About Pretense

Building the future of secure AI development

Pretense is the AI firewall that keeps secrets out of every prompt, with audit trails and policy presets. Budgets open, deals close, and your ROI shows up in the revenue.

When auditors knock on the door asking for your AI logs, on cloud models and local models alike, what would you hand them?

EgressRaw, on your machine

const dbHost  = "orders-prod-7.internal"const ownerId = "acct_northstar_ops"const service = "claims-adjudicator"

Your real secret values, safe on your machine.

2025Founded

Los AngelesHeadquarters

Open BetaStage

Solo-preneurTeam

Why Pretense

Your code stays yours, and your revenue keeps moving

Real-time code protection

Your code is swapped before the model ever sees it, right inside the request, live.

Automation built into your workflow

Works with the tools your team already pays for. Same editor, same habits, same speed.

Real-time insights and analytics

See every identifier that left, when, and to which provider, cloud and local alike. Your budgets stay approved and your ROI stays visible.

Enterprise-grade access control

Decide who sees what, per team and per model, with an audit trail that unlocks enterprise budgets.

Mission

Your private data stays yours alone. The AI still gets the work done.

Vision

Every team works with AI, and everything private stays right where it belongs.

Principles

Keep sensitive code private while your context, your visibility, and your answer quality all stay whole.

Our story

Why we built Pretense

Let me get this straight. Most leaders assume legal and regulatory alignment and AI velocity compete, and in today's fast-moving market, security compliance feels immense enough to scale to the moon.

To be clear: when we mindfully cooperate speed and security, compliance becomes the bread and butter of a thriving business.

At AbbVie, I watched brilliant engineers, and me as their manager, beating around the bushes with traditional firewalls. That is exactly why Pretense matters: an AI firewall with audit trails and policy presets that turns organizational trust into 10× revenue.

It keeps secrets out of every prompt. Your code names are restored locally, so your context stays whole, your teams keep their speed, and your answers keep their quality. Today that means sailing through enterprise security reviews, unlocking budgets that were waiting, and turning complete trust into revenue.

Cloud models

For growing startups

We sanitize sensitive data before external APIs ever see it, and every cloud prompt arrives with its own audit log. Enterprise procurement clears, the revenue that once waited on security review closes, and your ROI shows up in Q1.

Local / custom models

For enterprises

Every local model call is logged exactly like a cloud call, so the answer for the auditor is already on file. Boundary controls move you from evaluation into production, stalled budgets open, and your ROI compounds at scale.

Jimmy Malhan

Founder & CEO, Pretense

Great achievements begin with a bold vision. Watching brilliant developers hold back their genius over security showed me this inspiring truth: total protection is your fastest path forward, and compliance is your ultimate engine for revenue growth.

Having guided high-impact platforms at AbbVie, Jimmy built Pretense to turn complete trust into immediate commercial success.

Sounds like you are ready to unlock enterprise budgets and capture fresh revenue today, yes?

Pretense protects your code dynamically and nurtures complete context, so your team sails through audits, closes high-value contracts faster, and expands revenue potential by 10×.

Ready when you are. Jimmy opens the door personally at [email protected] as your technical founder, and every onboarding gets his personal attention until your team is protected and shipping.

Code protection flow

How Pretense protects your code

6 steps, 1 round trip. Real → protected → code names restored, and the rail beside each step shows exactly where your data stands: real on your machine, protected in flight.

Step 1

Install the CLI

Set up Pretense in 1 command, in seconds. Every default lands ready to go.

Setup

Step 2

Connect your workflow

Point your existing tools and AI environment at Pretense. Everything else stays exactly as it is.

Setup

Step 3

Detect sensitive data

Scan the request for credentials, keys and personal data.

Real, local only

Step 4

Protect secrets & PII

Replace every match with a safe synthetic equivalent that preserves structure & meaning.

Real, local only

Step 5

Send to AI safely

The model receives fully functional code and works entirely on safe synthetic values, every time.

Protected, in flight

Step 6

Restore and deliver

Your code names are reversed locally, so the answer reads exactly as your code did. Secrets stay as placeholders, and the audit trail your budgets rely on is kept.

Code names restored, byte for byte