Information Remover.

It’s a lightweight tool that scans raw text and masks sensitive information before it gets sent to an AI model.

What it does

Personal Information Remover is designed to be simple and practical.

It can detect and mask:

email addresses
phone numbers
credit card numbers
SSNs
IBANs
API keys
tokens
credentials
private keys
and many other sensitive text patterns

The goal is straightforward: put a safety layer between your app and external AI APIs.

Why this matters

A lot of AI teams focus on prompt quality, model latency, and cost.

But privacy mistakes are often much more serious than prompt mistakes.

If customer information, internal credentials, or personal identifiers leave your environment unintentionally, you create legal, security, and trust problems very quickly.

A simple masking layer reduces that risk immediately.

Good use cases

This tool is useful when you are:

sending support tickets to LLMs
analyzing logs with AI
summarizing customer conversations
processing CRM or sales notes
cleaning internal documents before AI enrichment
building AI copilots on top of user-generated content

If there is any chance raw text may contain personal or sensitive data, this tool helps reduce the risk before the prompt goes out.

Install from npm

You can install it with npm:

npm install @remova/personal-information-remover

Or run it directly with npx:

npx @remova/personal-information-remover --text "Contact john@email.com at +1 415-555-2671"

You can also pipe text into it:

echo "Card 4242 4242 4242 4242" | npx @remova/personal-information-remover

Use it in code

Example:

const { maskSensitiveInfo } = require("@remova/personal-information-remover");

const input = "Email: john@email.com, Phone: +1 415-555-2671, Card: 4111 1111 1111 1111";
const output = maskSensitiveInfo(input);

console.log(output);
// Email: [EMAIL REMOVED], Phone: [PHONE REMOVED], Card: [CARD REMOVED]

You can also disable the extended regex database if you want a more limited masking pass:

maskSensitiveInfo("SSN 123-45-6789", { extended: false });

Why I like simple tools like this

A lot of security improvements do not need to start as giant platforms.

Sometimes the right first step is a small, reliable utility that developers can actually drop into their workflow today.

That’s what Personal Information Remover is meant to be.

Not a full compliance system. Not a giant privacy suite. Just a practical filter that helps stop obvious mistakes before they become expensive ones.

Important note

This tool is a strong first-pass masking layer, but it should not be treated as a complete enterprise privacy system on its own.

You still need proper governance, access control, auditability, and review processes if you’re handling sensitive data at scale.

Where to get it

Install:

npm install @remova/personal-information-remover

Run instantly:

npx @remova/personal-information-remover

Final thought

If you’re building AI features, privacy protection should happen before the API call, not after the mistake.

That’s the purpose of Personal Information Remover.

If you need stronger AI security, policy controls, and enterprise-grade protection around AI usage, visit www.remova.org.

If you need help integrating AI into your systems, products, or growth workflows, check out www.goexpandia.com.

Stop Surprise AI Bills Before They Happen: A Tiny CLI for Prompt Cost Estimation

Remova - AI for Companies — Fri, 03 Apr 2026 11:14:50 +0000

If you’re building with OpenAI, Anthropic, or other LLM APIs, one thing becomes obvious fast: costs can get out of hand quietly.

A few extra retries, larger prompts, a background job you forgot to stop, or a script looping longer than expected, and suddenly your AI bill is much higher than you thought it would be.

That’s the exact reason I built AI Cost Tracker.

It’s a lightweight CLI tool that estimates how much a prompt will cost before you send it to an AI model.

What it does
AI Cost Tracker is intentionally simple:

It takes a prompt
Roughly estimates the token count
Applies pricing for popular AI models
Prints the estimated cost clearly in the terminal
Keeps a running session total so you can track spend as you work
It’s not meant to replace full billing or analytics platforms. It’s meant to give developers a fast, practical “sanity check” while building.

Why this matters
Most AI cost problems don’t come from one huge request.

They come from:

lots of small requests
prompts growing over time
testing multiple models
scripts running longer than expected
hidden costs during iteration
When you can see the estimated cost before a prompt goes out, you make better decisions immediately.

That changes behavior.

Example use case
Imagine you’re iterating on a customer support workflow, a content pipeline, or an internal AI assistant.

You start small. Then you add:

more context
larger system prompts
more history
retrieval results
extra retries
Now every request is bigger than it was a few hours ago.

AI Cost Tracker gives you a quick checkpoint in the terminal before those changes silently become a billing problem.

Install from npm
You can run it directly with npx:

npx @remova/ai-cost-tracker
Or install it globally:

npm install -g @remova/ai-cost-tracker
ai-cost-tracker
How it works
Once it starts, you can paste or type a prompt and get:

estimated tokens
estimated prompt cost
running session total
It also supports simple commands like:

/models to list supported models
/model to switch models
/total to show your session total
/quit to exit
That makes it useful as a quick local budgeting tool while you’re testing prompts or workflows.

Important note
This tool uses a rough estimation approach, not exact provider-side token accounting.

That’s deliberate.

The goal is speed and visibility, not perfect financial reconciliation. For most developer workflows, a fast pre-send estimate is far better than no estimate at all.

If you need strict enterprise controls like hard budgets, per-user limits, usage governance, or audit trails, you’ll want something more robust around your AI stack.

Where to get it
npm package:

npm install -g @remova/ai-cost-trackeror

`npx @remova/ai-cost-tracker

`Final thought
The simplest way to reduce surprise AI bills is to make costs visible earlier.

That’s what this tool does.

If you’re building AI products and want stronger controls around usage, security, and governance, visit www.remova.org

If you need help integrating AI into your product, systems, or growth workflows, check out www.goexpandia.com

DEV Community: Remova - AI for Companies