Secure operational intelligence

Secure operational intelligence without the monolith.

Vrangr helps sensitive teams use AI on protected data. It checks what can be seen, where a request can go, and what must be recorded.

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Scope: Protected data
Control: Check before answer
Record: Full audit trail

Vrangr // Request control Live

01AskQuestion about protected datareceived

02CheckIdentity, access, rules, labelsverified

03RetrieveOnly approved contextscoped

04RedactRestricted detail removedapplied

05RouteThrough an approved environmentapproved

06AnswerReturned with sourcesreturned

07RecordAudit trail keptlogged

Every request passes through control. Run the demo

Restricted Case 1981-04 · Protected records Handling: controlled

The constraint

Your best data is usually the hardest to use.

Legal files, security reports, internal records, and restricted documents cannot be treated like ordinary prompts. Teams need AI, but they also need rules, routes, and records. Vrangr gives them all three.

Q1Who is allowed to see this?
Q2What can leave this system?
Q3Which route is approved?
Q4What must be redacted?
Q5What record do we keep?

The control loop

Every request passes through control.

Ask. Check. Retrieve. Redact. Route. Answer. Record. Vrangr turns protected-data AI into a controlled process, not a casual prompt.

Vrangr // Control loop 7 steps

01AskA user asks a question about protected data.input

02CheckVrangr checks identity, access, rules, and data labels.control

03RetrieveOnly approved context is retrieved.control

04RedactRestricted details are removed or summarized.control

05RouteThe request moves through an approved AI environment.control

06AnswerThe user receives an answer with sources.output

07RecordVrangr keeps a clear audit trail.record

Walk through a real request, start to finish. Open the demo

Controls

Control what AI can touch.

Six controls stand between a question and an answer. Each one is a checkpoint, not a convenience.

C-01

Permission checks

Access is bound to who is asking, their role, and the task at hand.

C-02

Data labels

Protected records are tagged so the system knows what each one holds.

C-03

Controlled search

Retrieval returns only what the requester is allowed to see.

C-04

Redaction

Restricted detail is removed or summarized before it reaches a model.

C-05

Approved routes

Requests run only in environments cleared for that class of data.

C-06

Audit trails

Every answer carries a record of what happened and why.

Trajectory

Start with one protected workflow.

Vrangr can begin with one sensitive question and one protected dataset. Over time, it can grow into a map of documents, people, events, and decisions, with rules in place the whole way.

Protected AI

Ask questions across sensitive data with rules in place.

Data map

Connect documents, people, events, and decisions to their sources.

Workflows

Support cases, reviews, alerts, approvals, and handoffs.

Deployments

Run in private cloud, VPC, on-prem, or approved AI gateways.

See the platform

Deployment

Deploy where your data is allowed to live.

Vrangr runs inside your boundary. Each mode is a controlled site, not a pricing tier.

D-01

Local evaluation sandbox

Try Vrangr against a confined dataset before anything moves.

Sandbox

D-02

Private cloud or VPC

Run inside your own cloud account and network boundary.

Approved

D-03

On-prem environment

Keep protected data on hardware you control.

Approved

D-04

Approved model gateway

Reach only the models your policy has cleared.

Controlled

D-05

High-control environment

Stricter handling for the most sensitive work.

Controlled

Research and field notes

Notes from the boundary.

Short notes on using AI over protected data: what controlled visibility buys you, and what it does not.

NOTE 01

Bring one protected workflow.

We will show how Vrangr checks the request, controls the route, returns the answer, and records what happened.

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