Semantic Routing Engine

Semantic routing
for production AI.

Route AI queries with 20× faster latency, 95.4% accuracy, and 33× less memory. Rust core. Python-first API. Enterprise governance built in.

$pip install stratarouter
P99 Latency
8.7ms20× faster
Throughput
18K/s40× higher
Accuracy
95.4%+12.7 pts
MIT LicensedPython 3.8+Rust 1.70+SOC 2 Ready
quickstart.py
Python 3.11
from stratarouter import Router, Route # Initialize with any embedding modelrouter = Router(encoder="all-MiniLM-L6-v2") # Define intelligent routesrouter.add(Route(    id="billing",    description="Billing and payment questions",    keywords=["invoice", "billing", "refund"])) router.build_index()  # O(n log n) HNSW # Route queries — blazing fastresult = router.route("I need my April invoice") print(result.route_id)      # → "billing"print(result.confidence)    # → 0.94print(result.latency_ms)    # → 1.8ms ⚡
Output:route: billingconf: 0.941.8ms
Works with🦜 LangChain🕸️ LangGraph🤖 CrewAI⚡ AutoGen

Independently verified benchmarks

The numbers that define the category

0.0ms
P99 Latency
20× faster than semantic-router
0K/s
Throughput
40× higher request rate
0.0%
Routing Accuracy
+12.7 pts over nearest rival
0MB
Base Memory
33× less than alternatives
0+
Framework Integrations
LangChain, CrewAI, AutoGen & more

AWS c5.4xlarge · 1M queries · 100-route index · all-MiniLM-L6-v2 · January 2026

Full-Stack AI Infrastructure

Purpose-built for
production AI systems

From raw routing throughput to enterprise governance — StrataRouter covers the complete infrastructure stack for intelligent AI applications.

Performance

Blazing Fast Routing

8.7ms P99 with 18,000 req/s throughput. SIMD-accelerated cosine similarity via Rust HNSW index. Zero-overhead Python bindings via PyO3.

Intelligence

Hybrid Scoring Engine

Combines dense semantic embeddings (HNSW), sparse BM25 keyword scoring, and rule-based patterns. Isotonic regression calibrates confidence for reliable decisions.

Architecture

Rust Core, Python API

The routing engine is Rust — maximum performance, memory safety, zero GC pauses. A clean Pythonic API means zero friction for ML teams. Cargo crate also ships.

Ecosystem

Deep Framework Support

First-class integrations for LangChain, LangGraph, CrewAI, AutoGen, OpenAI Assistants, and Google Vertex AI. Drop-in in 5 lines of code.

Cost Savings

Semantic Caching

85%+ cache hit rate cuts LLM cost by 70–80%. Mandatory gate checks prevent incorrect cache reuse. Deterministic blake3 hash keys for reproducible results.

Runtime

TCFP Workflow Engine

Runtime executes Typed Compositional Flow Protocol workflows with full isolation. Batch deduplication, state snapshots, and checkpoint recovery built in.

Compliance

Enterprise Governance

Multi-agent consensus with quorum voting. SHA-256 hash chains create immutable audit trails. SOC 2, HIPAA, ISO 27001 compliant out of the box.

Security

Multi-Tenancy & RBAC

Complete tenant isolation with per-tenant quotas, cost caps, and model allowlists. Role-based and attribute-based access control. Idempotency prevents duplicate calls.

Observability

Full Observability

Prometheus metrics, OpenTelemetry 2.0 distributed tracing, structured logging. Health endpoints, cost tracking, and latency monitoring out of the box.

LLM Routing

Multi-Model Routing

Route to GPT-5, Claude 4.5, Gemini 3.1, or local models based on complexity, cost, latency, and capability. Reduce inference spend by up to 60%.

Deployment

Production Deployment

Production Docker images, Helm charts for Kubernetes, docker-compose for local. Freemium resource limits (4 vCPU / 24 GB / 10 concurrent) enforced automatically.

