Core

Users

User directory: identity, contact, role, and onboarding metadata.

low riskusers_v1

Schema

Fields

7 canonical fields with multilingual hints and field-level validators. Any source column that resolves to one of these is mapped automatically by the cascade.

ColumnTypeRequiredHints / validators
idstringyes
emailemailyese-mail · mail · correo · courriel · email
first_namestringvorname · prenom · prénom · nombre
last_namestringnachname · nom · apellido · cognome
roleenumrolle · role · rol · ruolo
created_atdate
countrystringland · pays · país · paese

Sample

Example data

8 rows, DE headers, role enum. Fully synthetic — safe to share, commit, and run in CI.

Download the fixture and drop it into the Workbench, or POST it straight to the API to watch the cascade resolve a real, deliberately-messy header row.

users_sample.csv
template
users_v1

Try it

Use it

Map a file to this template with one call. The cascade resolves most columns for free on the deterministic layers; only the leftovers reach the metered LLM.

REST

POST the file with template=users_v1 to /v1/uploads. Schema-only mode sends only headers plus a few clamped sample rows; full-data mode runs row-level AI in-region under a BAA and spends a few tokens per map from your prepaid wallet.

curl
curl -X POST https://api.adaptivmapr.com/v1/uploads \
  -H "Authorization: Bearer $ADAPTIVMAPR_API_KEY" \
  -F "file=@users_sample.csv" \
  -F "template=users_v1"
Model Context Protocol

Drop AdaptivMapr into Cursor or Claude Desktop and call the same cascade as an MCP tool. Schema-only calls leave only column names and a few clamped samples — a data-minimization mode by design.

mcp
adaptivmapr.match_headers({
  template: "users_v1",
  headers: ["first_name", "last_name", /* ... */]
})
MCP install instructions →

Ready when you are

Put users in production — without shipping raw records.

Spin up a key in minutes. Schema-only mapping runs on the free deterministic cascade; a $10 prepaid wallet covers the metered layer when you need it.

Schema-only is a data-minimization mode · a few tokens per map
Users — AdaptivMapr