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Rexaris AI

AI is already inside your company.
Take control before your data leaves the perimeter.

On-prem AI control plane for employees, applications and AI agents. Enforce data policies before sensitive information reaches external models.

Request a Private PilotSee How It Works
  • 100% On-Prem
  • BYOK
  • No customer prompts in our cloud
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policy PII_EXTERNALaction MASK2 entities masked184 tokens$0.004

AI adoption is growing faster than enterprise control.

  • Shadow AI

    Employees use ChatGPT, Claude and other AI tools without centralized policies.

  • Sensitive data

    PII, credentials, source code and confidential information can reach external providers.

  • AI agents

    Claude Code, MCP tools and autonomous agents introduce a new layer of access and execution risk.

  • No visibility

    Security teams often cannot answer:

    Who used which AI, with what data, under which policy and at what cost?

One control plane for enterprise AI

Every managed AI request is inspected before it reaches the model.

  1. Users, applications and agents talk to one OpenAI- and Anthropic-compatible endpoint inside your network.
  2. Each request is classified, matched against your policies and either allowed, masked, blocked or routed to an approved model.
  3. The decision, the data classes involved, tokens and cost are written to the audit log before the response is returned.
managed request path

Configurable AI protection controls

Define what data can be sent, which models can process it, and how every AI request should be handled.

One policy layer across every model.

Whether your teams use OpenAI, Anthropic or internal models, Rexaris AI applies the same security and data policies before every managed request.

  • OpenAI
  • Anthropic
  • Internal models

Sensitive data never has to reach the model

Detected entities are replaced with stable placeholders before the request leaves the gateway. The mapping stays inside your trusted boundary.

user input
Prepare a summary for Ivan Petrov.Email: ivan@bank.comCard: 4111 1111 1111 1111
MASK PII
sent to model
Prepare a summary for <PERSON_1>.Email: <EMAIL_1>Card: <CARD_1>

After the model responds, placeholders can be restored inside the trusted perimeter, so the user sees the real values and the provider never did.

PII
names, emails, phone numbers, national IDs
PCI
card numbers, IBANs, account identifiers
Credentials
API keys, tokens, passwords, private keys
Source code
proprietary repositories and snippets
Custom patterns
your own regex and dictionary classifiers

Bring shadow AI into the same control plane

Rexaris controls managed AI traffic directly and integrates with your existing security stack to discover AI usage outside the gateway.

  • Discover shadow AI

    Import AI usage discovered by endpoint, browser, DLP and SASE security tools.

    • Personal ChatGPT
    • Gemini
    • Claude
    • DeepSeek
    • Unknown AI SaaS
    • Coding assistants
    • AI browser extensions

  • Unified AI registry

    Maintain one inventory of enterprise AI usage, whether it is managed by the gateway or observed by a connected security tool.

    • Approved
    • Restricted
    • Prohibited
    • Shadow
    • Observed

    Tracked per AI system

    Application · Type · Source · Users · Owner · Risk · Data exposure · Policy status

  • Correlate risk

    Combine AI usage with security events to see the difference between controlled and shadow usage.

    ChatGPT PersonalProhibited
    Users
    17
    PII exposure
    12
    Source code
    7
    Credentials
    2

    source Check Point

    Claude CodeApproved
    Users
    11
    Requests
    14,820
    Masked
    53
    Blocked
    27

    source Rexaris Gateway

  • Orchestrate enforcement

    Where supported by integrations, Rexaris can synchronize AI policy with existing security controls.

    Rexaris policy

    ChatGPT PersonalProhibited

    Connected SASE / DLP platform

    BLOCK

    Rexaris policy

    Claude EnterpriseApproved

    External security tool

    ALLOW

    Where supported by the connected security platform. Endpoint and network blocking is performed by the integrated tool, not by Rexaris.

