New Business Signal Scout

New Business Signal Scout turns selected official public business registration and license datasets into normalized, scored new-business opportunity signals.

It reads structured government open-data sources, normalizes source-specific records into one schema, applies deterministic scoring, and returns records with vendor-need tags, score reasons, risk flags, source health, and a run summary.

The Actor uses public structured sources only. It does not enrich contacts, find emails, verify phone numbers, send outreach, sync CRMs, or claim verified buyer intent.

What It Does

• Fetches recent public business registration and license records from selected official sources.
• Normalizes source-specific fields into a consistent record shape.
• Tags likely vendor needs such as bookkeeping, local SEO, insurance, POS/payments, signage, security, cleaning, restaurant suppliers, contractor services, and professional services.
• Scores records by freshness, vendor-need category fit, completeness, and source confidence.
• Returns ranked new-business opportunity signals with score reasons and risk flags.
• Produces a run summary with per-source health and aggregate counts.

Who It Is For

• Local B2B service providers looking for newly registered or recently licensed businesses.
• Agencies building manual research lists around new local businesses.
• Payroll, bookkeeping, insurance, POS/payments, signage, cleaning, and security providers.
• Market researchers and data buyers who need normalized public business activity feeds.
• Operators who want selected official-source signals without contact enrichment or automated outreach.

Supported Sources

source id	source	type	dataset
chicago_business_licenses	Chicago Business Licenses	city business license	uupf-x98q
nyc_legally_operating_businesses	NYC Legally Operating Businesses	city business license	w7w3-xahh
oregon_recent_business_registrations	Oregon Recent Business Registrations	state business registry	esjy-u4fc
colorado_business_entities	Colorado Business Entities	state business registry	4ykn-tg5h
texas_business_entities	Texas Business Entities	state business registry	2vfr-72e4

What It Does Not Do

• It does not find emails.
• It does not verify phone numbers.
• It does not enrich owners, decision makers, domains, LinkedIn profiles, or contacts.
• It does not send outreach.
• It does not create ready-to-email lists.
• It does not sync CRMs.
• It does not claim verified buyer intent.
• It does not currently cover every state, city, or business registry.
• It does not use AI scoring in the MVP.
• It does not provide legal, compliance, tax, or business advice.

New Business Signal Scout provides public-record opportunity signals, not verified sales leads.

Example Use Cases

• Find recently licensed restaurants that may need POS, payroll, signage, local SEO, cleaning, security, or supplier services.
• Monitor newly registered LLCs and corporations in supported state registries.
• Compare recent new-business activity across selected public sources.
• Build an internal research workflow around newly visible businesses.
• Pull source-health summaries to check whether selected feeds are returning usable records.

Input Fields

field	type	default	description
sources	string array	all supported sources	Official public sources to query.
daysBack	integer	30	Return records whose primary event date is within this many days. Accepted range: 1-365.
states	string array	none	Optional state filters where source fields support state-level filtering.
cities	string array	none	Optional city filters where source fields support city-level filtering.
categories	string array	none	Optional text filters for license, entity, category, or activity fields.
entityTypes	string array	none	Optional entity/license type filters.
includeExpansionSources	boolean	false	Reserved for later source additions. MVP supports the five default sources only.
maxResultsPerSource	integer	100	Maximum normalized records to fetch per selected source. Accepted range: 1-5000.
minOpportunityScore	number	none	Optional minimum deterministic opportunity score.
includeRawRecord	boolean	false	Include the original source row on each normalized record.

Example Input

{
  "sources": [
    "chicago_business_licenses",
    "nyc_legally_operating_businesses",
    "oregon_recent_business_registrations",
    "colorado_business_entities",
    "texas_business_entities"
  ],
  "daysBack": 90,
  "maxResultsPerSource": 100,
  "minOpportunityScore": 60,
  "includeRawRecord": false
}

More examples are in examples/.

