AI Gateway

TL;DR * Claude Code natively supports Amazon Bedrock and Google Vertex AI through environment variables, so teams can run the agent against Claude models inside their own cloud accounts under existing IAM, billing, and data-residency controls. * Native Claude Code Bedrock and Vertex configurations point at exactly one provider each;

TL;DR * Anthropic's cost documentation reports that Claude Code costs an average of about $13 per developer per active day and $150 to $250 per developer per month, so reducing Claude Code token costs is a per-seat spend problem, not a rounding error. * Token cost scales with

Semantic caching serves stored LLM responses to similar prompts using embedding similarity. Bifrost runs it with direct and semantic lookup paths. Semantic caching is a request-side cache that embeds an incoming prompt into a vector, searches previously stored prompt vectors, and returns a stored response when the cosine similarity

TL;DR * Cloudflare AI Gateway is a hosted edge proxy, so it cannot be deployed inside a customer VPC or an air-gapped environment, which rules it out for many regulated workloads. * Bifrost is the strongest enterprise alternative, adding 11 microseconds of overhead per request at 5,000 requests per

TL;DR * LLM costs are driven by token volume rather than provisioned capacity, so they can rise by an order of magnitude in a day with no deployment change. * Bifrost enforces budgets at four independent levels (customer, team, virtual key, provider config), and blocks a request when any applicable budget

Bifrost resolves LLM gateway routing, provider fallback, and governance in one request path. Here is the order of operations and how to configure each layer. LLM gateway routing is the process of deciding which provider, model, and API key serve a given request, and it is the layer where cost