One registry for managed and shadow AI

ai registry · models, applications, agents, MCP serversProduct preview, sample data
One registry for managed and shadow AI
ApplicationTypeSourceUsersStatusRiskEvents
Claude CodeApplicationRexaris11ApprovedControlled27
ChatGPT EnterpriseApplicationRexaris84ApprovedControlled12
Qwen (internal)ModelRexaris39ApprovedControlled0
Finance AgentAgentRexaris3RestrictedControlled5
Jira MCPMCP serverRexaris6RestrictedMedium2
ChatGPT PersonalApplicationCheck Point17ProhibitedHigh21
Gemini PersonalApplicationNetskope9ShadowMedium7
Unknown AI SaaSApplicationPurview4ShadowHigh3

Rexaris does not replace your existing security stack. It turns it into part of your AI governance architecture.

Connect the tools you already run and bring managed and shadow AI into one control plane.

Security integrations

Integration roadmap
  • Check Point
  • Netskope
  • Microsoft Purview
  • Zscaler
  • Other DLP / SASE / endpoint security

Integrations are planned and are not yet available. Names are listed to show the intended architecture, not current support.

Rexaris Gateway
Deep enforcement
Security integrations
Shadow AI visibility
Deep controlBroad visibilityEnterprise AI governance

Run Rexaris with one team and see what your AI traffic actually contains.

Request a Private Pilot

Claude Code without losing control

Developers keep their normal workflow. Security keeps visibility and policy enforcement.

  • No need to replace the developer workflow
  • Centralized API access, one corporate endpoint
  • Usage and cost visibility per developer and project
  • Secrets protection before code leaves the perimeter
  • Policy enforcement on every request
  • MCP and tool governanceroadmap
developer request path
gateway logclaude-code

alex@corp → POST /v1/messages

✕ AWS_SECRET_ACCESS_KEY detectedinfra/terraform.tfvars

policy
CREDENTIALS_EXTERNAL
action
BLOCK

request not forwarded · event logged · developer notified

Built for environments where data cannot leave your control

100% On-Prem
Application, database, policies and audit logs run inside customer infrastructure.
BYOK
Customers use their own OpenAI, Anthropic and other provider credentials.
No vendor data path
Customer prompts do not pass through our cloud.
Internal LLM support
Connect Qwen, Llama, vLLM, Ollama or any OpenAI-compatible endpoint.
Air-gapped ready
Architecture designed to support restricted and isolated enterprise environments.

See every managed AI request

AI audit
Who used which model, which policy was triggered, token consumption, cost and security events, per request.
AI FinOps
Spend by user, department, application, agent and model, with budgets and limits before the bill arrives.
overview · last 7 daysProduct preview, sample data
Active AI users
128
AI requests
42,180
Tokens
184M
AI spend
$18,420
Blocked requests
47
Masked requests
328
Secrets detected
12
PII events
143
Recent managed AI requests (sample data)
UserSourceModelPolicyActionCost
IvanWebGPTPII_EXTERNALMASK$0.14
AlexClaude CodeClaudeCREDENTIALBLOCK—
MariaAPIQwenINTERNALALLOW$0.03
Finance AgentAgentClaudePII_EXTERNALMASK$0.21
OlgaCursorGPTDEFAULTALLOW$0.08

Where teams start

Designed for regulated enterprises

For organizations with strict security, privacy and data residency requirements.

  • Banking
  • Fintech & Payments
  • Government
  • Telecom
  • Healthcare
  • Critical Infrastructure

Up and running inside your network

  1. step 1

    Deploy

    Install inside your infrastructure.

    Docker / Kubernetes

  2. step 2

    Connect

    Add OpenAI, Anthropic and internal LLM endpoints.

    Your own provider keys

  3. step 3

    Enforce

    Define policies and route corporate AI traffic through the gateway.

    Rule by rule, audit-only first

Start with visibility. Enable enforcement when ready.

From the blog

All posts

Start with one team. Get control before scaling AI across the company.

Deploy with a small team, connect existing AI providers and validate policies using real workflows.

Apply for a Private Pilot

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Current AI usage

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