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Bring Your Own Model (BYOM) lets you connect your own LLM provider — such as OpenAI, Anthropic, Google, or any OpenAI-compatible endpoint — to power AI-driven browser automations in Anchor. BYOM is configured at the project level: each project has its own model configuration, so different projects can use different providers and models. Why use BYOM?
  • Cost control — use your existing API agreements and volume discounts
  • Model choice — pick the exact model that works best for each project’s use case
  • Data privacy — LLM requests go directly to your provider, never through Anchor’s inference layer
  • Rate limits — manage your own LLM rate limits

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Supported Providers

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Setup

1

Open your project's model settings

  1. Navigate to your project in the Dashboard
  2. Go to Project Settings → Model Configuration
2

Add your API key

  1. Click Add Provider
  2. Select your provider from the dropdown
  3. Paste your API key
  4. (Optional) Set a custom base URL — required for Azure and custom endpoints
  5. Click Verify & Save — Anchor will make a test call to confirm the key works
3

Choose a model

Select the specific model you want this project to use. Anchor will auto-populate available models for OpenAI, Anthropic, and Google. For custom endpoints, type the model name manually.
4

Save

Click Save to apply. All sessions created under this project will now use your configured model.Repeat these steps for each project that needs its own model. Projects without a BYOM configuration will continue using Anchor’s default model.

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Using BYOM via the REST API

Include the model object in your POST /projects request:

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FAQs

Yes. When you bring your own model, Anchor does not charge for LLM usage — you pay your provider directly. You still pay for other Anchor browser usage metrics as usual.
Yes — that’s the core idea. Each project has its own BYOM configuration. You can use GPT-4o in one project, Claude in another, and Anchor’s default in a third.
Project-level keys are encrypted. Session-level keys are never persisted — they exist in memory only for the session’s lifetime.