Find Fiber AI Reference Values with AI

Identify the names and codes that fit your supplied classification.

What to Ask Leina to Do with Fiber AI

Copy a prompt, add your details, and send it to Leina in your connected team chat.

Retrieve a reference dataset and identify entries relevant to supplied labels.

Read Fiber AI reference dataset [industries, regions, skills or other dataset]. Match [supplied labels] to relevant entries, preserving the names and any identifiers present. For subdivisions use country code [code], and flag ambiguous matches.

Get Started with Fiber AI

  1. Connect Your Account

    Connect with a Fiber AI API key.

  2. Try a Task

    Tell Leina what you need in your team chat. Include the source, destination, and expected result.

    Set Up Leina in Your Chat →
  3. Check the Result

    Review the result and any changes in the connected app.

Supported Fiber AI Capabilities

Read reference datasets such as industries, regions, skills and technologies. AI can locate relevant entries and explain possible matches; organization credits and rate limits can also be inspected separately.

Reference datasets

Retrieve classification and location values for matching or input preparation.

Account usage metadata

Inspect organization credit, pricing and rate-limit metadata.

View All 3 Actions
  • Get Org Credits
  • Get Rate Limits
  • List Enum Values

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Frequently Asked Questions

Which reference categories can I look up?

Available categories include industries, NAICS codes, regions, subdivisions, languages, skills, technologies and time zones, alongside other defined reference sets.

What is needed for subdivisions?

Select the subdivisions dataset and supply the country’s two- or three-letter code.

Does a matching label guarantee an exact classification?

Compare the returned entries with your source meaning. Keep ambiguous labels unresolved instead of forcing a code assignment.

Your AI employee for Fiber AI

Tell Leina what you need in your team chat. Include the source, destination, and expected result.