Fluree AI vs Velane: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of Fluree AI and Velane — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

Fluree AI

Fluree

Freemium

Enterprise knowledge graph platform that makes structured and unstructured data AI-ready for GraphRAG and agents.

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

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

Freemium

Open-source integration infrastructure for AI agents — 800+ OAuth-connected APIs, sandboxed runtimes, and dev/staging/prod promotion via MCP.

800+ OAuth Integrations: One connection lets agents call Salesforce, Stripe, Slack, HubSpot, Notion, GitHub, Linear, Zendesk and hundreds more via the Nango catalog.
MCP-Native Interface: Agents connect to mcp.velane.sh and drive discovery, code generation, execution, and deployment through a single MCP server.
Bun & Python Sandboxes: Every invocation runs in an isolated ephemeral runtime, so agent code can be tested safely without touching production state.
Dev / Staging / Prod Environments: Promote workflows through three environments with agent-issued publish_snippet calls and stable versioned HTTP endpoints.
Shared Credential Store: One OAuth connection per provider is reused across every team member's agent — no secret ever appears in code.
Invocation Logs & Audit Trail: Per-tenant execution logs let agents call get_logs to debug failures and give teams a full audit history.
Role-Based Access: Invoke, manage, and admin scopes control what each teammate's agent is allowed to do.
Self-Host or Hosted: Run Velane on your own infrastructure under AGPL-3.0 or use the managed mcp.velane.sh endpoint.

Agent-Built Stripe→HubSpot Automations: An agent in Cursor writes a Bun workflow that reads Stripe customers and pushes them into HubSpot, tests it in dev, and promotes to prod in one conversation.
Solo Developer Shipping SaaS Integrations: A single developer wires up Slack, Notion, and GitHub actions without maintaining an OAuth backend.
Multi-Tenant B2B Agent Products: A team runs Velane per tenant so each customer's agent has isolated credentials, sandboxes, and audit logs.
Safe Refactors of Live Workflows: Deploy a new version of a workflow to staging, verify with logs, then roll to prod with instant rollback.
MCP-First Prototyping: Prototype an entire integration pipeline from an IDE chat without spinning up backend infrastructure.