Gatekeeper
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Gatekeeper vs LiteLLM

LiteLLM is the most popular Python proxy for AI routing. Gatekeeper is built on the Blackhole mesh — a fundamentally different architecture with cryptographic auth and NATS transport.

Gatekeeper

Built on the Blackhole NATS mesh. Go binary, async routing, Ed25519 key signing, CRDT distributed rate limiting. Routing target overhead. Designed as infrastructure.

LiteLLM

Python library/proxy. HTTP-based routing, token auth via API keys, and Redis-backed rate-limit patterns. Designed as a developer library.

Routing overhead
Measured
Gatekeeper
Measured
LiteLLM
Validation required
Memory usage
Benchmark
Gatekeeper
Benchmark
LiteLLM
Evidence required
Failover validation
Assisted proof
Gatekeeper
Manual config
LiteLLM
Evidence required
FeatureGatekeeperLiteLLM
Routing overheadMeasured during setupMeasured during review
Transport layerNATS (async)HTTP sync
LanguageGoPython
Ed25519 API keys
ZK rate limiting
CRDT token budgets
Key delegation
Self-hosted
SSE streaming
Provider failoverAssisted proofManual config
Provider count15+100+ (via config)
RBACFreeEnterprise plan
No data retention default
Mesh-nativeNATS mesh
Audit logs
Budget hard limitsvia Redis
Open sourceApache 2.0MIT
Multi-node clusteringBuilt-inManual Redis
Binary deploymentSingle binarypip install
Memory footprint~20MB~200MB+

Why Teams Switch from LiteLLM

1
Runtime profile
Gatekeeper positions a Go runtime for teams that want a compact gateway surface. Performance claims stay tied to deployment-specific benchmarks.
2
Key governance
Gatekeeper emphasizes governed keys, delegation, role budgets, and evidence trails rather than unmanaged shared provider secrets.
3
Distributed limits
Rate-limit architecture is scoped during assisted onboarding so customer topology, storage, and failure expectations are explicit.
4
Mesh integration
Gatekeeper is designed to sit beside Blackhole Mesh and AISP so routing, identity, and budgets become one company-control layer.
5
Operational packaging
The launch path favors a small, reviewable deployment profile with support boundaries documented before production rollout.