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Import data with Assist

You'll learn how to: Use Assist to upload a CSV file, auto-map columns, review duplicates, and bulk-import contacts or companies.

Time: 5-10 minutes.

Prereqs: Run an Assist workflow. A CSV file ready to import (contacts, companies, or activity data).

About the Import Data workflow

Assist's Import Data workflow handles the heavy lifting:

  • You upload a CSV.
  • Assist reads the file and previews the first few rows.
  • Assist maps your CSV columns to Nynch fields automatically.
  • Assist flags potential duplicates in your existing network.
  • You review and approve the mapping and dedup decisions.
  • Assist imports the data in one step.

Steps

  1. Open Assist (green sparkle in the sidebar or floating button).
  2. Click New chat.
  3. In the WORKFLOWS row, click Import Data.
  1. Click Upload CSV (or drag a file into the upload zone).

Select your file. The file size limit and accepted formats are .

  1. Assist previews the first few rows of your file.
  1. Review the Column Mapping section.

Assist shows a table:

Your CSV Column Nynch Field Confidence
first_name Contact First Name High
email_address Email High
role Contact Title Medium
company_name Company Name High

Verify each mapping. If Assist got a column wrong (e.g., mapped "role" to "Department" instead of "Title"):

  • Click the Nynch Field dropdown for that row.
  • Pick the correct field from the list.
  • Assist re-scores confidence as you adjust.

Fields marked "Low" confidence should be double-checked. If a column has no matching Nynch field, Assist offers to skip it or store it as a custom note.

  1. Review the Duplicate Detection section.

Assist compares incoming rows against your existing contacts. It flags potential matches by email, name, or company.

Example:

CSV Row Potential Match Action
john@acme.com John Smith (existing contact) Skip this row / Import as new
jane@abc.io New record Import as new

For each flagged row:

  • Skip this row = don't import (use if it's a true duplicate).
  • Import as new = add it anyway (use if it's a different person with a similar name).
  • Merge = combine it with the existing record.
  1. Click Review & Import.

Assist shows a summary:

  • X rows will be imported as new contacts.
  • Y rows will be skipped (duplicates).
  • Z rows will merge with existing records.
  1. Click Confirm Import.

The import runs. Assist logs progress and shows a completion message when done.

Your new data is now live in your network.

For manual imports or more control

If you need finer dedup control or prefer a step-by-step import, see CSV import step by step.

Tips

  • Clean your CSV first: Remove blank rows, fix typos in headers, and ensure emails are unique within the file. Assist catches most issues, but cleaner input = faster imports.
  • Start small: If you're importing 1000+ rows, try a test batch (100 rows) first. This helps you catch mapping mistakes before importing everything.
  • Use consistent company names: If your CSV says "Acme Inc" and your network says "Acme Incorporated," Assist may not recognize the duplicate. Standardize company names in your CSV before importing.

If something goes wrong

  • Symptom: "Upload fails with 'File too large.'" → Fix: Split your CSV into smaller batches (500-1000 rows each) and import separately.
  • Symptom: "Column mapping shows 'Unmapped' for important columns." → Fix: Click the dropdown for that row and pick the matching Nynch field. If no match exists, you can store the data as a custom contact note.
  • Symptom: "Assist flagged too many rows as duplicates." → Fix: Review the flagged rows. If they are truly different (e.g., two people at the same company), click Import as new for each. You can deduplicate later manually if needed.
  • Symptom: "Import completed but some rows are missing." → Fix: Check Assist's completion message for rows that failed validation (e.g., rows with no email or name). Assist logs these in the import summary. Correct the source CSV and re-import those rows.

Related: CSV import step by step | Run an Assist workflow | Finding and fixing duplicates.