We secure the data, wherever AI touches it.
BlueAspen is data security for AI — the layer that controls what data your AI can reach and inspects what it brings back, across the agents you run and the employees using AI. Built for teams where a leaked AI interaction is a reportable breach.
AI is reaching your most sensitive data. We make sure it can't take it.
Every AI touchpoint is a new insider — one with standing access, moving data all day. We're the specialist on that data path.
Agents act on their own with credentials you issued once and access you rarely revoke. Employees paste regulated data into public AI across thousands of apps security never approved. In both cases the sensitive part is often in what comes back — a tool response, a model answer — and that's the half most tools never inspect.
BlueAspen is the security specialist that sits on the data itself: validated detection, redaction in place that keeps the reply valid, and fail-closed enforcement where it guards data. Not a networking side-feature and not a governance dashboard — the layer that inspects and controls the real content, inline, at the moment of the call.
Gateways log that it happened. The data already left.
A tool returns a patient record or a card number, and it flows straight into the model's context, the agent, or the person — and onward. BlueAspen stops the data from leaving by inspecting and redacting what AI brings back, in place, before anyone sees it.
Not a PII checkbox. Built around the data.
Our wedge is depth — on four axes a connection-first product doesn't do well.
Data, not traffic
- We inspect and redact what AI brings back — on the result leg, where the leak happens
- Redaction applied in place, so the reply stays valid and the AI keeps working
Audit-grade, not best-effort
- Validated detection — Luhn, NPI, IBAN, Shannon entropy — across 60+ context-scored patterns
- A reason on every finding, tuned for low false-block. A compliance artifact, not a guess
Fail-closed where it guards data
- On ingress and agent-to-tool paths, a call we can't judge never reaches the data
- A misconfigured gateway refuses to start. (Employee egress fails open by design — never block someone working.)
Find what's undeclared
- Agents, MCP servers and AI usage surfaced from the traffic itself
- Including the shadow ones no registry knows about
The same engine, whether the actor is an agent or a person.
Agent Proxy + MCP Gateway.
Control what your agents reach over MCP tools, other agents (A2A) and models — and front the MCP servers you expose. Redact what they return, protocol intact.
Employee Proxy.
A forward proxy and endpoint agent for people using ChatGPT, Claude, Gemini and thousands of AI apps — the same validated detection and the same audit evidence.
One policy engine and one detection stack behind both. Land on whichever surface is on fire; expand to the other on the same engine.
Founded by enterprise-security leaders (ex-Proofpoint, ex-Workday, ex-Teradata), bringing data-loss prevention to AI.
Shipped and verified — in design-partner pilots.
Proof you can check, not logos. We're pre-revenue by choice, in pilots with regulated teams.
enforcement modes shipped
live end-to-end — A2A + AWS Bedrock
automated tests
validated patterns — PCI, HIPAA, PII, secrets
Our inbound gateway passes the official MCP client SDK run against the reference server, and 12 analyzers run on local ONNX models — so by default no customer data goes to a third-party LLM.