The Best Data Enrichment APIs (2026)

An enrichment API is something you build on. Your signup flow, your lead scoring, or your warehouse sync.

Four things matter:

• A stateless, idempotent contract: send records, get enriched records back. Ask the same question twice, get the same answer.
• Versioned, typed endpoints, so what your code calls today means the same thing next year.
• A sandbox. Enrichmnet data is expensive and you don't want to burn credits during testing.
• Coverage beyond one dataset, billed only when there's a result.

Quick comparison

Every dataset has gaps. A waterfall that asks several providers in order fills them:

pipe0

pipe0 is a stateless, idempotent data API over 50+ providers. Every enrichment is a pipe with a versioned ID and fixed inputs and outputs. Here is a work email from a LinkedIn URL:

import { Pipe0 } from "@pipe0/client";

const pipe0 = new Pipe0({ apiKey: process.env.PIPE0_API_KEY });

const result = await pipe0.pipes.pipe({
  pipes: [
    {
      pipe_id: "person:workemail:profileurl:waterfall@1",
    },
  ],
  input: [
    {
      id: "1",
      profile_url: "https://www.linkedin.com/in/jane-doe",
    },
  ],
});
console.log(result);

import requests

response = requests.post(
    "https://api.pipe0.com/v1/pipes/run/sync",
    headers={"Authorization": f"Bearer {API_KEY}"},
    json={
        "pipes": [
            {
                "pipe_id": "person:workemail:profileurl:waterfall@1",
            },
        ],
        "input": [
            {
                "id": "1",
                "profile_url": "https://www.linkedin.com/in/jane-doe",
            },
        ],
    },
)
print(response.json())

curl -X POST "https://api.pipe0.com/v1/pipes/run/sync" \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "pipes": [
    {
      "pipe_id": "person:workemail:profileurl:waterfall@1"
    }
  ],
  "input": [
    {
      "id": "1",
      "profile_url": "https://www.linkedin.com/in/jane-doe"
    }
  ]
}'

The waterfall bills only the provider that answered. Its order is yours to change: pass a providers list in the pipe's config to pick which providers it asks, and in what sequence. Set config.environment to "sandbox" and the same call returns mock data for free.

Pipes also decide, branch, and write to other systems, so a whole automation fits in one request.

People Data Labs

People Data Labs sells person and company records from one large dataset, through APIs and CSV enrichment. It's a good fit when you want raw records at volume and plan to build the logic around them yourself. Coverage is whatever the one dataset has.

Crustdata

Crustdata keeps its people and company data fresh by re-verifying it continuously, and adds live signals like hiring and funding. Pick it when freshness matters more than breadth. It's also one of the providers inside pipe0's waterfalls.

Four more, quickly

• Apollo: its API exposes the same database as the app. Useful if your team already lives in Apollo.
• Hunter: finds and verifies emails from a name and a domain. Simple, well documented, and narrow.
• FullEnrich: an email and phone waterfall over 20+ vendors. Requests are asynchronous, with results by webhook.
• LeadMagic: low prices for emails and mobiles, and you only pay for valid results. Coverage is thin on its own.

What about Clay?

Clay's API is a remote control for the Clay workspace. It triggers tables, functions, and workflows that live in Clay, but it isn't a data API you can build a product on. More in Clay vs pipe0 for developers.

How to choose

If you need raw records at volume, start with People Data Labs or Crustdata. If you only need emails, Hunter or LeadMagic will do. If enrichment is part of your product or your pipeline, pick a data API with a waterfall and a sandbox, and start with pipe0.

Prospecting for an SDR team is a different job; see the best SDR APIs for lead generation.