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

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

Cadenya

Paid

A managed agent runtime that layers your tools, agents and objectives so teams can test agent behavior safely and iterate fast.

Unified Tool Layer: Connect MCP servers, OpenAPI specs and existing endpoints once, and expose them to every agent through a single managed interface.
Model-Agnostic Variations: Set a default model and run canary variations on other providers side by side to compare behaviors before promoting a change.
Progressive Tool Discovery: Tool schemas stay out of the context window until an agent asks for them, with configurable max tools per search, search hints and a rerank threshold, so every request gets smaller.
Live Token Metering: Track cost as it accrues across loops, active variations, memory entries and widgets, so usage is visible rather than discovered on the invoice.
Webhooks and SSE Streaming: Push agent events — assistant messages, tool results, approval requests, sub-agent spawns, compaction, timeouts — into your own apps in real time.
Memory Layers: Attach stored documents such as playbooks and policy sets to an agent so its guidance persists across objectives.
Outcome Feedback Scoring: Collect scored comments on each objective, attributed to the variation and model that produced it, to see which behaviors actually work.
Embeddable Widgets: Drop an agent experience into any frontend as a widget rather than building the conversational surface yourself.

Operational Exception Handling: Run an agent that detects stalled shipments or orders and reroutes them through your dispatch API within policy.
Safe Model Migration: Evaluate a new frontier model as a canary variation against live objectives before switching the default.
Wrapping Existing APIs: Turn internal OpenAPI endpoints into agent-callable tools without rewriting the services behind them.
Embedding Agent Chat in a Product: Ship a conversational agent surface into an existing frontend using widgets instead of building it in-house.
Cost Control at Scale: Use progressive discovery and live metering to keep context size and per-loop cost down as agent traffic grows.
Agent Quality Review: Compare scored feedback across variations to understand which prompt or model changes improved real outcomes.

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.