Govyn vs LiteLLM
Feature comparison
| Feature | Govyn | LiteLLM |
|---|---|---|
| Architecture | Governance proxy | Python proxy (FastAPI) |
| Multi-provider routing | ||
| OpenAI-compatible API | ||
| Per-agent budget caps | ||
| Policy enforcement (YAML) | ||
| Approval workflows | ||
| Full request/response replay | Via integrations | |
| Agent never sees real API keys | ||
| Load balancing / failover | Basic | |
| 100+ provider support | Any HTTP API | |
| PII redaction | ||
| Self-hosted | ||
| Requires PostgreSQL + Redis | ||
| Setup complexity | npx, single YAML | Docker + DB + Redis |
| License | MIT | MIT |
Architecture comparison
Sits between agent and provider at the HTTP level. Agents never see real API keys. No code changes required.
Sits between agent and provider at the HTTP level.
When to use LiteLLM
LiteLLM is a strong choice when multi-provider routing is your primary concern. If you need to unify dozens of LLM providers behind a single OpenAI-compatible interface with advanced load balancing, latency-based routing, and automatic failover, LiteLLM has more mature routing capabilities. It also has a large ecosystem of logging integrations (Langfuse, Helicone, etc.) and a well-documented virtual key system with hierarchical budgets at the org, team, and user level. For platform teams managing LLM access for many internal consumers, LiteLLM's routing-first design is a natural fit.
When to use Govyn
Govyn is purpose-built for agent governance — not just routing. If your primary concern is controlling what AI agents are allowed to do (not just which provider they talk to), Govyn's policy-as-code model gives you declarative YAML rules for budgets, model restrictions, rate limits, approval workflows, and PII redaction. Govyn requires no database or Redis — it's a single binary with a YAML config, making it dramatically simpler to deploy. And because Govyn is governance-first, features like full request replay, approval gates, and per-agent audit trails are built in rather than bolted on through third-party integrations.
Migrating from LiteLLM
Export your LiteLLM model configuration
List your model deployments and routing rules from your LiteLLM config.yaml. Note which providers, models, and API keys you're using.
Translate routing rules to Govyn YAML
Map your LiteLLM model groups to Govyn routing entries. Govyn uses a similar YAML format — upstream URLs, model names, and API keys translate directly.
Migrate virtual keys to Govyn agent keys
Replace LiteLLM virtual keys with Govyn agent keys. Add budget and policy rules per agent — you'll get more granular control than LiteLLM's budget system.
Swap the base URL in your applications
Point your applications from the LiteLLM proxy URL to the Govyn proxy URL. Both expose OpenAI-compatible endpoints, so no code changes needed beyond the URL.
Remove PostgreSQL and Redis dependencies
Govyn stores state locally and doesn't require external databases. Once migration is verified, you can decommission the PostgreSQL and Redis instances LiteLLM required.
Try Govyn in 5 minutes
Open source, MIT licensed. One command to start governing your AI agents.
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Explore more
SDK wrappers are door locks. Proxies are walls. A deep technical comparison of both governance architectures for AI agents in production.
FROM OUR BLOGHow smart model routing through a proxy cut our OpenAI and Anthropic bill from $2,140/mo to $578/mo. Zero code changes. Just YAML.
INTEGRATIONAdd budget limits, policy enforcement, and full replay to LangChain agents using OpenAI. Five-minute setup, zero code changes.
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