You are 25 people or 900, and your customers are reading your TOS with red pens. PrivacyPal is the governance layer that lets you build on GPT, Claude, Gemini and Grok without putting your customers' data on a subprocessor list. Sidecar topology, sovereign by design, agent-native for Claude Code, Copilot, Hermes Agent & MCP, so you keep velocity and don't get lapped.
When you add OpenAI to your stack, every 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? For a smaller vendor that question is existential. Deals slow down. Renewals get harder. "AI-first" becomes "AI-stuck."
PrivacyPal breaks the pattern. The governance lives in your VPC: a sidecar beside your app. 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.
Sidecar in your VPC · outbound real → twin, inbound twin → real · never lands on your subprocessor list · zero real values on the wire
Ship in-product AI assistants without appearing on any vendor subprocessor list. Privacy Twins keep tenant data sovereign: the LLM never sees customer values.
Let AI agents see user code without shipping proprietary IP to a model vendor. Native governance for Claude Code, Copilot, Hermes Agent & MCP: secret detection on the way out, real values stitched back on the way in.
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.
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.
OpenAI-compatible endpoint. One base_url change and your stack inherits end-to-end redaction.
Different customers, different rules. Apply detectors by tenant ID, enforce by API key.
Preserves SSE and chunked responses end-to-end. Your LLM UX doesn't change.
Max governs your own people: every engineer in Claude Code, every AE in ChatGPT, every laptop under one policy. $30 per seat a month at 1 to 9 seats, $25 at 10, $21 at 100, billed annually. Cloud is the enterprise tier that runs the sidecar inside your VPC so customer data never reaches a model vendor, and the SDK puts the same engine in your own pipelines.