Architecture / Infrastructure

Built for engineers who care about every millisecond

A transparent look at how requests flow through RALO — from the Nginx gateway, through the high-speed cache and guardrail layers, to a low-latency hit on the right model.

Pipeline visualization

Every request is authenticated, deduplicated, screened, and dispatched — securely and with minimal latency.

request lifecyclestreaming
01

Nginx Gateway

Ingress, TLS termination, rate limiting

02

Cache Layer

Distributed semantic RAG cache

03

Guardrails

PII masking & policy enforcement

04

Model Fleet

Routed to Claude / GPT-4o / OSS

p50: 41msp99: 80mscache hit: 94.2%guardrail block rate: 0.3%
Hybrid deployment

Runs where your workloads run

Edge nodes

Run the caching and routing layer on globally distributed edge points of presence for sub-100ms TTFT anywhere.

Private deployment

VPC-isolated or fully on-prem installs. Your keys, your data plane, your network boundary — RALO never sees raw payloads.

Multi-cluster cloud

Docker and Kubernetes-native. Scale horizontally across regions and clusters with declarative manifests and zero-downtime rollouts.

Technical stack

The whole stack, no black boxes

IngressNginx · gRPC · HTTP/3
CacheVector store · semantic dedup
Control planeRust router · <5ms decisions
OrchestrationDocker · Kubernetes · Helm
ralo.yamlconfig
# ralo.yaml — declarative agent backbone
gateway:
  ingress: nginx
  protocols: [http2, http3, grpc]

cache:
  mode: semantic
  store: vector
  ttl: 3600

router:
  strategy: cost_quality_balance
  models:
    - anthropic/claude-3.5-sonnet
    - openai/gpt-4o
    - oss/llama-3.1-70b

guardrails:
  pii_masking: true
  policy: enterprise-default

deploy:
  target: kubernetes
  regions: [iad1, fra1, sin1]

Want a deployment blueprint for your stack?

Request access and our infrastructure team will map RALO onto your existing topology.