Quality

95.8% Test Coverage

Google-standard code quality, 55 tests, 95.8% coverage. Full CI/CD, automated benchmarks, and property-based testing ensure correctness in production.

Architecture

Three layers. One platform.

Start with the free Core, add production execution with Runtime, scale to enterprise governance — each layer independently deployable.

Layer 1

StrataRouter Core

< 2ms routing

Python Library · MIT License

HNSW IndexBM25 ScoringHybrid RoutingPyO3 Bindings
Layer 2

StrataRouter Runtime

10K exec/day free

Execution Engine · Rust/Axum

TCFP WorkflowsSemantic CacheBatch DedupREST API
Layer 3

StrataRouter Enterprise

SOC2 · HIPAA · ISO

Governance Platform · Rust

Multi-Agent ConsensusAudit TrailsRBAC/ABACMulti-Tenancy

Infrastructure

PostgreSQL
State persistence
Prometheus
Metrics & alerts
OpenTelemetry
Distributed tracing

LLM Providers

🧠 GPT-5🔮 Claude 4.5🌐 Gemini 3.1🏠 Local Models
01

Query arrives

Your application sends a natural-language query to the router.

02

Hybrid scoring

Core scores via dense embeddings + BM25 + rules in under 2ms.

03

Routed & executed

Runtime executes the matched handler with caching and observability.

Benchmarks

The performance gap is undeniable

Independently verified benchmarks across leading semantic routing libraries. StrataRouter wins on every dimension that matters in production.

Routing Speed
req/s (higher = better)
StrataRouter
18K/s
semantic-router
450/s
LlamaIndex
380/s
P99 Latency
ms (lower = better)
StrataRouter
8.7ms
semantic-router
178ms
LlamaIndex
245ms
Memory Usage
MB (lower = better)
StrataRouter
64 MB
semantic-router
2.1 GB
LlamaIndex
3.2 GB
Routing Accuracy
% (higher = better)
StrataRouter
95.4%
semantic-router
84.7%
LlamaIndex
82.3%
MetricStrataRoutersemantic-routerLlamaIndexImprovement
P99 Latency8.7ms178ms245ms20–28×
Throughput18,000/s450/s380/s40–47×
Memory64 MB2,100 MB3,200 MB33–50×
Accuracy95.4%84.7%82.3%+10–13 pts
Cold Start< 50ms1,200ms2,000ms24–40×
AWS c5.4xlarge (16 vCPU, 32 GB RAM) · 1 million queries · 100-route index · all-MiniLM-L6-v2 · January 2026
Use Cases

The routing layer for every AI app

From chatbots to enterprise orchestration, StrataRouter adapts to your exact workflow.

AI Agent Orchestration
from stratarouter import Router, Route router = Router(encoder="all-MiniLM-L6-v2") # Specialized agent routesrouter.add(Route("billing",    description="Payment and invoices",    examples=["refund", "invoice", "charge"])) router.add(Route("technical",    description="Product bugs and errors",    examples=["crash", "error", "not working"])) router.add(Route("sales",    description="Pricing and upgrades",    examples=["pricing", "plan", "upgrade"])) router.build_index() # Intelligent routing in real-timeresult = router.route("My payment failed last night")# → Route: billing  |  Confidence: 0.94  |  1.8ms ⚡
Routed successfullyavg 1.8ms
Integrations

Works with your entire AI stack

Native integrations for every major framework, LLM provider, and infrastructure tool. Drop in StrataRouter without rewriting your pipeline.

