Feature

Model Access Controls

Not every team needs the most expensive model.

TL;DR

—Control which models each department can access. Prevent your marketing interns from using highly expensive coding models to draft basic social media copy..
—Keep expensive frontier models for teams that need the performance. Ensure that your data scientists and senior analysts always have access to the heavy compute they require without breaking the bank..
—New models roll out in phases, not all at once. Test the safety, efficacy, and cost-profile of new AI releases with a controlled pilot group before authorizing a company-wide deployment..
—Designed for governed enterprise AI usage.

How It Works

Some tasks are fine with a standard model. Others genuinely need frontier-level reasoning. Remova lets you decide which models are available to which teams. When a new model launches, you roll it out to a test group first instead of making it available to everyone at once. It's about putting the right tool in the right hands.

The difference in cost between a standard AI model and a frontier reasoning model can be 50x or even 100x per token. Without strict model governance, an enterprise will rapidly hemorrhage budget as employees default to the most expensive tool for basic tasks like summarizing an email or drafting a Slack message. Remova provides the fine-grained controls necessary to align model capabilities with actual business requirements.

Furthermore, model governance is essential for risk management. When a new foundation model is released to the public, it may exhibit novel security vulnerabilities or behavioral quirks that your organization hasn't vetted yet. With Remova, you can completely block that new model globally, or provision it exclusively to a secure sandbox team for evaluation before deciding to deploy it to the wider enterprise.

Key Benefits

Control which models each department can access. Prevent your marketing interns from using highly expensive coding models to draft basic social media copy.
Keep expensive frontier models for teams that need the performance. Ensure that your data scientists and senior analysts always have access to the heavy compute they require without breaking the bank.
New models roll out in phases, not all at once. Test the safety, efficacy, and cost-profile of new AI releases with a controlled pilot group before authorizing a company-wide deployment.
One place to manage model availability across the organization. Eliminate the need to chase down different department heads to update permissions across multiple disjointed AI vendor platforms.
Users see a consistent set of models based on their team. Provide a curated, uncluttered interface that prevents users from feeling overwhelmed by a dozen identical-looking AI options.

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Use Cases

Reserving the most capable models for teams with complex analysis needs. Guarantee that complex financial forecasting or deep code refactoring tasks are powered by the most intelligent engines available.

Testing a new model with one department before opening it up. Allow your IT security team to aggressively red-team a new Anthropic or OpenAI release before granting it to general staff.

Keeping a standard set of approved models per department. Establish a reliable, predictable baseline of AI capability that department managers can plan their workflows around.

Preventing ad-hoc model selection that drives up costs. Stop the common phenomenon of employees defaulting to the 'smartest' option when a cheaper, faster model would have been sufficient.

Rollout Checklist

Define policy scope and ownership for model access controls.
Pilot model access controls with one department and measure adoption quality.
Set alert thresholds for governance events and escalation workflows.
Review outcomes monthly and tune controls based on operational feedback.

Metrics to Track

Control adoption rate by team
Policy or safety event volume trend
Exception turnaround time
Cost impact before vs after rollout

Free Resource

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A ready-to-review AI policy document customized to your company.

Knowledge Hub

Model Access Controls FAQs

Yes, you can set a highly efficient, cost-effective model as the global default, requiring users to actively switch if they need advanced reasoning.

They won't even see the model in their interface dropdown. If they attempt to access it via API, the gateway will return a clear permissions error.

Yes, through our routing engine, you can dictate that highly sensitive data (like PII) is only processed by locally hosted open-source models rather than external APIs.

Absolutely. You can control access to DALL-E, Midjourney APIs, or custom image generators using the exact same role-based governance framework.

AI FOR COMPANIES

Deploy model access controls and related controls with Remova's enterprise AI governance platform.