TypeSafe AI for n8n
Use Jev decisions inside an n8n workflow
Implementation and evidence →JEV GUIDE
Jev n8n integration: community nodes and email routing
In n8n, Jev can evaluate upstream data and return a typed answer for a branch. This guide provides a field-mapping and workflow design, not an untested importable workflow.
Check the community node and its environment
The collected n8n-nodes-typesafe-ai package is a community integration. Its pinned documentation limits availability to self-hosted instances until n8n verification and uses a TypeSafe AI API credential. Check current n8n and package compatibility before installing.
Map upstream fields to Choice and a branch
An editorial email-routing design is: test fixture → keep message ID, subject and body → TypeSafe Ask Choice → Switch → a results table. Start with a logging destination and connect business actions only after checking the branches.
Possible options are invoice, general and needs_review, each with a clear definition. Keep the API key out of State and avoid sending attachments or contact fields that the decision does not require.
| Setting | What to check |
|---|---|
| State | Expressions resolve to the intended text or JSON |
| Ask Choice + Simplify | Actual choice and confidence field locations |
| Evaluate Questions | Answers are nested under answers; use a different mapping |
| Switch fallback | Missing, unknown or uncertain answers reach review |
What does the email example actually do?
Jev Email Intent Workflow demonstrates mock-email routing in LangGraph. Its intent design is relevant, but it is not an n8n template. The reviewed handlers update destination state rather than sending email or paying invoices, and lack a separate low-confidence human branch.
Handle retries, failures and duplicate execution
The community node documentation delegates retries to n8n settings. Editorial recommendation: bound attempts and total waiting time, separate API failures from uncertain answers, and preserve message IDs to prevent duplicate downstream actions.
Use fictional invoices, general requests, mixed intents, empty messages and API failures. Inspect each actual JSON output and branch. A successful node execution does not establish correct classification. We have not installed the node or called the live API.
Explore these projects next
Jev Email Intent Workflow
Route email intent through a LangGraph branch
Implementation and evidence →Continue reading
02 / JEV GUIDE
Jev API quickstart: send and validate your first request
Build a Jev API request with state, typed questions and Bearer authentication. Download a JSON fixture and review response checks.
Read guide →06 / JEV GUIDE
Jev text classification and task routing: labels to fallbacks
Design Jev Choice classification with distinct labels, unknown inputs and review paths, then explore model-routing and semantic-filtering projects.
Read guide →09 / JEV GUIDE
Jev content moderation: Discord spam detection and false positives
Use Jev to assess messages while the application decides whether to allow, review or act. Explore Discord moderation rules, thresholds and failure handling.
Read guide →