Fluree AI vs Switchyard: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Fluree AI and Switchyard — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Fluree AI
Fluree
Enterprise knowledge graph platform that makes structured and unstructured data AI-ready for GraphRAG and agents.
Key features
- Verifiable Knowledge Graph: FlureeDB stores entities and relationships with cryptographic verifiability to every fact
- AI-Ready Data Foundation: Golden records, entity resolution, semantic layer, and taxonomy governance to prep any data
- GraphRAG Activation: Ground LLM retrieval on the graph for up to 95% answer accuracy in benchmarks
- Fluree Memory: Long-term, governed memory store for AI agents across sessions
- Fluree MCP: Plug your governed knowledge graph into any MCP-capable agent or IDE
- AI Agent Governance: Policy and audit controls for how agents access and modify enterprise data
- Conversational Analytics: Natural-language interface over the enterprise semantic layer
- Open-Source Core: FlureeDB is free to start and open source
Best for
- Build a governed enterprise knowledge graph that AI agents can query verifiably
- Deploy GraphRAG on top of internal data to raise LLM answer accuracy
- Give AI agents persistent, policy-governed long-term memory across tools
- Expose enterprise data to any MCP client (Claude, Cursor, IDEs) with role-based governance
- Consolidate customer or product records via entity resolution before feeding an LLM
- Run enterprise AI search grounded in structured relationships instead of raw text chunks
- Estimate and control AI agent TCO across the organization
Switchyard
NVIDIA
An open-source Rust proxy and library that routes LLM traffic across models and providers while preserving native OpenAI and Anthropic API compatibility.
Key features
- Protocol Translation: Converts between OpenAI Chat Completions, OpenAI Responses and Anthropic Messages formats so clients keep their native API while any backend serves the request.
- Multi-Backend Routing: Spreads traffic across vLLM, NVIDIA NIM, Ollama and any OpenAI-compatible endpoint, letting you point an existing coding agent at an open-source model without changing the agent.
- LLM Classifier Router: Uses request content to decide whether a given turn needs the weak or the strong model tier, cutting spend on turns that do not need frontier capability.
- Stage Router: Routes most turns from signals already in the conversation — tool results, errors, conversation stage — so no extra model call is needed to make the decision.
- Escalation Router: Runs every turn on the weak tier first, then has a judge read that answer and decide whether the same request should be re-sent to the strong tier.
- Random Routing for A/B Tests: Applies a fixed traffic split across targets for benchmarking, baselines and cost experiments.
- Operational Metrics: Exposes Prometheus metrics for requests, errors, latency, token counts and the overhead added by routing itself.
- Server or Library Deployment: Run it as a standalone Rust proxy configured by routes.toml, or embed switchyard-libsy in your own application so it decides the target and hands the model call back to you.
Best for
- Pointing Coding Agents at Open Models: Serve Claude Code or Codex from vLLM, NIM or Ollama without the agent knowing the API changed.
- Cost/Performance Optimization: Send routine turns to a cheap weak-tier model and reserve the strong tier for turns a classifier or judge says need it.
- Model A/B Benchmarking: Split traffic on a fixed ratio across two models to compare quality, latency and cost on real production requests.
- Provider Migration and Failover: Keep application code on one API shape while swapping or mixing the providers behind it.
- Embedding Routing in an Agent Runtime: Drop the routing algorithms into an existing gateway or agent framework via the library path without adopting a new HTTP stack.
- Operational Visibility: Track per-route latency, error rates and token spend through Prometheus to find which routes are actually costing money.