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Atif Ali
42 lines
1.9 KiB
Markdown
42 lines
1.9 KiB
Markdown
# AI Bridge
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AI Bridge is a smart gateway for AI. It acts as an intermediary between your users' coding agents / IDEs
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and providers like OpenAI and Anthropic. By intercepting all the AI traffic between these clients and
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the upstream APIs, AI Bridge can record user prompts, token usage, and tool invocations.
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AI Bridge solves 3 key problems:
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1. **Centralized authn/z management**: no more issuing & managing API tokens for OpenAI/Anthropic usage.
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Users use their Coder session or API tokens to authenticate with `coderd` (Coder control plane), and
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`coderd` securely communicates with the upstream APIs on their behalf.
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1. **Auditing and attribution**: all interactions with AI services, whether autonomous or human-initiated,
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will be audited and attributed back to a user.
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1. **Centralized MCP administration**: define a set of approved MCP servers and tools which your users may
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use.
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## When to use AI Bridge
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As LLM adoption grows, administrators need centralized auditing, monitoring, and token management. AI Bridge enables organizations to manage AI tooling access for thousands of engineers from a single control plane.
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If you are an administrator or devops leader looking to:
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- Measure AI tooling adoption across teams or projects
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- Establish an audit trail of prompts, issues, and tools invoked
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- Manage token spend in a central dashboard
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- Investigate opportunities for AI automation
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- Uncover high-leverage use cases last
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AI Bridge is best suited for organizations facing these centralized management and observability challenges.
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## Next steps
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- [Set up AI Bridge](./setup.md) on your Coder deployment
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- [Configure AI clients](./clients/index.md) to use AI Bridge
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- [Configure MCP servers](./mcp.md) for tool access
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- [Monitor usage and metrics](./monitoring.md) and [configure data retention](./setup.md#data-retention)
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- [Reference documentation](./reference.md)
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