Company Enrichment API: Enrich Any Domain With Signals

Quickstart: Your First Enrichment Call

curl -X POST "https://signals.autobound.ai/v1/companies/enrich" \
  -H "X-API-KEY: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "domain": "stripe.com",
    "limit": 5
  }'

A response looks like this (trimmed to a few signals for readability):

{
  "company": {
    "name": "Stripe",
    "domain": "stripe.com",
    "linkedin_url": "https://linkedin.com/company/stripe",
    "industries": [],
    "employee_count_low": 0,
    "employee_count_high": 0
  },
  "signals": [
    {
      "signal_id": "sig_9f2a1c",
      "signal_type": "news",
      "signal_subtype": "companyNews",
      "signal_name": "",
      "detected_at": "2026-06-28T14:02:00Z",
      "association": "company",
      "company": { "name": "Stripe", "domain": "stripe.com" },
      "contact": null,
      "data": {
        "summary": "Stripe expanded stablecoin payment support across 100+ countries.",
        "url": "https://stripe.com/newsroom/news",
        "title": "Stripe expands stablecoin payments"
      }
    },
    {
      "signal_id": "sig_71b0e4",
      "signal_type": "hiring-trends",
      "signal_subtype": "departmentGrowth",
      "signal_name": "",
      "detected_at": "2026-06-21T00:00:00Z",
      "association": "company",
      "company": { "name": "Stripe", "domain": "stripe.com" },
      "contact": null,
      "data": {
        "summary": "Open engineering roles up sharply quarter over quarter."
      }
    },
    {
      "signal_id": "sig_44c8aa",
      "signal_type": "github",
      "signal_subtype": "release",
      "signal_name": "",
      "detected_at": "2026-06-18T09:30:00Z",
      "association": "company",
      "company": { "name": "Stripe", "domain": "stripe.com" },
      "contact": null,
      "data": {
        "summary": "New major release published to a public Stripe repository."
      }
    }
    // ...2 more signals (limit was 5)
  ],
  "signal_summary": {
    "news": 2,
    "hiring-trends": 1,
    "github": 1,
    "product-reviews": 1
  },
  "coverage": {
    "total_before_filters": 63,
    "total_after_filters": 63,
    "signal_types_available": [
      "news", "hiring-trends", "github",
      "product-reviews", "financials", "seo-traffic"
    ],
    "date_range": {
      "earliest": "2025-08-14T00:00:00Z",
      "latest": "2026-06-28T14:02:00Z"
    }
  }
}

The 32 Signal Types — and How to Filter Them

A filtered call — only funding, news, and hiring, only since May 1st:

curl -X POST "https://signals.autobound.ai/v1/companies/enrich" \
  -H "X-API-KEY: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "domain": "stripe.com",
    "signal_types": ["news", "sec-form-d-funding", "hiring-trends"],
    "detected_after": "2026-05-01T00:00:00Z",
    "limit": 50
  }'

Legacy SEC slugs (10k, 10q, 8k) and other registered aliases resolve server-side to their canonical values, so an old integration won't silently break. For what each family of signals means for outreach, see the trigger events guide plus our hiring signals and SEC filings breakdowns.

Three Patterns Teams Ship in a Day

Pattern 1: A clean single-domain helper

The building block for everything else. Note the 404 handling (free, not an error worth retrying) and the fallback chain for rendering a signal title.

import requests

API_KEY = "YOUR_API_KEY"
URL = "https://signals.autobound.ai/v1/companies/enrich"

def enrich(domain, signal_types=None, detected_after=None, limit=50):
    body = {"domain": domain, "limit": limit}
    if signal_types:
        body["signal_types"] = signal_types
    if detected_after:
        body["detected_after"] = detected_after

    resp = requests.post(
        URL,
        headers={"X-API-KEY": API_KEY, "Content-Type": "application/json"},
        json=body,
        timeout=30,
    )

    if resp.status_code == 404:
        return None  # no signals for this company — you were not charged
    resp.raise_for_status()

    # Credit accounting lives in the response headers
    print("charged:", resp.headers.get("x-credits-charged"),
          "remaining:", resp.headers.get("x-credits-remaining"))
    return resp.json()

data = enrich("stripe.com", signal_types=["news", "hiring-trends"])
for s in (data or {}).get("signals", []):
    # signal_name is often empty — fall back to subtype or data.summary
    title = s.get("signal_name") or s.get("signal_subtype") or s["data"].get("summary")
    print(s["signal_type"], s["detected_at"], "-", title)

Pattern 2: “Bulk” enrichment by parallelizing

There's no batch endpoint, so enrich a CSV by running single calls concurrently while respecting the 300/minute limit. This handles 429 with the Retry-After header and skips unmatched domains for free.

import concurrent.futures as cf
import csv, time, requests

API_KEY = "YOUR_API_KEY"
URL = "https://signals.autobound.ai/v1/companies/enrich"
# Account limit is 300 requests/minute. A handful of workers with a small
# delay keeps you comfortably under it.
MAX_WORKERS = 4

def enrich(domain):
    resp = requests.post(
        URL,
        headers={"X-API-KEY": API_KEY, "Content-Type": "application/json"},
        json={"domain": domain, "detected_after": "2026-01-01T00:00:00Z"},
        timeout=30,
    )
    if resp.status_code == 429:
        time.sleep(int(resp.headers.get("Retry-After", "5")))
        return enrich(domain)
    if resp.status_code == 404:
        return domain, None  # unmatched — free
    resp.raise_for_status()
    return domain, resp.json()

with open("accounts.csv") as f:
    domains = [row["domain"] for row in csv.DictReader(f)]

results = {}
with cf.ThreadPoolExecutor(max_workers=MAX_WORKERS) as pool:
    for domain, payload in pool.map(enrich, domains):
        results[domain] = payload
        time.sleep(0.2)  # ~5 req/sec ceiling

matched = sum(1 for v in results.values() if v)
print(f"Enriched {matched}/{len(domains)} domains")

Pattern 3: CRM auto-enrichment on lead creation

When a lead enters Salesforce or HubSpot, a webhook enriches the account and writes the freshest signal plus a type breakdown back to the record. Reps open the account and immediately see what's happening.

// CRM webhook: enrich an account when a new lead is created
async function onLeadCreated(lead) {
  const resp = await fetch("https://signals.autobound.ai/v1/companies/enrich", {
    method: "POST",
    headers: {
      "X-API-KEY": process.env.AUTOBOUND_KEY,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({
      domain: lead.company_domain,
      detected_after: "2026-01-01T00:00:00Z",
      limit: 25,
    }),
  });

  if (resp.status === 404) return; // no signals, nothing to write
  const { signals, signal_summary } = await resp.json();

  // Write the freshest signal + a type breakdown back to the account record
  const top = signals[0];
  await crm.updateAccount(lead.account_id, {
    latest_signal: top?.data?.summary ?? top?.signal_subtype ?? "None",
    latest_signal_at: top?.detected_at ?? null,
    signal_types: Object.keys(signal_summary).join("; "),
    signal_count: signals.length,
  });
}

Bonus: an agent tool for AI SDRs

The same endpoint is exposed through Autobound's MCP server, so an AI SDR can call enrichCompany as a tool, pull the freshest signal, and use data.summary as the personalization hook before a message ever sends. That's the difference between generic personalization and something specific, timely, and sourced — more on that in why AI SDR platforms need a signal data layer.