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Roadmap

StrataRouter's vision and planned features for upcoming releases.

Vision

Build the world's most performant and accurate semantic routing engine that exceeds enterprise standards while remaining developer-friendly and framework-agnostic.

Current Status — v0.3.0

Completed features:

  • Production-grade core routing engine
  • HNSW index with SIMD optimization
  • Hybrid scoring (semantic + keyword + rules)
  • Confidence calibration with isotonic regression
  • Runtime execution engine
  • Core-Runtime Bridge integration
  • Multi-provider support (OpenAI, Anthropic, Google)
  • Batch processing and semantic caching
  • Comprehensive OpenTelemetry observability
  • Python bindings and framework integrations

Q1 2025 — v0.4.0 "Performance & Scale"

Primary Goals

  • GPU acceleration for embedding generation and similarity search
  • Distributed deployment support with horizontal scaling
  • Advanced analytics with routing insights and optimization suggestions
  • Streaming support for long-running queries

Features

GPU Acceleration

  • CUDA support for HNSW index operations
  • GPU-accelerated embedding generation
  • Batch inference optimization
  • Memory management for large-scale deployments

Target: 3–5× faster inference, support for 100K+ routes

Distributed Deployment

  • Shard-based route distribution
  • Consistent hashing for load balancing
  • Cross-shard query optimization
  • Distributed caching with Redis cluster

Target: Linear scaling to 1M+ routes, <15ms P99 latency

Analytics & Insights

  • Route performance analytics dashboard
  • Query pattern analysis
  • Optimization recommendations
  • A/B testing framework for routes

Target: 20% accuracy improvement through insights

Streaming Support

  • Server-sent events (SSE) for real-time updates
  • Chunked response processing
  • Progress tracking for long queries
  • Timeout handling and recovery

Target: Support queries up to 10K tokens

Performance Targets

Metric Target Current
P99 Latency < 8ms 8.7ms
Throughput 50K req/s 18K req/s
Memory 40MB 64MB
Accuracy 97% 95.4%

Q2 2025 — v0.5.0 "Multi-Modal & Intelligence"

Primary Goals

  • Multi-modal routing (text + images + audio)
  • Adaptive learning from routing outcomes
  • Advanced policy engine with complex business rules
  • Edge deployment with WebAssembly

Features

Multi-Modal Routing

  • Image embedding and routing
  • Audio transcription and routing
  • Cross-modal similarity search
  • Unified embedding space

Target: 93%+ accuracy on multi-modal queries

Adaptive Learning

  • Online learning from feedback
  • Automatic route optimization
  • Concept drift detection
  • Model retraining pipeline

Target: 5% accuracy improvement over 30 days

Advanced Policy Engine

  • Complex business rule support
  • Conditional routing logic
  • Priority-based execution
  • Custom validators and transformers

Target: Support 90% of custom routing logic

Edge Deployment

  • WebAssembly build targets
  • Reduced model size for edge
  • Offline-first routing
  • Progressive enhancement

Target: <10MB WASM bundle, <5ms latency

Performance Targets

Metric Target
P99 Latency < 5ms
Throughput 100K req/s
Memory 30MB
Accuracy 97.5%

Q3 2025 — v0.6.0 "Enterprise & Governance"

Primary Goals

  • Enterprise security features
  • Governance and compliance tools
  • Advanced monitoring and alerting
  • Cost optimization features

Features

Enterprise Security

  • Role-based access control (RBAC)
  • Audit logging for all operations
  • Data encryption at rest and in transit
  • SOC 2 compliance

Target: Enterprise-ready security posture

Governance & Compliance

  • Route versioning and rollback
  • Change approval workflows
  • Compliance reporting
  • Data residency controls

Target: GDPR and SOC 2 compliant

Advanced Monitoring

  • Anomaly detection in routing patterns
  • Predictive alerting
  • Custom dashboards
  • Integration with DataDog, New Relic

Target: <1 min mean time to detection

Cost Optimization

  • Provider cost tracking
  • Smart fallback strategies
  • Cache hit optimization
  • Cost-based routing

Target: 30% cost reduction through optimization

Q4 2025 — v1.0.0 "Production Ready"

Primary Goals

  • Stability and reliability hardening
  • Documentation completeness (100% API coverage, 50+ examples)
  • Enterprise support programs
  • Certification and compliance

Performance KPIs for v1.0

Metric Target
P99 Latency < 5ms
Throughput 100K req/s
Accuracy 99%
Uptime SLA 99.99%

Future Vision — 2026+

Long-Term Goals

Autonomous Routing — Self-optimizing routes based on performance data. Automatic route generation from examples. Zero-configuration deployments. Target: 10× faster setup, 99%+ accuracy.

Global Scale — Multi-region deployments with CDN-like distribution. Target: <10ms latency globally.

AI-Native Features — LLM-powered route generation, natural language configuration, automatic documentation. Target: natural language → production routes.

Developer Experience — Visual route builder, no-code configuration, one-click deployments. Target: 10 min from idea to production.

Research & Innovation

Active Research Areas

  1. Neural Routing Models — Learned routing functions, attention-based routing, transfer learning
  2. Quantum-Inspired Algorithms — Quantum annealing for optimization, quantum random walks for search
  3. Federated Routing — Privacy-preserving routing, distributed learning, cross-organization routing
  4. Explainable AI — Route decision explanations, confidence visualization, bias detection

Community Input

We welcome community input on our roadmap. Ways to contribute:

  • Feature Requests — GitHub Discussions
  • RFC Process — Propose major features through RFCs
  • Beta Testing — Join the beta program for early access
  • Feedback — Share your use cases and pain points

Release Schedule

Release Type Cadence
Major releases (0.x.0) Quarterly
Minor releases (0.x.y) Monthly
Patch releases As needed
Security updates Immediate

Backward compatibility: Breaking changes only in major versions. 2-major-version deprecation notice always provided. LTS releases starting with v1.0.0 (12-month support).

Adoption KPIs for v1.0

KPI Target
GitHub Stars 10K+
Production Deployments 1K+
Enterprise Customers 100+
Weekly PyPI Downloads 10K+
Contributors 100+
Discord Members 1K+

Staying Updated

Questions?

Last Updated: January 2026. This roadmap is subject to change based on community feedback, technical discoveries, and market conditions.