Pyrana vs n8n

Architecture

n8n is built around the workflow: a trigger starts an execution, data moves through a chain of nodes, and the run ends. Pyrana is built around the application: declared pages, operations (targets), versioned resources, agents, and workflows, all behind one gate that authorizes and records every call. In n8n, governance lives inside each workflow's design. In Pyrana, it lives in the platform under every application.

What n8n is designed for

n8n gives builders a visual canvas, hundreds of integration nodes, code nodes for JavaScript and Python, and AI nodes including the AI Agent node. A workflow can be triggered by a webhook, a schedule, a chat message, or an app event. n8n 2.0, released on December 5, 2025, hardened the runtime: Code node executions run in isolated task runners by default, and saving a workflow no longer changes production until you publish it. It runs on n8n Cloud or self-hosted, with a free Community Edition.

What Pyrana is designed for

Pyrana is an application platform. A client authors one App configuration plus the frontend experience. Identity, authorization, durable storage, orchestration, approvals, audit, and context are built once and shared by every App. A call can arrive from the App's own pages, the copilot, the API, MCP, a schedule, or an external event, and every one of those doors leads to the same eight-step gate. The gate fails closed.

Context and knowledge

n8n handles knowledge through nodes you assemble: document loaders, embeddings, vector stores, and retrieval tools attached to the AI Agent node. That is flexible and quick to set up. Pyrana's context engine, cortIQ, stores company knowledge as typed, classified Context Units with evidence passages and content-hash identities, and accounts for every unit retrieved, injected, and cited in each run.

Does it matter which one you use?

For a support bot over a handful of documents, a vector store in n8n is enough. The difference shows up when knowledge changes under governance. In cortIQ, a unit's classification decides how it may change: absolute units never auto-change, regulated units wait for a person, and changes supersede rather than overwrite. Because citations are content-addressed, the exact business context used in any run is provable later.

Agent capabilities

Both products run tool-calling agents. n8n's AI Agent node connects a chat model, memory, and tools, including MCP servers and other agents used as tools. Pyrana agents belong to an App and inherit its rules; a model is assigned per agent, and one workflow can fan out to many specialized agents per entity and group, each publishing back versioned resources.

How tools differ

In n8n, a tool is usually another node or a sub-workflow, with whatever credentials that node holds. In Pyrana, tools are specific to the job: the agent passes the entity and the period, and the tool holds the query. Tool bindings are scoped per agent, and tool policies map the caller's scope entitlement to tool arguments before the call. Agents do not write free-form queries against source systems.

Governed actions and approvals

n8n can pause an AI Agent before it runs a chosen tool and ask a person to approve, through Slack, Microsoft Teams, Gmail, n8n Chat, and other channels. Pyrana binds approvals to the business action itself: a policy over typed arguments decides which invocations need a person, and the exact invocation is frozen under a hash until a named lane decides.

Does n8n have human in the loop?

Yes. Since version 2.6 (January 26, 2026), a human review step can sit between the AI Agent and specific tools. The reviewer sees the tool name and parameters ($tool.name, $tool.parameters), and a denial cancels the action and informs the agent. On Slack and Telegram you can restrict which user IDs may approve. The "Send and wait for response" actions also pause a workflow for a reply.

What Pyrana adds to the approval

Pyrana's tool approval policies use thresholds, membership, existence checks, and compound rules, so a purchase request under a limit runs while one above it queues. The frozen invocation holds the operation, arguments, scope, and evidence. Reviewer eligibility is checked when the decision is made, not when the request was sent. The invocation is revalidated before dispatch, and dispatch is idempotent, so a retry reuses the receipt. A queued request is visibly different from a posted entry in the application.

Building the application

n8n is where the automation lives; the application people work in usually lives elsewhere. Its user-facing surfaces are the chat interface and the messaging channels it connects to. Pyrana ships the application layer: an App shell, declared pages that hand exact page context to the agent, a copilot, and personal pages a person asks the copilot to generate.

Where outputs go

An n8n workflow writes its results to the systems it targets: a spreadsheet, a CRM, a ticket. Pyrana publishes outputs as resources: versioned, immutable, and attributed. Version 1 might come from an agent run and version 3 from the copilot acting for a person. Publishing against a stale version is refused, never overwritten, and pages read a resource at an exact version.

Governance and security

n8n's enterprise controls are real and plan-dependent: instance roles (Owner, Admin, Member), project roles (Admin, Editor, Viewer), custom project roles on Enterprise, SSO and LDAP on Business and Enterprise, external secret stores and log streaming on Enterprise. Pyrana runs one authorization check on every call, at tenant, App membership, access profile, and scope entitlement, and writes the audit record before execution.

Per-user authorization on every call

In n8n, nodes authenticate with credentials stored in n8n and shared through projects, so downstream systems typically see the credential, not the person who triggered the run. In Pyrana, identity is explicit: an agent with its own identity, an agent on behalf of a user, or a workflow as a service principal, all through the same authorization path. The user's own principal passes through to Snowflake and Databricks row-level security, and unauthorized things read as absent.

Operations

Both products run durable, long-lived work. n8n offers queue mode for scaling workers (Business and above), wait nodes, and execution logs, and its 2.x releases added OpenTelemetry support for AI Agent telemetry. Pyrana's workflows run on Temporal workers: a run waiting for an approval survives a restart or deploy and resumes, and every run's traces, tokens, and tool errors are available as JSON.

Change control

n8n 2.0 separates Save from Publish, and Business and Enterprise plans add Git-backed environments. In Pyrana, push compiles the App configuration into an immutable version without activating it; activation moves the active pointer, is audited, and requires an App owner; rollback is an activation of a prior version.

Cost structure

n8n prices by monthly workflow executions, regardless of how many steps a workflow has. Cloud Starter and Pro are low monthly fees; Business is self-hosted with SSO and environments; Enterprise is quoted. The Community Edition is free to self-host. Pyrana is enterprise platform pricing; the cost to compare is the platform plus the application work on each side.

With clean data available, a Pyrana application typically takes about a week to stand up, with the frontend experience as the main effort. A first engagement, including SSO, access profiles, the approval policy, and loading the policy library into cortIQ, runs about six weeks. On n8n, a first automation can run the same day; the effort grows with the application layer you build around it.

What it takes to ship the same application

The reference application: a person or agent drafts a purchase request; amounts above a threshold need a finance approver; the request waits durably for the decision; everything is recorded.

Using them together

n8n is a capable integration layer, and many enterprises already run it. An n8n workflow can call a Pyrana App through its API or App MCP server as a service principal; that call passes the same gate as a person's. In the other direction, a Pyrana agent can call an n8n workflow exposed as a REST webhook or MCP tool, with the call admitted and audited on the Pyrana side. A practical split: n8n moves data and handles routine notifications, and Pyrana holds the application, the approvals, and the record.

When not to choose Pyrana

• You need to connect a few SaaS tools this week, and the workflow is the whole deliverable.
• Your builders are a small technical team who want to own every flow on a canvas and self-host for free.
• There are no consequential actions to approve and no outputs anyone will audit later.
• You are standardizing on SAP Joule Studio and want the embedded n8n environment it provides.