For B2B SaaS & technology companies

Ship AI features.
Pass every security review.

Your enterprise customers are reading your TOS with red pens. PrivacyPal is the governance layer that lets you build on GPT, Claude and Gemini without putting your customers' data on a subprocessor list. Sidecar topology, sovereign by design, agent-native for Claude Code, Copilot & MCP — so you keep velocity and don't get lapped.

Engineers shipping AI features with PrivacyPal
The B2B AI headwind

Every AI feature triggers a new vendor review.

When you add OpenAI to your stack, every enterprise customer's CISO asks the same question: where does our data go, who else sees it, and what do you do when an agent calls our tools? Deals slow down. Renewals get harder. "AI-first" becomes "AI-stuck."

PrivacyPal breaks the pattern. The governance lives in your VPC. Customer data never reaches the LLM — Privacy Twins preserve statistical bandwidth without surfacing the original. The LLM never makes your subprocessor list. Your pipeline stays fast. The shift is here.

A sidecar topology: your app sits beside a PrivacyPal sidecar in your VPC. Real customer values are swapped to realistic Privacy Twins before reaching the LLM, then restored on return. YOUR VPC · TENANT CUSTOMER DATA Tenant database name · email · document body customer_id · payload · context YOUR APP AI-powered feature summarize · classify · draft via OpenAI / Anthropic SDK PRIVACYPAL · SIDECAR · PRIVACY-TWIN ENGINE OUTBOUND · REAL → TWIN "Jane Park" "Mira Tan" cust_47291 cust_82064 "$48,200/yr" "$62,500/yr" INBOUND · TWIN → REAL "Mira Tan" "Jane Park" cust_82064 cust_47291 "$62,500/yr" "$48,200/yr" PERIMETER · TWINS ONLY ↓ TWIN REQUEST ↑ TWIN RESPONSE EXTERNAL · LLM PROVIDER OpenAI · Anthropic · others "Summarize cust_82064's account for Mira Tan, currently at $62,500/yr, renewing on Oct 14..." NEVER LANDS ON YOUR SUBPROCESSOR LIST · ZERO REAL VALUES ON THE WIRE
Who deploys PrivacyPal

B2B SaaS · platforms · dev tools · data infra.

01

B2B SaaS copilots

Ship in-product AI assistants without appearing on any vendor subprocessor list. Privacy Twins keep tenant data sovereign — the LLM never sees customer values.

02

Developer tools & Claude Code workflows

Let AI agents see user code without shipping proprietary IP to a model vendor. Native governance for Claude Code, Copilot & MCP — secret detection on the way out, real values stitched back on the way in.

03

Data platforms & agentic queries

Enable natural-language queries and agent-driven workflows over customer-hosted data. Values stay in the tenant. Only statistically accurate Privacy Twins go to the model. Full audit trail.

04

Internal tooling & agentic ops

Give engineers AI copilots on production logs, traces and prod data — without the leak risk. Org-wide AI controls, prompt-injection prevention, agent governance.

"Our fastest-ever security review. Three enterprise customers said yes to AI the week we launched with PrivacyPal."
— CTO, Series C data infrastructure
Built for engineers

Deploy in a sprint, not a quarter.

Drop-in API

OpenAI-compatible endpoint. One base_url change and your stack inherits end-to-end redaction.

Per-tenant policies

Different customers, different rules. Apply detectors by tenant ID, enforce by API key.

Streaming native

Preserves SSE and chunked responses end-to-end. Your LLM UX doesn't change.

Ship AI fast.
Pass every security review.

30-minute technical walkthrough with one of our deployment engineers. Install once. Run sovereign. Get governance the CISO greenlights.

Book a demo. Start 5-day trial