Fiber.ai

Fiber.ai is a B2B data platform with fresh data on 40M+ companies, 850M+ people, and 30M+ jobs. Search live company, people, and job data, and enrich incomplete records with work emails, personal emails, and phone numbers. Attach fiber to an Exa Agent run through Exa Connect, and the agent queries Fiber.ai alongside Exa web search.

Use it for

Cleaning up a CRM by reverse-looking-up a work or personal email to a person, or enriching a partial company/person record.
Tracking real-time LinkedIn signals: job changes, promotions, new jobs, headcount changes, and fundraising.
Finding relevant posts across LinkedIn, X, Instagram, TikTok, Reddit, and YouTube, pulling their comments and reactions, then enriching the authors’ contact info.
Searching across 40M+ companies and 850M+ people and enriching prospects with work email, personal email, and phone numbers.

Provider ID

Use this value in dataSources:

fiber

Pricing

Fiber.ai bills in credits at $0.02 / credit, and each call is charged the credits Fiber reports for it:

Operation	Credits
Search	2 + 1 per result returned
Company lookup	~2 per candidate returned
Person lookup / email reverse lookup	2
Contact reveal	2 (work email) – 5 (phone)

Calls that return no match (or whose charge Fiber refunds) are free. Parameter choices change the price: a company lookup’s numResults sets how many candidates you pay for, and a search’s result count drives most of its cost.

Example

Build a B2B prospecting list of Series A fintech companies in New York with 50–200 employees.

from exa_py import Exa

exa = Exa()
run = exa.agent.runs.create(
    query="I'm building a B2B sales prospecting list using a B2B company database. Find Series A fintech companies in New York with 50-200 employees, and for each return the company's LinkedIn profile, domain, employee count, and funding stage.",
    data_sources=[{"provider": "fiber"}],
    output_schema={
        "type": "object",
        "required": ["companies"],
        "properties": {
            "companies": {
                "type": "array",
                "maxItems": 10,
                "items": {
                    "type": "object",
                    "required": ["name", "domain", "employeeCount", "fundingStage"],
                    "properties": {
                        "name": {"type": "string"},
                        "domain": {"type": "string"},
                        "employeeCount": {"type": "number"},
                        "fundingStage": {"type": "string"},
                    },
                },
            }
        },
    },
)
run = exa.agent.runs.poll_until_finished(run.id)

import Exa from "exa-js";

const exa = new Exa();
const run = await exa.agent.runs.create({
  query: "I'm building a B2B sales prospecting list using a B2B company database. Find Series A fintech companies in New York with 50-200 employees, and for each return the company's LinkedIn profile, domain, employee count, and funding stage.",
  dataSources: [{ provider: "fiber" }],
  outputSchema: {
    type: "object",
    required: ["companies"],
    properties: {
      companies: {
        type: "array",
        maxItems: 10,
        items: {
          type: "object",
          required: ["name", "domain", "employeeCount", "fundingStage"],
          properties: {
            name: { type: "string" },
            domain: { type: "string" },
            employeeCount: { type: "number" },
            fundingStage: { type: "string" },
          },
        },
      },
    },
  },
});

curl -s -X POST "https://api.exa.ai/agent/runs" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $EXA_API_KEY" \
  -d '{
    "query": "I'\''m building a B2B sales prospecting list using a B2B company database. Find Series A fintech companies in New York with 50-200 employees, and for each return the company'\''s LinkedIn profile, domain, employee count, and funding stage.",
    "dataSources": [{ "provider": "fiber" }],
    "outputSchema": {
      "type": "object",
      "required": ["companies"],
      "properties": {
        "companies": {
          "type": "array",
          "maxItems": 10,
          "items": {
            "type": "object",
            "required": ["name", "domain", "employeeCount", "fundingStage"],
            "properties": {
              "name": { "type": "string" },
              "domain": { "type": "string" },
              "employeeCount": { "type": "number" },
              "fundingStage": { "type": "string" }
            }
          }
        }
      }
    }
  }'

Pairs well with

Similarweb: size up a prospect’s web presence and competitors.
Baselayer: verify officers and registrations for shortlisted US businesses.
Particle: find what podcasts are saying about a company or executive.

Next steps

Attach it to a run

The Exa Connect quickstart covers dataSources, pricing, and the full partner catalog.

Combine providers

Attach up to five partners to one run and shape the query so each one fires.

Learn Exa Agent

Create runs, stream progress, design output schemas, and control effort and cost.

Get an API key

Create a key in the dashboard and run this page’s example as-is. New accounts start with free credits.

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Example

Pairs well with

Next steps