Securing Claude For Enterprise Usage

For enterprises adopting GenAI, there's a real tension in giving employees access Claude: you want them to use it for deep knowledge work, but you don't want to lose control of your enterprise's sensitive data going to Anthropic. Claude Desktop, secured by Mavs, puts our runtime layer in front of the standard Claude Desktop app. It lets your employees use Claude for real work while you keep control of your sensitive data. Every prompt is evaluated before it reaches the model. Sensitive values are replaced with similarity-preserving synthetic stand-ins on the way in and mapped back on the way out. Since the sensitive values never reach the model, inference itself is not the exposure point. Every session is written to an immutable audit log.

Why your existing stack can't govern Claude

Traditional data security tools were built for data at rest and data in motion between systems. A prompt is neither. It is language flowing from a person into a model, in an encrypted stream your current stack can't look inside.

• Network DLP and CASB see one encrypted stream to the model API. They can block it; they can't look inside it.
• Endpoint DLP and app control have two settings for AI: allow or deny. Deny it and productivity moves to whatever employees can reach without you. Allow it and they see a permitted application receiving typed input, with no exfiltration event to flag. On an unmanaged device, neither is in the path at all.
• DSPM classifies data at rest in your cloud repositories. It has nothing to say about content that goes into a prompt.
• API monitoring watches your own APIs. It doesn't sit between an employee and Anthropic's.

The prompt is where your data actually flows, so that is where the control belongs.

What the Mavs AI runtime control layer enables

That is where Mavs sits. Mavs AI supported Claude Desktop puts the Mavs runtime layer in front of Claude as an AI gateway. Every prompt generated from Claude Desktop, whether it comes from Chat or from Cowork, is evaluated by Mavs before it reaches the configured Anthropic model, so your policy applies while the work is happening. That makes Claude governable, and lets you give it to people to use on real work rather than rationing it to a trusted few.

Runtime prompt security

Every prompt is evaluated by Mavs before it reaches the model.

• Sensitive business data and PII are replaced with synthetic values before the prompt reaches the model, then mapped back on the way out, so the file your team opens holds the real values.
• Coverage extends past formatted PII to what is sensitive to the business: deal codenames, unannounced pricing, M&A terms, key accounts.

Enterprise AI governance platform

1. AI policy enforcement

Set your AI policy for Claude Cowork and have AI guardrails enforce it at runtime, so your teams can do deep knowledge work on sensitive data.

2. Conversation auditability and investigations

Prompts, tool calls and policy decisions are recorded in tamper-evident logs, so a specific session can be reconstructed when compliance or security needs to know what happened. This covers desktop app sessions, which Anthropic's Compliance API does not reach on any plan.

3. Connector access decided centrally, by team

An admin decides which connectors each team can use, rather than each user deciding for themselves.

4. Security and productivity dashboards

See which teams are using Claude Cowork, for what, and where your biggest risks are. Measure your enablement alongside your risk posture.

5. Authentication through your identity provider

Push and configure through your existing MDM, and have users sign in through Mavs AI with your enterprise identity provider, such as Microsoft Entra ID. Access follows the same identity, group membership and offboarding path as the rest of your estate.

Data sovereignty and residency

With Mavs in the path, the picture splits in two, and each half lands where you want it.

Conversation history never leaves the user's machine: it is stored on the local disk, not on Anthropic's servers.

Prompts are different. Every prompt has to reach a model somewhere to get processed, and inference is the part that crosses a border. With Mavs in the path, the prompt reaches Anthropic's API with the sensitive values already replaced, pinned to a region you choose. That answers the residency question that GDPR, DPDP and sovereign data rules ask. The audit record is produced at the gateway, so you get the evidence without centralising the transcripts.

There is one more network benefit. The standard Claude Desktop app loads its interface from claude.ai over the internet each time it runs. In the Mavs supported build, that interface ships inside the app itself, so the app connects to a short, fixed list of destinations that your network team can allowlist.

For organisations that need processing inside their own environment, local options for inference and processing are on the way.

With Mavs AI, cost follows usage, not headcount

Token consumption is billed against your Anthropic API licence rather than per seat. That removes the per-head cost of giving someone access, and moves the spending controls to you:

• Give Claude Cowork to more users without buying a licence for each one.
• See adoption and usage by team on the productivity dashboard.
• Set token limits by team or user.

Employee experience doesn't change

Everything Claude Cowork can do, it still does with the Mavs runtime security layer in place: the same tasks, files, projects, skills and the plugins you allow, at the same speed. Mavs runs inline at sub-second latency, and prompts are processed rather than blocked, because Mavs protects the sensitive data inside a request instead of refusing the request. What changes is that every one of those actions is now governed and secured at runtime, without the employee doing anything differently.

See how it works on the Claude Desktop page, or book a demo.