Bifrost
7.6#3 in llm gateway softwareFree planFree planWebAPILinuxmacOS
VisitBifrost vs Routerly
What both publish
| Fact | Bifrost | Routerly |
|---|---|---|
| Budget controls | Teams can set spending limits and track costs by teams, projects and models. | Budgets can be set globally, per project, or per token, and can track cost, calls, or token usage over rolling or calendar windows. |
| Deployment | Bifrost can run as a self-hosted binary or through npx, Docker and Kubernetes, including private-cloud and disconnected environments. | The maker provides Docker and installer-based deployment, and says the installer supports Windows, macOS, and Linux. |
| Intended users | The OSS edition is presented for developers, small teams, and self-managed deployments, while Enterprise is for teams running production AI systems at scale. | The site describes Routerly as built for developers and use cases ranging from indie projects to enterprise deployments, including SaaS teams and local-first development. |
| Product | Bifrost is an enterprise AI gateway and control plane for routing, governing, and securing AI traffic, including LLM calls, MCP tools, and agents. | Routerly is a self-hosted gateway between applications and AI providers that routes requests, tracks costs, and enforces budgets. |
| Security | The security documentation describes Snyk dependency and code scanning, CodeQL analysis, Docker image scanning, and hardened non-root production containers. | The documentation says provider API keys and project tokens are AES-256 encrypted at rest, and user passwords are bcrypt-hashed. |
Bifrost plans
- OSSFree
- EnterprisePriced on request
Routerly plans
- Free self-hostedFree
Pick Bifrost if…
The OSS edition suits developers and small teams that can manage a self-hosted deployment. Enterprise targets teams running production AI systems at scale and needing additional controls or SLA-backed support.
Pick Routerly if…
Routerly is aimed at developers and teams, including SaaS groups and local-first projects, that want to manage AI-provider routing and budgets on their own infrastructure. It may suit users who need project-level separation and compatible OpenAI- or Anthropic-format clients.