Output Fields

Each output record follows this normalized shape:

field	description
signalId	Deterministic signal ID derived from the source and source record.
sourceId	Source ID selected from the supported source list.
sourceName	Human-readable source name.
sourceType	Source type, such as city business license or state business registry.
sourceRecordId	Stable record identifier from the source when available.
sourceUrl	Source API or record URL when available.
businessName	Normalized business/entity name.
tradeName	DBA/trade name when available.
entityType	Entity or license type when available.
licenseType	License type when available.
category	Normalized category/activity field when available.
activityDescription	Source activity description when available.
status	Source status when available.
eventDate	Normalized ISO event date when available.
eventDateType	Meaning of the event date, such as issued date or registration date.
address	Normalized address when available.
city	City when available.
state	State when available.
zip	ZIP/postal code when available.
latitude / longitude	Coordinates when the source provides them.
vendorNeedTags	Deterministic category tags for likely B2B vendor needs.
scoreReasons	Concise reasons explaining the score.
riskFlags	Missing/ambiguous/stale/source-link flags.
observedAt	Runtime timestamp when the record was observed.
freshnessScore	0-100 event-date freshness score.
categoryFitScore	0-100 vendor-need category match score.
completenessScore	0-100 required-field completeness score.
sourceConfidenceScore	0-100 source-confidence score.
opportunityScore	Weighted deterministic opportunity score rounded to one decimal.
rawRecord	Optional original source row when includeRawRecord is true.

Example Output

{
  "signalId": "nbs_76419521ea2c8f3e5d95",
  "sourceId": "chicago_business_licenses",
  "sourceName": "Chicago Business Licenses",
  "sourceType": "city_business_license",
  "sourceRecordId": "3085203",
  "sourceUrl": "https://data.cityofchicago.org/resource/uupf-x98q.json",
  "businessName": "CHDG PHASE 1A1 SUB-LESSEE, LLC",
  "tradeName": "HYATT HOUSE/HYATT PLACE AND FOOD CT",
  "entityType": "Retail Food Establishment",
  "licenseType": "Retail Food Establishment",
  "category": "Preparation of Food and Dining on Premises With Seating",
  "activityDescription": "Preparation of Food and Dining on Premises With Seating",
  "status": "AAI",
  "eventDate": "2026-05-22",
  "eventDateType": "date_issued",
  "address": "1835 W HARRISON ST",
  "city": "CHICAGO",
  "state": "IL",
  "zip": "60612",
  "vendorNeedTags": [
    "commercial_cleaning",
    "payroll_or_bookkeeping",
    "pos_or_payments",
    "restaurant_supplier",
    "security",
    "signage_or_print",
    "website_or_local_seo"
  ],
  "freshnessScore": 100,
  "categoryFitScore": 100,
  "completenessScore": 100,
  "sourceConfidenceScore": 95,
  "opportunityScore": 99.2,
  "scoreReasons": [
    "fresh record",
    "strong vendor-need category",
    "complete public record",
    "official structured source with stable identifier"
  ],
  "riskFlags": [
    "source_record_without_row_url"
  ]
}

This is a real output-shape example from a public dataset sample. It is not a verified sales lead and does not include contact enrichment.

Run Summary

The Actor writes a RUN_SUMMARY key-value store record with:

• totalRecordsFetched
• totalRecordsReturned
• recordsBySource
• recordsByState
• recordsByCategory
• recordsByFreshnessBand
• averageOpportunityScore
• topVendorNeedTags
• sourceHealth
• warnings

examples/run_summary_sample.json shows the expected shape.

Scoring Model

The MVP uses deterministic scoring only:

opportunityScore =
  freshnessScore * 0.35 +
  categoryFitScore * 0.25 +
  completenessScore * 0.25 +
  sourceConfidenceScore * 0.15

opportunityScore is rounded to one decimal.

Freshness score:

• 0-7 days old: 100
• 8-30 days old: 80
• 31-90 days old: 50
• 91-365 days old: 20
• 366+ days old: 0
• missing or invalid date: 0
• future date: 50

Category fit score:

• Strong vendor-need category: 100
• Matched vendor-need category: 80
• Generic business category: 45
• Missing usable category: 10

Completeness score:

• +20 business name
• +20 event date
• +20 category/entity/license type
• +20 location
• +20 stable source ID

Source confidence score:

• Starts at 85
• +5 for state business registry sources
• +5 for stable source record ID
• +5 for source URL
• Capped at 100

Current Validation Status

Local sampling and private Apify validation have passed across all five MVP sources.

• AF-010 private Apify validation passed on build 0.1.3 with five returned records and all five sources healthy.
• AF-011 larger local sample passed with 50 returned records, 10 per source, all five sources healthy, and no warnings.
• AF-013 capped private Apify validation passed on build 0.1.4 with 50 returned records, 10 per source, all five sources healthy, no raw records, and no top-level warnings.

The Actor is launched as a public-source signal product. It returns normalized opportunity signals from selected official sources; it does not provide verified contact data or automated outreach.