🦜
LangChain
Chain, Retriever, LCEL
🕸️
LangGraph
Graph routing nodes
🤖
CrewAI
Routed agent workflows
AutoGen
Group chat router
🧠
OpenAI
GPT-5 Assistants
🔮
Anthropic
Claude 4.5 Sonnet
🌐
Google
Vertex AI agents
🤗
Hugging Face
Any SBERT model
🐳
Docker
One-line deploy
☸️
Kubernetes
Helm chart ready
📊
Prometheus
Metrics & alerting
🐘
PostgreSQL
State persistence
🦜
LangChain
Chain, Retriever, LCEL
🕸️
LangGraph
Graph routing nodes
🤖
CrewAI
Routed agent workflows
AutoGen
Group chat router
🧠
OpenAI
GPT-5 Assistants
🔮
Anthropic
Claude 4.5 Sonnet
🌐
Google
Vertex AI agents
🤗
Hugging Face
Any SBERT model
🐳
Docker
One-line deploy
☸️
Kubernetes
Helm chart ready
📊
Prometheus
Metrics & alerting
🐘
PostgreSQL
State persistence
🦜
LangChain
Chain, Retriever, LCEL
🕸️
LangGraph
Graph routing nodes
🤖
CrewAI
Routed agent workflows
AutoGen
Group chat router
🧠
OpenAI
GPT-5 Assistants
🔮
Anthropic
Claude 4.5 Sonnet
🌐
Google
Vertex AI agents
🤗
Hugging Face
Any SBERT model
🐳
Docker
One-line deploy
☸️
Kubernetes
Helm chart ready
📊
Prometheus
Metrics & alerting
🐘
PostgreSQL
State persistence
🦜
LangChain
Chain, Retriever, LCEL
🕸️
LangGraph
Graph routing nodes
🤖
CrewAI
Routed agent workflows
AutoGen
Group chat router
🧠
OpenAI
GPT-5 Assistants
🔮
Anthropic
Claude 4.5 Sonnet
🌐
Google
Vertex AI agents
🤗
Hugging Face
Any SBERT model
🐳
Docker
One-line deploy
☸️
Kubernetes
Helm chart ready
📊
Prometheus
Metrics & alerting
🐘
PostgreSQL
State persistence
$pip install stratarouter

Python 3.8+ · MIT License · Rust 1.70+ · Docker available

Trusted by AI teams

From builders who use it
in production

Engineering leaders and AI architects choose StrataRouter for their most demanding workloads.

StrataRouter cut our routing latency from 180ms to under 9ms. Our AI orchestration layer went from a bottleneck to invisible infrastructure. Best routing decision we made all year.

PR
Priya Raghunathan
Principal AI Engineer · Fortune 500 FinTech

The semantic caching alone saved us $15K/month in OpenAI costs. With 85%+ cache hit rates, the ROI was positive in the first week. This is what production AI infrastructure should look like.

MC
Marcus Chen
CTO · AI-first SaaS startup

We handle 50K+ routing decisions per day flawlessly. The LangGraph integration was 5 lines of code. Accuracy improvement from 84% to 95%+ reduced escalations by 40%.

SH
Sophia Hartmann
Head of Engineering · Enterprise SaaS, 400+ employees

After evaluating semantic-router, LlamaIndex, and building our own — StrataRouter won on every metric. The Rust core is genuinely game-changing for production latency requirements.

JO
James Okafor
ML Platform Lead · Series B AI company

The Enterprise governance layer gave us SOC 2 readiness for our AI workflows in a week. Multi-tenancy, audit trails, and RBAC — everything we needed, production-tested from day one.

LP
Linda Park
VP Engineering · Healthcare AI platform

We replaced a complex custom router with StrataRouter and reduced routing-related incidents to zero. The BM25 + dense hybrid handles edge cases our old system consistently missed.

AM
Arjun Mehta
Senior AI Architect · Global consulting firm
Free forever for the Core library

Route smarter.
Ship faster.

Join leading AI teams using StrataRouter to power intelligent, production-grade routing. Up and running in 5 minutes.

$pip install stratarouter
< 5 min
Time to first route
MIT
Core license
95.4%
Out-of-box accuracy
Need enterprise governance?Talk to our teamsupport@stratarouter.com