Your AI is leaking data.
Notis stops it. Adopt AI. Securely.
Today, data flows straight through — unprotected
Every AI API call is a data egress event
Nearly half of employees using GenAI do so through personal accounts their organization can’t see — measured across enterprise traffic, not self-reported. Only 5% of organizations report full visibility into their AI usage.
Sources: Netskope, Cloud and Threat Report: 2026 (network telemetry); Check Point, 2026 Cloud Security Report.
Built for security teams at healthcare, banking, government, and enterprise SaaS companies.
No visibility
Your production services, AI agents, and developer tools send data to AI providers thousands of times per day. Security has zero visibility.
No controls
Patient records, API keys, source code, and trade secrets flow to external models with no policy enforcement and no way to stop it.
No audit trail
Sensitive data leaves through AI every day, and nothing records what, where, or whether policy allowed it. There's nothing to hand the auditor.
Then the auditor asks:
“How many times was your AI acceptable‑use policy violated last quarter?”
“Show me how your AI data egress is controlled.”
No logs. No evidence. No answer.
See what the answer looks like — a live audit trail →Claude Code and Codex aren’t just for developers anymore.
Finance, ops, product — even execs are getting coding agents now. Every prompt can carry source, secrets, and customer data out the door, from machines you don’t monitor. It’s the fastest-growing ungoverned egress channel in your company.
What can walk out the door
- •
.envfiles, API keys, DB credentials - •Proprietary source & architecture
- •Trade secrets & proprietary methods
- •Customer data in test fixtures & logs
- •Internal endpoints & infra topology
With Notis
- ✓Every machine covered — Mac · Windows · Linux
- ✓Same detectors, policies & audit as production
- ✓Redact / tokenize / block before it leaves the laptop
- ✓Full egress trail — per user, agent & repo
Desktop app or CLI — protecting your coding agents in minutes.
Three steps. Under one millisecond.
Enable Notis with one URL change or one DNS record. No SDK. No code changes.
Detect
Every AI request is scanned for sensitive data — PII, PHI, secrets, API keys, and custom patterns. Deterministic, sub-millisecond, no ML latency.
Enforce
Policies define what happens — block the request, redact the sensitive data, or alert and log. YAML-based, versioned with diff and rollback, per-workload.
Log
Every action produces an audit event with trace ID, findings, confidence scores, and policy version. Exports to your SIEM via OTEL, Syslog, or webhooks.
Deploy in minutes, not months
Three ways to protect your AI — pick one.
Change one URL
Point your provider base URL — OpenAI, Anthropic, Azure, or any OpenAI-compatible API — to Notis. Same SDK, same code, same response.
Add one DNS record
Transparent mode for managed fleets. Split-horizon DNS plus a trusted Notis CA route every device through Notis — no SDK, no code changes, nobody even knows it’s there.
Install the App
A cross-platform desktop app — macOS, Windows, Linux — installed in a click or pushed fleet-wide by your MDM. One toggle protects Claude Code, Codex, and every AI tool on the machine. (CLI available too.)
Your data never leaves your boundary to be scanned.
Notis detects and enforces in‑process, in‑path, deterministically — inside the gateway you run. No model in the hot path, no third‑party scanner, no second copy of your prompts.
Most AI gateways
Portkey (now Palo Alto), LiteLLM, and Cloudflare route your prompts to external guardrail services — or their own cloud — to scan them.
That’s more egress, not less.
Notis
Detection runs inside the gateway, in the request path, in microseconds. Sensitive data is redacted, tokenized, or blocked beforeit leaves — and only audit metadata reaches the control plane.
Your prompts stay yours.
Audit-ready from day one
Every request produces a structured audit event. Export to your existing SIEM, query by your compliance team, defend in front of auditors. Privacy by design — no sensitive data stored in logs.
Refining Policy with Real Workloads
We're standardizing an AI data protection layer for enterprise teams. It's called Notis.
Notis provides enforceable AI data egress control. We start with high-confidence detection for regulated data classes and refine policy with your real workloads — working with security teams who need to prove control of AI data egress before the auditor, the regulator, or the board asks.
Currently validating with teams in:
Questions we're pressure-testing
- Do all your LLM calls route through a single control point today?
- Can you block PHI from being sent to external AI providers in production?
- Can you restrict model or provider access by environment?
- Can you export LLM call logs to your SIEM?
If these gaps exist in your organization, we should talk.
Frequently asked questions
Nothing leaves without Notis.
Adopt AI. Securely.
AI Data Protection for healthcare, finance, government, and enterprise.
Regulators are moving — bank examiners and auditors are already asking how AI data egress is controlled. “We’ll figure it out later” is about to stop being an answer.
Free during the private beta · running in an afternoon · no code changes