VeyraOS Router

Every model call,
routed to the right model

Task-aware model routing for enterprise AI: automatic tiering by task, cost-first selection, failover built in. OpenAI-compatible — zero changes to your callers.

40-60%
Cost reduction
99.9%
Model availability
<30s
Failover time
router · decision trace
Incoming request
「Refactor this function for concurrency」
Task type
code.gen
Tier
COMPLEX
glm-5.2 · Vendor A
¥8/MSelected
glm-5.2 · Vendor B
¥9.5/MStandby
deepseek-pro · elevated errors
Auto-avoided
Decision logged with reason — auditable
Capabilities

From forwarding to deciding

Six capabilities that turn a model gateway into an intelligent routing platform.

Task-Aware Routing

Requests are classified by task type and difficulty, then matched to the right model tier — translation and summaries take the fast lane, code and reasoning get the heavyweights.

19 Task Types4 TiersAuto Classification

Cost-First Selection

Among channels that meet the quality bar, the cheapest wins. Simple tasks are automatically downgraded — 40-60% lower blended cost.

Cost BandsAuto DowngradeSavings Estimate

Auto Failover

Rate limits and upstream outages trigger automatic retries and channel switch-over in under 30s. Requests never fail because of a single provider.

Auto RetryCircuit BreakerDegrade Chain

Latency-Aware Scheduling

Continuous percentile latency profiling per channel (5-min rolling window). Slow nodes lose traffic automatically — P99-first scheduling.

p50 / p99Rolling WindowWeighted LB

Explainable & Auditable

Every routing decision carries its reason in response headers and is logged to a tamper-evident daily hash chain — enterprise compliance built in.

Decision ReasonHash ChainFull Audit

Zero-Change Adoption

OpenAI-compatible endpoint. Point your SDK's base_url at the router and declare intent with model=auto — the platform absorbs model iteration and price swings.

OpenAI Compatiblemodel=autoSSE Stream
Architecture

A five-layer routing platform

The access layer absorbs caller differences, the routing brain is the intelligence core, and the signal loop compounds into a data flywheel.

L5
Access Layer
Unified OpenAI-compatible entry · per-caller API keys · declared intent (cost band / latency preference / model=auto)
L4
Routing Brain
Admission → task profiling → risk pricing → capability matching. New strategies run in observe-only parallel before taking traffic
L3
Cost Ledger
True upstream cost per request — the source of truth for budgets, chargeback and usage reports
L2
Signal Loop
Decision logs (7-day TTL) · daily hash-chain anchors · health profiles · quality feedback — all fed back into routing policy
L1
Provider Adapters
Multi-vendor pool with protocol normalization and basic retry — pluggable, replaceable, not the core asset
One request, one full decision chain
0
Admission
OpenAI-compatible request, caller key
1
Context Sizing
Token estimate filters out short-window models
2
Task Classification
Type + difficulty tier set the quality bar
3
Health Filter
Circuit-broken / slow channels excluded
4
Cost Optimization
Cheapest channel above the quality bar
5
Weighted Dispatch
Weighted LB across channels, decision logged
Deployment

Deploy it your way

Run the routing stack inside your own cluster today, or consume it as a managed service.

Available now

Self-Hosted Stack

A standalone deployment unit (own LiteLLM instance, own database) that drops into any Kubernetes cluster — zero coupling to the VeyraOS platform.

  • Standalone namespace & secrets
  • Ready in minutes with kubectl apply
  • Private, data never leaves your network
Coming soon

Managed Cloud Service

Fully managed model routing with self-serve keys, budgets and quotas — one key for every model, capacity planning absorbed by the platform.

  • Self-serve key lifecycle
  • Budgets, rate limits, overrun circuit-breakers
  • Usage & decision audit built in

Absorb the model zoo. Route with intent.

Start with reliability and cost visibility today; let the data flywheel make routing smarter every day.